Medicine, Faculty of
Population and Public Health (SPPH), School of
DSpace
UBCV
McLeod, Kim Vanessa
Doctor of Philosophy - PhD
University of British Columbia
The impact of regulatory inspections of workplace safety on injury rates in British Columbia (BC), Canada is examined in this dissertation. Previous studies of the effect of inspections relied on theoretical frameworks that were non-existent, overly simplified, or reliant on economics and rational choice theory while neglecting the contributions of academic disciplines such as organizational theory. In Chapter 2, the theories of the elements of a successful inspection are examined and incorporated into a framework to understand how inspections may or may not work to reduce injury rates. Results of studies of inspections differ by jurisdiction, and even among studies within the same state, the effectiveness appears to change over time. The details of the regulatory systems provided in published articles are generally limited, making it difficult to discern which differences between the jurisdictions may explain the varied results. In Chapter 3, studies of inspections in California, Washington, and Pennsylvania are examined in detail and publicly available data from safety inspections in those states are summarized. Combining the information from the studies and the results of that analysis, it was found that inspections with penalties may be effective in reducing injury rates, and inspections without penalties were not found to be effective. In British Columbia, penalties arising from inspections are rare, so inspections in general are not likely to be effective at reducing injuries. Chapter 4 is focused on finding the best method to analyze data from WorkSafeBC (The Workers Compensation Board of BC) to determine if inspections are linked to a decline in injury rates. Statistical methods used in previous studies of inspections and injuries and other analysis methods were examined. It was determined that either difference-in-differences analysis with coarsened exact matching or fixed effects analysis with or without matching would be appropriate. The dissertation concludes with Chapter 5, where matched fixed effects analysis is used to analyze WorkSafeBC data. It was found that inspections generally do not influence acute injuries, which supports the hypothesis that inspections at WorkSafeBC, where penalties are rare, will not be effective at decreasing injuries.
UNDERSTANDING REGULATORY WORKPLACE SAFETY INSPECTIONS IN BRITISH COLUMBIA, CANADA: THEORY AND EVALUATION by KIM VANESSA MCLEOD B.Sc., University of Alberta, 2000 J.D., University of British Columbia, 2005 M.Sc., University of British Columbia, 2009 A DISSERTATION SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Occupational and Environmental Hygiene) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) November 2019 © Kim Vanessa McLeod, 2019 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Understanding Regulatory Workplace Safety Inspections in British Columbia, Canada: Theory and Evaluation submitted by Kim McLeod in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Occupational and Environmental Hygiene. Examining Committee: Chris McLeod, Population and Public Health Co-supervisor Hugh Davies, Population and Public Health Co-supervisor Benjamin Amick, Public Health and Social Work, Florida International University Supervisory Committee Member Mike Law, School of Population and Public Health University Examiner Mark Thompson, Sauder School of Business University Examiner Additional Supervisory Committee Member: Mieke Koehoorn, Population and Public Health Supervisory Committee Member iii Abstract The impact of regulatory inspections of workplace safety on injury rates in British Columbia (BC), Canada is examined in this dissertation. Previous studies of the effect of inspections relied on theoretical frameworks that were non-existent, overly simplified, or reliant on economics and rational choice theory while neglecting the contributions of academic disciplines such as organizational theory. In Chapter 2, the theories of the elements of a successful inspection are examined and incorporated into a framework to understand how inspections may or may not work to reduce injury rates. Results of studies of inspections differ by jurisdiction, and even among studies within the same state, the effectiveness appears to change over time. The details of the regulatory systems provided in published articles are generally limited, making it difficult to discern which differences between the jurisdictions may explain the varied results. In Chapter 3, studies of inspections in California, Washington, and Pennsylvania are examined in detail and publicly available data from safety inspections in those states are summarized. Combining the information from the studies and the results of that analysis, it was found that inspections with penalties may be effective in reducing injury rates, and inspections without penalties were not found to be effective. In British Columbia, penalties arising from inspections are rare, so inspections in general are not likely to be effective at reducing injuries. Chapter 4 is focused on finding the best method to analyze data from WorkSafeBC (The Workers Compensation Board of BC) to determine if inspections are linked to a decline in injury rates. Statistical methods used in previous studies of inspections and injuries and other analysis methods were examined. It was determined that either difference-in-differences analysis with coarsened exact matching or fixed effects analysis with or without matching would be appropriate. The dissertation concludes with Chapter 5, where matched fixed effects analysis is used to analyze WorkSafeBC data. It was found that inspections generally do not influence acute iv injuries, which supports the hypothesis that inspections at WorkSafeBC, where penalties are rare, will not be effective at decreasing injuries. v Lay Summary Safety inspections of workplaces are an important part of ensuring that regulations designed to keep people safe are being followed. Inspections in Canada have not been well studied and this dissertation is the first to examine safety inspections in the Canadian province of British Columbia. Based on previous research, only inspections with penalties are effective in reducing workplace injury rates, while inspections without penalties are not. In British Columbia, penalties are rare, but orders that give instructions to an out-of-compliance employer to come into compliance by a certain date are common. Applying statistical analysis to 2004-2014 data provided by WorkSafeBC (the provincial workers’ compensation system), it was found that inspections in British Columbia generally do not lead to a decrease in injury rates. vi Preface This dissertation is my original work. The research question was part of the research program at the Partnership for Work, Health, and Safety (PWHS), a research unit at the University of British Columbia. The data extract was completed by a staff member of the PWHS. I performed data cleaning and linking procedures, and all statistical analysis. Human Ethics approval was provided by the UBC Behavioural Research Ethics Board, Certificate Number H12-02635. vii Table of Contents Abstract ....................................................................................................................... iii Lay Summary ................................................................................................................ v Preface ........................................................................................................................ vi Table of Contents ........................................................................................................ vii List of Tables ................................................................................................................xii List of Figures ............................................................................................................. xiv Glossary ..................................................................................................................... xvi Acknowledgements .................................................................................................... xix Dedication ................................................................................................................... xx Chapter 1: Introduction and Background ....................................................................... 1 1.1 Workplace Safety Inspections: An Introduction ...........................................................1 1.2 Study Justification ......................................................................................................3 Significance of inspections ........................................................................................................... 3 Need for research in this area ...................................................................................................... 5 1.3 Study Setting .............................................................................................................9 1.4 Study Objectives ........................................................................................................9 1.5 Research Questions ................................................................................................. 10 Can a practical model of workplace safety inspections be generated using theories from various disciplines? ................................................................................................................................. 10 Can a detailed look at past inspections help to inform this and future studies? ....................... 10 Considering previous research methods, and in review of current available methods, what is the most appropriate statistical approach to investigate the effect of workplace safety regulatory inspections on injury rates? .................................................................................................................... 11 viii Are workplace safety regulatory inspections associated with lower acute injury rates in British Columbia? Does the association vary by firm characteristics? ............................................................... 11 A Conceptual Framework of Inspections and Safety ................................ 13 2.1 Introduction ............................................................................................................ 13 2.2 Model ...................................................................................................................... 14 2.3 Legitimate Regulations and Agencies ........................................................................ 15 2.4 Crafting an Effective Regulatory Regime ................................................................... 17 Developing technically effective regulations ............................................................................. 18 2.5 An Effective Enforcement Regime ............................................................................. 25 Firm targeting ............................................................................................................................. 26 Quality and scope of inspection ................................................................................................. 29 2.6 Motivating Firms ...................................................................................................... 30 Motivating firms through Rational Choice Theory ..................................................................... 30 The deterrence model ................................................................................................................ 33 The compliance model ............................................................................................................... 35 Inspector discretion: responsive regulation ............................................................................... 37 2.7 Internalizing and Operationalizing the Results of Inspections in Organizations........... 40 Theoretical models of the firm ................................................................................................... 42 Compliance and safety in an organization: safety culture ......................................................... 45 2.8 Implementing Safety at the Worker Level ................................................................. 47 Power imbalance between workers and management ............................................................. 47 Individual workers ...................................................................................................................... 49 Organized labour ........................................................................................................................ 49 2.9 Discussion ................................................................................................................ 51 What does an inspection mean? Putting previous research in context .... 54 3.1 Introduction ............................................................................................................ 54 3.2 Background ............................................................................................................. 55 3.3 Occupational Health and Safety Regulators and Inspections in the United States ....... 56 ix 3.4 Summaries of previous studies ................................................................................. 60 California: Cal/OSHA and the 1996-2006 study ......................................................................... 61 Washington State: WISHA 1998-2008 study .............................................................................. 62 Pennsylvania: OSHA 1998-2005 study ....................................................................................... 64 Summary of previous studies results ......................................................................................... 65 3.5 Materials and Methods ............................................................................................ 67 3.6 Results ..................................................................................................................... 69 Inspections data ......................................................................................................................... 69 Citations and penalties ............................................................................................................... 70 Appeals and adjustments after the fact ..................................................................................... 72 Industries .................................................................................................................................... 74 3.7 Workplace Safety Regulatory Systems in Canada ...................................................... 74 WorkSafeBC prevention activities background .......................................................................... 75 Prevention activities across Canada ........................................................................................... 79 3.8 Discussion ................................................................................................................ 81 Choosing an Analysis Strategy for the Inference of Causal Effects ........... 85 4.1 Introduction ............................................................................................................ 85 4.2 Background ............................................................................................................. 85 4.3 The Challenge of Observational Studies .................................................................... 86 4.4 Approaches to analytical methods in previous studies .............................................. 88 Inspections at Pennsylvania manufacturing firms: Scholz-Gray change model ......................... 88 Washington State inspections: generalized estimating equations ............................................ 89 California randomized inspections: fixed effects with exact matching ...................................... 90 Inspections at Italian manufacturing plants: interrupted time series and survival analysis ...... 91 Certificate of recognition intervention study, British Columbia: matched difference-in-differences .............................................................................................................................................. 91 4.5 Model Selection ....................................................................................................... 92 Dealing with count nature of data ............................................................................................. 92 Dealing with longitudinal nature of data ................................................................................... 94 Dealing with Selection Bias ........................................................................................................ 96 x Discussion of models ................................................................................................................ 104 Model selection ........................................................................................................................ 106 4.6 Replication of Previous Studies .............................................................................. 108 Data description ....................................................................................................................... 108 Cohort, description, summary statistics and trends ................................................................ 109 Analyses .................................................................................................................................... 114 4.7 Results Comparing Analytical Methods of Previous Studies and Fixed Effects with Data from WorkSafeBC ............................................................................................................. 115 Difference method: Scholz-Gray and Haviland et al. ............................................................... 115 Generalized estimating equations: Foley, Baggs, Silverstein ................................................... 115 Fixed effects: Levine et al. ........................................................................................................ 116 Matched difference-in-differences .......................................................................................... 117 4.8 Discussion .............................................................................................................. 117 The Effect of Regulatory Inspections on Workplace Injury Rates in British Columbia ............................................................................................................ 121 5.1 Introduction .......................................................................................................... 121 5.2 Background ........................................................................................................... 121 5.3 WorkSafeBC Prevention and Enforcement Activities ............................................... 122 5.4 Methods and Materials .......................................................................................... 124 Data source and sample definition .......................................................................................... 124 Outcome and treatment variables ........................................................................................... 125 Variables ................................................................................................................................... 127 Matching .................................................................................................................................. 128 Statistical analysis..................................................................................................................... 128 5.5 Results ................................................................................................................... 129 Cohort creation and descriptive statistics ................................................................................ 129 Matching results ....................................................................................................................... 132 Model results ........................................................................................................................... 133 5.6 Discussion .............................................................................................................. 145 xi Strengths and limitations ......................................................................................................... 147 Overall Conclusions of the Dissertation ................................................ 149 6.1 Introduction .......................................................................................................... 149 6.2 Summary of findings in context of research questions and previous research .......... 149 Can a practical model of workplace safety regulation and enforcement be generated using theories from various disciplines? ........................................................................................................ 149 Putting inspections in the context of today’s enforcement theories ....................................... 151 What is the most appropriate statistical approach to answer the question: “Do workplace safety regulatory inspections lead to lower injury rates?”? ................................................................. 152 Do workplace safety regulatory inspections lead to lower injury rates? ................................. 152 6.3 Policy Applications of Research Findings ................................................................. 153 Policy recommendations to WorkSafeBC ................................................................................. 153 Recommendations to WorkSafeBC with reference to the 2014 Macatee Report ................... 154 Broader policy recommendations ............................................................................................ 157 6.4 Suggestions for Future Research ............................................................................. 158 6.5 Conclusion ............................................................................................................. 160 References ................................................................................................................ 161 Appendix A: Previous research .................................................................................. 187 Appendix B: Tables of Data, with specific reference to the database .......................... 194 Appendix C: Result Tables and Supplemental Figures, Chapter 4 ................................ 199 Appendix D: Example Result Tables and Supplementary Materials, Chapter 5 ........... 209 xii List of Tables Table 1 Previous studies on inspections examined in this chapter .............................................. 60 Table 2 Summary of results of previous studies of the effect of inspections on injury rates ...... 66 Table 3 Summary statistics of citations by state .......................................................................... 71 Table 4 Summary of penalties in California, Pennsylvania, and Washington State ..................... 72 Table 5 Information on serious citations in California, Pennsylvania, and Washington State ..... 72 Table 6 Contested citations: average time to resolve contested citations in months ................. 73 Table 7 Penalties changes after adjustment in United States Dollars .......................................... 73 Table 8 Industry make up of firms in California studied in Levine and colleagues (2012) ........... 74 Table 9 Industry make up of firms in Washington State studied in Foley and colleagues (2012) 74 Table 10 Person hours dedicated to prevention activities at WorkSafeBC, by year (2007-2011) 77 Table 11 Number of WorkSafeBC inspection and enforcement activities, by year and type of activity, for the years of inspections studied (2005-2012) .................................................... 79 Table 12 Summary of threats to causal inference in observational studies from Loeber and Farrington (2008) ................................................................................................................... 87 Table 13 Summary of count data choices ..................................................................................... 94 Table 14 Description of the applicability of longitudinal data models ......................................... 95 Table 15 Methods for addressing selection bias .......................................................................... 96 Table 16 Discussion of models to deal with selection bias......................................................... 105 Table 17 Percentage distribution of all BC firms and analytic sample of firms by sector and FTE characteristics ...................................................................................................................... 112 Table 18 Variables available for use in statistical analyses of the impact of inspections on injury rates in British Columbia (replication studies) .................................................................... 113 xiii Table 19 Results of Scholz-Gray and Haviland change models, percent change in acute and short-term, long-term, and fatal (SLF) injuries after inspection, unmatched and matched ............................................................................................................................................. 115 Table 20 Results of GEE Poisson models as incident rate ratios, matched and unmatched ...... 116 Table 21 Results of fixed effects models as incident rate ratios, matched and unmatched ..... 116 Table 22 Results of matched difference-in-differences models as incident rate ratios, acute and short term, long term, and fatal injuries ............................................................................. 117 Table 23 Changes in cohort characteristics by cohort selection ................................................ 130 Table 24 Changes in firm characteristics by sample selection criteria ....................................... 131 Table 25 Results of matching firm size, base premium rate, injury rate, and experience rating, using data extract from study ............................................................................................. 132 Table 26 Results of matching firms by sector, using 4-digit sector level, number of firms in each category ............................................................................................................................... 133 Table 27 Results of conditional fixed effects model by inspection type, acute injuries, and match ................................................................................................................................... 136 Table 28 Matched and unmatched results of conditional fixed effects model by inspection type, short term, long term, and fatal injuries ............................................................................. 136 Table 29 Matched and unmatched results of the conditional fixed effects for inspections with fall protection orders, fall from height injuries only ........................................................... 137 Table 30 Inspections in large service sector and non-service sector firms, 12 month follow up ............................................................................................................................................. 142 Table 31 Inspections with site visit compared to all inspections, 12 and 13-24 month follow up ............................................................................................................................................. 142 Table 32 With very small firms removed (<1st percentile FTE) .................................................. 143 Table 33 With very large firms removed (>99th percentile FTE) ............................................... 143 Table 34 With firms with higher injury rates removed (>0.10 Injuries per FTE) ........................ 143 xiv List of Figures Figure 1 Trends in prevention hours spent at WorkSafeBC, annually, 2005-2017 ........................ 4 Figure 2 Trends in inspection hours at WorkSafeBC and Employment, 2005-2017 ...................... 4 Figure 3 Model of an effective workplace inspection .................................................................. 15 Figure 4 Number of inspections per year in each state ................................................................ 69 Figure 5 Number of inspections per year in each state, for each 100 establishments ................ 70 Figure 6 Comparison of inspection type, by state ........................................................................ 71 Figure 7 Graphical explanation of difference-in-differences method ........................................ 102 Figure 8 Acute injury rate over study period, full cohort firms and final cohort firms .............. 111 Figure 9: Cohort creation and final analytic sample for investigation of the effect of inspections on workplace injuries .......................................................................................................... 130 Figure 10: Changes in distribution of firms by sector by cohort selection ................................. 131 Figure 11 Inspection effect on acute injuries, by duration of follow up and type of inspection (with 95% confidence interval bars) .................................................................................... 134 Figure 12 Inspection effect on all short term, long term, and fatal injuries combined, by duration of follow up and type of inspection (with 95% confidence interval bars) .......................... 135 Figure 13 Inspection effect on acute injuries, 12 months following inspection, by sector ........ 138 Figure 14 Inspection effect on acute injuries, 13-24 months following inspection, by sector .. 138 Figure 15 Inspection with order effect on acute injuries, 12 months following inspection, by sector ................................................................................................................................... 139 Figure 16 Inspection with order effect on acute injuries, 13-24 months following inspection, by sector ................................................................................................................................... 139 Figure 17 Inspection effect on acute injuries, by injury type and duration of follow up, by firm size: small 1-5 FTE, medium 5-20 FTE, large 20+ FTE .......................................................... 140 xv Figure 18 Inspection with order effect on acute injuries, by injury type and duration of follow up, by firm size: small 1-5 FTE, medium 5-20 FTE, large 20+ FTE ....................................... 141 Figure 19 Results of sensitivity analysis removing firms by size and high injury rates, Inspections ............................................................................................................................................. 144 Figure 20 Results of sensitivity analysis removing firms by size and high injury rates, inspections with orders........................................................................................................................... 144 xvi Glossary All terms defined below are reproduced from the 2017 WorkSafeBC Statistics Report (WorkSafeBC 2018) (pp. 112-118), for the sake of consistency in terminology and interpretation. Accepted claim or Allowed claim A claim WorkSafeBC deems work-related and eligible for coverage. Claim A request for payment or benefit to compensate for an injury, illness, or disease a claimant believes is work-related. Classification unit (CU) A very specific grouping of types of business, such as Candy or Chocolate Manufacturer. The system hierarchically groups B.C. firms into sectors, subsectors, and CUs1. Using this system, each employer in B.C. is classified into the appropriate unit based on the products or services produced, and the processes, technology, or materials used. Each CU is made up of firms considered to be peers or competitors, based on the similarity in business activities. A firm’s CU determines its base premium rate. Inspection A formal inspection conducted by a prevention officer2 at a worksite to ensure compliance with the Workers Compensation Act and the Occupational Health and Safety Regulation. Inspection report A document that records the occupational health and safety activity carried out by a prevention officer. This activity usually involves a site visit to ensure regulatory compliance under the Workers Compensation Act and the Occupational Health and Safety Regulation. An inspection report may relate to either the prevention officer’s initial or follow-up activity. Order A WorkSafeBC directive issued as a result of an inspection by a prevention officer. It directs an employer to remedy a contravention of the Workers Compensation Act and/or the 1 These industry categorizations have 2 digits (sector), 4 digits (sub-sector) or 6 digits (classification unit). 2 Prevention officers are referred to as inspectors in this dissertation for consistency to other jurisdictions. xvii Occupational Health and Safety Regulation. Orders may be issued as a result of an initial or follow-up activity. Follow-up orders are orders that confirm the status of compliance on previously issued orders. Rescinded orders are still considered orders. Penalties imposed Administrative penalties that employers have been ordered to pay through additional assessments for violations of Part 3 of the Workers Compensation Act or the Occupational Health and Safety Regulation. Person-year One person-year is the equivalent of one person working all year on either a part-time or full-time basis. WorkSafeBC estimates person-years using employers’ reported payroll and the average wage for the industry the employer is classified in. Prevention officer A WorkSafeBC employee who conducts workplace inspections and is empowered to enforce the Workers Compensation Act and the Occupational Health and Safety Regulation by writing orders and directives, recommending penalties, and issuing closure orders. Prevention officers also investigate incidents, conduct safety program reviews, and provide consultation, education, and technical assistance to employers. Reported claim An injury or disease reported to WorkSafeBC as being work-related and for which compensation is being sought. Includes claims that may be disallowed or rejected at a later date. Also known as a Reported injury and Registered claim. Sector A broad grouping of industries, such as the manufacturing sector. The system groups B.C. firms hierarchically into sectors, subsectors, and CUs. For the purposes of section 37 of the Workers Compensation Act, a sector is equivalent to a class. Also known as Industry sector. See also CU and Subsector. Short-term disability claim A claim from an injured worker who has lost time from work. Also known as Wage-loss claim or Lost-time claim. SLF (Short-term, long-term, and fatal injuries) Injuries or fatalities for which short-term disability, long-term disability, or survivor benefits have been awarded. xviii Serious injury claim Serious injury claims include all time-loss claims with a first payment in the year of injury or in the three months following the year of injury that meet one of the following criteria:  Serious medical diagnosis (one of 434 selected ICD-9 codes)  Potentially serious medical diagnosis (one of 369 selected ICD-9 codes) with a long recovery period (50 or more workdays lost). Subsector A specific grouping of industries, such as road construction. The system groups B.C. industries hierarchically into sectors, subsectors, and CUs. For the purposes of section 37 of the Workers Compensation Act, a subsector is equivalent to a subclass. See also CU and Sector. Warning letter A letter sent to an employer as a result of workers being exposed to a serious hazard, or for repeated non-compliance. Warning letters indicate that an administrative penalty will be considered if further violations of Part 3 of the Workers Compensation Act or the Occupational Health and Safety Regulation occur. xix Acknowledgements This dissertation would not have occurred without the support of many people in my life. To my committee, I thank you for your incredible help as I completed this endeavor, your words of encouragement, and the vast amount of knowledge you represent and were able to share with me. Dr. Chris McLeod, I am incredibly grateful for your many years of support, mentorship, and patience. Dr. Hugh Davies, you were an exceptionally supportive and reassuring force on my committee, and I appreciated your perspective. Dr. Mieke Koehoorn, you are incredibly knowledgeable and an excellent teacher, and I truly appreciate you taking the time to be on my committee. Dr. Benjamin Amick III, thanks for the fascinating reading suggestions, helpful advice, and kind voice over the ether. Cheers to everyone at the Partnership for Work, Health, and Safety for being the best group of coworkers anyone could ask for. To my friends, especially Sarah and Amy, thanks so much for listening to my grumblings as well as for being a positive force in my life. My furry friends, Maggie and Nugget, were also very appreciated for their wags as they sat under my desk not getting walked nearly as much as they deserved. Finally, I thank my family for their cheer and support when I was around and understanding when I was not. It really made all the difference. xx Dedication I dedicate this thesis to those injured on the job in British Columbia and beyond. May research into workplace injuries one day become obsolete. 1 Chapter 1: Introduction and Background 1.1 Workplace Safety Inspections: An Introduction Though injury rates have been declining for the past two decades, workplace injuries remain a significant public health burden. Each year in British Columbia (BC), approximately 65 to 70 deaths and 150,000 injuries3 are related to injuries from workplace incidents4. This is more injuries than from motor vehicle crash injuries in BC each year5. The resulting Workers’ Compensation claims total over $1 billion per year (WorkSafeBC 2015b). To reduce the social and economic burden of these injuries, government and quasi-government agencies regulate employers to make workplaces safer, in addition to the traditional efforts to prevent illness and injury at work that have come from a combination of political initiatives, labour involvement, firm leadership, professional expertise, and technological improvements. However, for safety regulations to be effective, workplaces must comply with them – regulatory systems can only be as strong as the enforcement systems supporting them. Regulatory agencies use various tools to bring about compliance that may be based on encouragement or coercion. In most countries the role of regulatory inspection and enforcement has been central to injury prevention efforts. Inspections are one common tool that regulators’ use to reduce unsafe practices and improve workplace safety. They are important because they allow regulators to experience first-hand knowledge of the workplaces 3 Counting all claims reported to WorkSafeBC 4 From 2010 to 2014 the number of deaths from occupational injuries ranged from 61 to 75 (WorkSafeBC 2015a) 5 There were 95,000 car crash injuries reported to the Insurance Corporation of British Columbia in 2017 (Insurance Corporation of British Columbia 2018) 2 they are charged with governing, allow the transfer of information from the inspector to the firm, and provide firms a reminder of the responsibilities of WorkSafeBC. Globally, inspections have been part of occupational health and safety regulation since 1833, when the HM Factory Inspectorate was formed in the United Kingdom as part of the Factories Act 1833.6 In Canada, Ontario was the first province to legislate workplace health and safety with the Ontario Factories Act of 1884 (Canadian Public Health Association n.d.). Establishing a system of inspections was a part of this legislation from the beginning. In British Columbia, legislation to implement government safety inspections was put into effect in 1917 (WorkSafeBC n.d.). Nearly two centuries after they were first used, regulatory inspections are still considered central to promoting occupational health and safety. The International Labour Organization (ILO) Promotional Framework for Occupational Safety and Health Convention 187, ratified in 38 countries, including Canada, explicitly recommends that member states should establish and maintain a regulatory system for occupational safety and health. This system ought to include laws and regulations and mechanisms for ensuring compliance, including “systems of inspection” (International Labour Organization 2006a).7 Today, traditional enforcement strategies and approaches such as inspections are under pressure due to a movement towards self-regulation and safety management systems. At the same time, work and the way it is organized has been changing, with issues such as outsourcing, restructuring and complicated subcontracting relationships, with challenges for both self-regulation and traditional enforcement systems (Walters, Johnstone, and Frick 2011b). 6 The duty of the inspectors (initially four) was to protect children working in about 3000 textile mills. They were also involved in the development of new health and safety laws and regulations. By the 1860’s the Factories Act extended to nearly all workplaces, and there were 35 inspectors and sub-inspectors to enforce regulation and provide technical advice. 7 Note that the ILO refers to national systems, though in Canada labour regulation is generally a provincial responsibility. 3 1.2 Study Justification Significance of inspections Prevention activities consume a significant amount of financial resources at WorkSafeBC, the regulator of workplace safety and provider of workers’ compensation insurance in British Columbia. In 2014, WorkSafeBC spent about 64 million dollars on prevention8. In that year, inspections were the most common prevention activity, commanding 69% of person-hours spent on prevention activities. This is part of a trend of increasing focus on inspection and education by WorkSafeBC. During the time period (2005-2012), WorkSafeBC performed 34,000 inspections per year9. Over the period of 2005 to 2012, prevention hours increased from just over 200,000 in 2005 to nearly 320,000 in 2010. During the same period, inspection hours almost doubled from just over 100,000 in 2005 to nearly 200,000 in 2010 (WorkSafeBC 2010a). This was followed by a stabilizing trend since 2011, as shown in Figure 1. In 2017, there were 220,898 inspection hours, out of 293,757 prevention hours (75%), with prevention activities costing 75 million dollars, roughly 30% of the operating costs of WorkSafeBC (WorkSafeBC 2018). 8 This group of activities is broadly defined and includes more than just inspections, consultation, and education. 9 These statistics were obtained by performing descriptive statistics on data from WorkSafeBC Annual Reports. 4 Figure 1 Trends in prevention hours spent at WorkSafeBC, annually, 2005-2017 Figure 2 Trends in inspection hours at WorkSafeBC and Employment, 2005-2017 0.00.51.01.52.02.53.0050,000100,000150,000200,000250,0002 005 2006 20 07 2008 200 9 2010 201 1 2 012 2013 20 14 2015 20 16 2017NUMBER OF EMPLOYEES IN BRITISH COLUMBIA, MILLIONSHOURS SPENT ON INSPECTIONS AT WORKSAFEBCInspection hours Employment107,811132,743160,515169,487199,866217,051202,846198,545202,159202,672211,578211,383220,89897,953 85,327 90,87798,961 99,072111,502100,134120,580103,72490,74878,72572,26772,859050,000100,000150,000200,000250,000300,000350,0002005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017PREVENTION HOURSInspection Hours Non-inspection prevention activity Hours5 Inspections remain a dominant and increasing proportion of enforcement activities by WorkSafeBC. The trends in traditional enforcement activities10 at WorkSafeBC show that inspections remain a consistent prevention activity and that inspection hours are roughly in keeping with employment growth (see Figure 2). As such, it is key to study the effectiveness of these resource-intensive activities to provide evidence for their continued use and to provide evidence that may be used to improve prevention activities. Need for research in this area Prior to studying the impact of any intervention, it is important to examine previous studies of similar interventions on similar populations. Studies of the impact of inspections, and inspections with penalties, on workplace injuries from 2001 onward are summarized below and presented in Appendix A. There are several characteristics from the previous studies that limit their generalizability. The studies were limited geographically. Except for one Ontario study (Hogg-Johnson et al. 2012), and two Italian studies using nearly identical data (Agnesi et al. 2016), studies tend to be of American firms, either at the national or state (Pennsylvania, California, and Washington State) level. The number of firms included in prior analyses is usually in the 1000 to 15,000 range, though the two randomized trials included approximately 100 firms. The studies generally focus on firms that have more than 10 employees because United States Occupational Safety and Health Administration (US OSHA) only conducts programmed (as opposed to complaint or accident investigation) inspections on that size of firm. In all studies, the firms were single location only, though the Washington State studies included a category called “non-fixed site” that included firms in the construction and transportation industries. 10 The term used here to refer to inspections and orders, as well as more punitive actions such as stop work orders and financial penalties. 6 These studies have a limited relevance to the types of inspections studied in the current dissertation, as outlined below:  One study looked at pre-planned inspections where the inspected location had prior warning of the inspection; (Lindell 1997)  Many or most studies did not use the variables relevant to the BC context, such as the contravened regulation cited by an order;  At least one study was conducted at the level of subindustry, not at the level of the individual firm (Auld et al. 2001); and  Some studies were limited to certain industries (generally manufacturing firms (see Haviland, Burns, et al. 2012), for example), or a specific size of firm, reducing the generalizability of these studies. There are also several knowledge gaps in the existing evidence base not addressed by prior research:  There is little data on smaller firms since much of the research neglects to include smaller firms; and  There is little research on Canadian firms, and none of British Columbia firms. The impact of an inspection may be influenced by the type of regulatory system. The more jurisdictions inspections are researched in, the more evidence there is available to apply the results to different jurisdictions and to examine the influence of regulatory context in effectiveness. The results of the previous studies of workplace inspections, and associated penalties, citations, and other sanctions, have been equivocal on whether these prevention activities reduce injuries in the workplace. Several systematic reviews offer an additional appraisal and synthesis of the results of the previous studies on the effect of regulatory safety interventions on injuries. The first systematic review of the impact of Occupational Health and Safety (OHS) regulation, including the introduction of regulation and the enforcement of regulation through inspections, citations, and penalties, was published in 2007 (Tompa, Trevithick, and McLeod 2007). This review of studies up to 2003, which included 18 studies with information on the 7 effect of inspections on injuries (as well as 16 on the effect of penalties and citations on injuries), found: “limited-to-mixed evidence of the general and specific deterrence of inspections and the general deterrence of citations and penalties on the frequency or severity of injuries” and “strong evidence that actual citations and penalties reduce the frequency or severity of injuries”. (p. 91) The authors noted that the effect of US OSHA enforcement activities has declined over time, in particular citing Gray and Mendeloff (W. Gray and Mendeloff 2002) who looked at the effect over several time periods, and found a decrease in the effectiveness of interventions such as inspections and inspections with penalties. There were several explanations for this waning effect, including the changing nature of injuries and the possibility that OHS standards were not keeping pace with changing technology in the workplace. However, the study authors recently revisited the subject (Haviland, Burns, et al. 2012) and found that US OSHA inspection activities combined with penalties were again effective at reducing injury rates in manufacturing plants. In 2013, a review of 23 studies of inspections on injuries by (Mischke et al. 2013) included a combination of randomized control trials, panel studies, controlled before-after studies, and qualitative studies; to investigate the effect of inspections and related activities, such as penalties, on injury rates, compliance, and “exposure to physical workload”. Follow-up in the included studies varied from one to four years and “quality of the evidence was low to very low”. The authors concluded that the effects of inspections were inconsistent in seven studies where injury rates decreased or stayed at a similar level compared to no intervention at short and medium-term follow-up. Altogether, there was evidence that inspections, particularly focused inspections, decreased injuries in the long term, but not the short term. The effect of inspections that were of longer duration or were higher frequency was not significantly different. The magnitude of the effect varied, and it was uncertain if penalties had an effect. In studies that found a decrease, the effect was small with a 10% decrease of the injury rate. 8 Complaint inspections resulted in higher compliance rates than other types of inspections11. Firm size also mattered. Inspections resulted in increased short-term compliance or decreased injuries at small firms if they were accompanied by citations or penalties. In discussing the inconsistent results with small effects, the authors noted the urgent need for higher quality studies, including randomised trials and novel enforcement methods. In 2016, Tompa and colleagues updated their 2007 review (Tompa et al. 2016; Tompa, Trevithick, and McLeod 2007). Significantly, it included a Canadian study (Hogg-Johnson et al. 2012) that was a randomized trial of a novel enforcement method – specialized consulting services. In general, the authors found that the new studies added since 2007 generally added to the strong evidence for their 2007 conclusion of an effect from inspections with penalties and no effect from inspections without penalties. Tompa et al. noted that this highlights the need for inspectors to be in the field to detect and cite non-compliance using the vehicle of penalties and citations. Evidence for the effect of general deterrence is lacking, although the 2016 updated review found that awareness campaigns of the consequences of non-compliance did increase compliance. Additionally, there was some evidence that safety consultations provided by regulators may be effective at reducing injury rates, based on one study that found significant effects (Foley et al. 2012). This was one of three studies on consultations total, two of which did not find evidence of an effect. However, one of these studies was the previous version (Baggs, Silverstein, and Foley 2003) of the study that did find an impact at the later date. Although the two systematic review of prevention and enforcement activities do not align completely, the sum of the results of these reviews show:  There is some evidence that inspections, particularly inspections with penalties or citations, or complaint inspections, reduce injuries rates and/or increase compliance;  There is evidence that focused inspections and consultations increase compliance; 11 Accident inspections also seemed more impactful, though this type of inspection is not considered an “inspection” in this dissertation due to issues of regression to the mean. 9  Firm size has an impact on effectiveness, but the effect by firm size varies depending upon the industry or the jurisdiction (although effectiveness was observed consistently in firms greater than 50 employees). 1.3 Study Setting In British Columbia, the organization responsible for both workplace safety regulation and workers’ compensation is WorkSafeBC. In order to promote occupational health and safety and to protect workers from risks to their health and safety, WorkSafeBC, under the legislative mandate of the Workers Compensation Act (WCA), sets the Occupational Health and Safety Regulation12 (the OHS Regulation) and its accompanying standards13 and guidelines14 (WorkSafeBC 2011). To encourage compliance with the OHS Regulation, prevention officers conduct inspections, provide consultations, and deliver education services. These activities are termed WorkSafeBC “prevention activities”15. 1.4 Study Objectives The purpose of this dissertation is to provide evidence of the impact of inspections on workplace injury rates within British Columbia for use in guiding the development of policy. Three key objectives are: 1. To develop a comprehensive model of an inspection that reduces injury rates within a firm. The process by which inspections may improve safety is complex, but the models 12 The Workers Compensation Act (WCA) gives WorkSafeBC the legal authority to set and enforce occupational health and safety regulations (including the Occupational Health and Safety (OHS) Regulation), standards and establish policies regarding compensation, assessment, rehabilitation, and occupational health and safety. The regulations contain legal requirements that must be met by nearly all workplaces in BC, except mines and workplaces under federal jurisdiction. 13 Guidelines are intended to assist with providing ways of complying with the legislation, not to provide exclusive interpretations. Many sections of the WCA and the OHS Regulation have associated guidelines. 14 Standards require firms to comply with conditions by adopting practices, means, methods, operations, or processes. 15 The full table containing this information can be found in Chapter 3, Table 11. 10 used in previous studies have been simple and not necessarily a realistic representation. (Chapter 2) 2. To summarize and provide context to previous studies of inspections to aid in the interpretation and application of the results of those studies, particularly in the context of British Columbia’s regulatory system. The context will also guide the determination of what details are important in disseminating the results of the evaluation of inspections in British Columbia within and across compensation jurisdictions. (Chapter 3) 3. To analyze the impact of inspections on injury rates in British Columbia, by: o Choosing an appropriate methodology that successfully addresses the challenge of observational data, (Chapter 4) and by o Using a population-based cohort of firms to examine injury rates before and after prevention and enforcement activities, specifically inspections and inspections with orders. (Chapter 5) 1.5 Research Questions Can a practical model of workplace safety inspections be generated using theories from various disciplines? The focus on economic theory in the study of enforcement exposes a strong reliance on financial motivations, minimizing the contributions that criminology, legal scholarship, epidemiology, safety engineering, and organizational theory can make. This question will examine what is needed, including coordination between institutions and individuals, for an inspection to be effective in reducing injuries and will outline a model that describes the process involved in an effective inspection in Chapter 2. Can a detailed look at past inspections help to inform this and future studies? The context of a study is vital to proper interpretation and application of the results. The results of studies on inspections and injury rates are equivocal and vary by jurisdiction; even then, limiting the applicability of the results to other jurisdictions. To parse the characteristics 11 of inspections that contribute to lower injury rates, the inspections from previous studies will be examined in more detail than in systematic reviews. Relevant characteristics will be used to inform a more nuanced model of workplace inspections for prevention can include the strategy used to choose a firm for inspection (targeting), the enforcement regime, and the types of firms included in the sample will be discussed in Chapter 3. This will allow the generation of a more nuanced and stronger hypothesis. Considering previous research methods, and in review of current available methods, what is the most appropriate statistical approach to investigate the effect of workplace safety regulatory inspections on injury rates? In this section, various methods that could be used to study the effectiveness of inspections will be analyzed. Using WorkSafeBC data, previous studies will be replicated, and the results compared. The differences in assumptions for each method, and the strengths, limitations, and differences in the interpretation of the results for each method, will be discussed in Chapter 4. Are workplace safety regulatory inspections associated with lower acute injury rates in British Columbia? Does the association vary by firm characteristics? Inspections are the most frequently used activity by WorkSafeBC and can be viewed as an expression of persuasive enforcement. The inspector may offer advice while viewing the workplace, issue suggestions in the form of verbal orders that can be corrected before the inspector leaves or write orders or other deterrence activities if there are significant and outstanding issues. Penalties and shut down orders are rarely used. Previous research indicates that inspections without penalties are generally ineffective at reducing injuries. However, inspections with orders can provide specific information for firms that would like to comply with regulation but do not. In addition, they have the possibility of penalties, which can provide a deterrence effect for those firms that require it. Whether 12 inspections are effective at reducing injuries and whether inspections with orders have a greater impact on injury rates than all inspections is analyzed in Chapter 5. 13 A Conceptual Framework of Inspections and Safety 2.1 Introduction The results of studies of the effect of inspections on workplace injury rates have been equivocal. Recent systematic reviews have concluded that “there is evidence that inspections decrease injuries in the long term”, though the magnitude of the effect and whether penalties are effective is uncertain, and the low quality of evidence makes these conclusions “tentative” (Mischke et al. 2013). To understand why inspections may work to increase the safety of workplaces, a model is important; models may be even more important to understand why inspections may fail to improve worker safety. However, past studies of workplace regulation enforcement rely heavily on economic theory in general, and rational choice theory in particular, without an underlying organising framework. If there is a model presented, it tends to show the firm as a black box that simply responds to economic motivation16. In addition, researchers tend to look at the regulator, firm, and outcome (generally compliance or effects on injury rates) as three separate entities. This is done without clear explication as to what may happen inside the firm or any interactions between the regulator and the firm. An improvement on this basic model can be found in a recent systematic review. Mischke and colleagues (2013) adapted a WHO model for the promotion of diet and physical activity “to explain how enforcement is related to similar interventions and how social, economic, health and environmental benefits are thought to be achieved” (p. 7). The model Mischke et al. used begins to illustrate the way enforcement activities and regulations act to create safer workplaces and is informative for how to evaluate these activities. The authors note that “behaviour change takes place on an individual and organizational level” and organizational changes are included as part of the model (p. 7). However, nothing in the model developed by 16 See (Weil 2001) for an example of one of these overly simplified models. 14 Mischke indicates the pathways or mechanisms by which these changes can happen, and none of the parts of the model are examined in detail. It is important to researchers and policy makers to have a model that can describe the nuances of how organizations work and interact and goes beyond the economist lens that is rooted in issues of rationality and efficiency, with an assumption of a rigid and obedient firm hierarchy. The number of actors involved in the regulation and safety of a workplace, along with workplace organization and individual workers, indicate a much more complicated set of motivations and culture that could obscure the causal pathway. The casual pathway could be enlightened by a look at other academic disciplines, such as sociology and organisational psychology, that provide insights regarding, for example, power and legitimacy (Barnett and Finnemore 2008). A model that describes the pathway of creation of a regulation to fewer injuries in a workplace, via an inspection, is presented in this chapter. This model incorporates theories from multiple disciplines and is more nuanced than previous models to assist with both the design and the evaluation of OHS regulations and enforcement. 2.2 Model The model shown in Figure 3 was developed for this dissertation to illustrate the circumstances necessary for an inspection to lead to a lower injury rate at a firm. It is a summary of the steps that may be involved in a successful inspection, starting from regulations that reduce injuries, to the choice of firm for inspection, and finally to the quality of inspection. It incorporates firm motivations and qualities, incorporating the theory of responsive regulation, a regulatory system where enforcement is applied gently at first but with escalating pressure on those who do not comply. In sum, the model flows from the regulatory system with legitimate and effective regulations. The inspection must be at a firm that needs improvement and be able to identify relevant safety infractions. The firm must be both motivated to achieve compliance, as well as be able to deal with the safety issues to achieve compliance. The inspector or regulator must be able to motivate firms lacking the motivation to provide a safe 15 workplace. Once the firm is motivated, or if the firm is already motivated, consultation or education can provide direction to a firm to achieve fewer workplace injuries. The motivation provided to ensure that the firm is willing to comply is generated by a responsive regulation approach (illustrated as an enforcement pyramid on the right side of Figure 3). Figure 3 Model of an effective workplace inspection The model is discussed in detail in the sections following, beginning with a description of the regulatory system needed for effective inspections. 2.3 Legitimate Regulations and Agencies Laws and decisions must be made in a way that will be followed by the majority of the public voluntarily, and authorities must act in ways that will promote public compliance with the law. Legitimacy, which stems from reasonable rules and an enforcement system that follows fair processes, is key to voluntary compliance (Tyler 1991). 16 The success of a rule in effecting its purpose also depends on whether it is transparent, accessible, and congruent with the policy objective. That is, the words used should be universally accepted and well-defined, the rule should be easily applicable to the situations in which it should apply; and the content of the rule, if followed, should lead to the desired behaviour (Diver 1983). If rules are viewed as meaningless, or cumbersome, even those in a rule-based environment such as the National Aeronautics and Space Administration (NASA) may be conditioned to ignore them (Haines 1999). Related to this is the problem of regulatory unreasonableness – the focus on legalistically enforcing rules rather than solving problems – that can also impact compliance when the goal of preventing harm is subsumed by the zeal to enforce the rules (Benson 2009). The legitimacy of rule can be challenged by moral authority that conflicts with the rules as written. Morality can assist with compliance – authorities who act morally have greater legitimacy and rules are followed willingly and not because of punishment. On the other hand, a law can be viewed as illegitimate if it is seen as morally unacceptable. For example, some people may use illegal drugs, viewing them as a personal choice, but refuse to commit other crimes, such as theft, because these are viewed as “wrong”. Another example occurred during the Vietnam War: even those who viewed the government as generally legitimate refused to follow drafting laws, as the war conflicted with their own moral code (Tyler 1991). A significant problem affecting legitimacy is agency capture, whereby the regulator appears biased towards some businesses, and thus loses illegitimacy by reducing the appearance fairness of process. By design and necessity, regulatory agencies work closely with industries, for example, during inspections, public hearings on the development of regulations, and industry consultations, among other activities. Regulatory inspectors also meet regularly with the people they regulate as they go about enforcing the rules. Hence, there is always the possibility that regulatory agencies will be “captured” by the regulated industry and begin to act more in the interests of the industry rather than the interests of the general public (Benson 2009). A study of OSHA inspections found that state agencies reacted to local economic conditions more than federal OSHA, that larger companies were more likely to receive lenience 17 than smaller companies, and that the political party in power can influence the magnitude of fines, showing at least some evidence of regulatory capture17 (Jung and Makowsky 2012). In addition to regulatory capture by industry, it appears that there can be political influence on inspections. In the United States, there is a tendency for Democratic governments to support the regulation of markets, and for Republican governments to oppose the regulation of markets (Klein and Stern 2004). In particular, the Executive Branch of government can have an effect on levied and reduced fines, with smaller fines observed fines under Republican Presidents (Jung and Makowsky 2012). 2.4 Crafting an Effective Regulatory Regime As Adam Smith stated, in a world of absolute liberty, a worker would seek advantageous employment and shun disadvantageous occupations, such as dangerous jobs. As more workers chose advantageous (safer) employment, the wage for disadvantageous employment rises theoretically until the risk is correctly priced into the wage (Smith 1776). In theory, employers would improve safety when it became less costly to prevent injuries than it was to deal with the costs of injuries via wages for disadvantageous employment. While this economic approach makes sense to the employer, it does not take the employees’ and society’s perspectives into consideration with regards to the economic consequences of employee injuries, including unemployment, medical care, and social issues (Barnetson 2010). As such, the true costs are often not correctly factored into wages and are passed from the employer to the worker. This would lead to a negative externality, which occurs when some individual’s or firm’s activities have a negative impact on the well-being of another some individual or firm without concomitant compensation for that impact. In theory, workers could attempt to recoup their costs via civil litigation, though this can be difficult due to evidentiary hurdles, sometimes weak causal attribution, and technicalities such as assumption of risk. 17 Jung and Makowsky found patterns of discretionary enforcement operating differently in state and federally conducted inspections. The executive branch exerts greater influence than congress over inspection outcomes with issued fines negotiated fines both smaller during Republican presidencies. (Jung and Makowsky 2012) 18 Government regulation is an attempt to correct this aforementioned market failure and internalize the externalities that shift the cost of injuries to the worker and society (Lambert 2004; Shannon, Robson, and Sale 2001). Ideally, regulation is technically effective (defined below) at reducing injuries, and takes an evidence-based approach, taking safety research and theory into account. Developing technically effective regulations Government regulation to correct the market’s failure, where the risk of injuries is borne by the worker, is one way to decrease injuries. However, to be effective in reducing risks to the worker, safety regulations must adequately address causes of workplace injury. If not, an inspection that succeeds in bringing a firm up to compliance will nonetheless still have no effect on injury rates. Regulations will be a futile tool in injury prevention if they address issues that do not tend to cause to injuries, or if they inadequately address issues that do cause injuries. In addition, regulations that are complex may decrease compliance as knowledge and understanding of the regulations become more difficult (Parker 2014). Many studies failed to find a correlation between regulations and a decline in injuries during the formative years of the Occupational Safety and Health Administration (OSHA) in the United States, following its introduction in 1970 (Leeth 2011). It is thought that, in a rush to see quick results from the new agency, regulations were quickly created from detailed guidelines and standards from industry groups. These regulations were more straightforward to enforce, but being derived by detailed standards, were overly technical and narrow, going so far as to specify the direction of the grain of wood on ladders. One study examined the relationship between violation of standards and 645 workplace deaths in California in 1976 and found that violations of standards accounted for 13 to 19 percent of the fatalities. In addition, one-half of these violations could have been detected in advance of the accident (perhaps by a workplace inspection). A longitudinal study using data from much of the 1970’s showed only weak linkages between noncompliance and workplace accidents. The authors concluded that the OSHA standards of the time were flawed because they emphasized “standards for capital equipment 19 when most accidents in fact are caused by complex epidemiological interactions of labor, equipment, and the workplace environment” (Bartel and Thomas 1985, p. 2). Following that formative period, OSHA began to deal with “the glaring incongruities produced by this strategy” (Diver 1983, p. 104). Later studies on safety regulations in the United States have shown that some regulations have had an impact on safety in the workplace. For example, a study in Washington State found that the introduction of a fall protection standard led to a reduction in lost days and cost per injury for fall injuries (Lipscomb 2003). A review of electrocution incidents in the United States found that most of the investigated incidents could have been prevented through compliance with regulations and code, or the use of adequate personal protective equipment (National Institute for Occupational Safety and Health 1998). In a study of the effects of revised safety regulations on injuries in structural iron and steel workers, Choe et al. found that both fatality and days away declined, by 22% and 54% respectively, after the implementation of the revised standards (Choe, Yun, and Leite 2016). Results from an interrupted time series study found that there was a significant decrease in the incidence of power saw injuries after the introduction of a power saw safety standard (Vosbikian et al. 2017). The contrast between the results of the early OSHA studies and the more recent studies indicate that properly written and administered standards and regulations can lead to a reduction in injuries. Notwithstanding this, in their systematic review of the impact of the introduction of OHS regulations and legislation on workplace injuries, Tompa and colleagues (2016) found only limited evidence of an effect. This small effect could be the true causal effect; or it could reflect the difficulty of observing small incremental effects in short-term studies, an artefact of varied types of legislation, an insufficient follow up period to catch any effects, or a combination of all of these. When considering the results of these analyses, it is important to consider the context of each legislation or legislative environment. In a meta-ethnographic study of OHS regulation (MacEachen et al. 2016), a synthesis of qualitative studies showed that the effectiveness of OHS legislation may be affected by the relative resources of inspectorates, the coordination of 20 authorities, and whether workers were able to participate in the system. Thus, while it is important to develop appropriate legislation, the context of implementation must also be considered. Legitimacy can also be gained from regulation programs that are based in science though highly inclusive of industry input, such as the European Network for Silica agreement in the European Union. (“NEPSI Agreement Continues to Improve Workers’ Health Protection” n.d.) Safety theory is described in the next section as a background to the discussion on technically effective regulation. 2.4.1.1 Safety theories relevant to the development of technically effective regulations Safety regulations are created to prevent injuries and the externalities caused by these injuries. To be effective, these regulations must be informed by theories of the causes of occupational injuries. Physical injury at work generally comes from the transfer of energy to the human body. This energy can come from many sources: kinetic energy, electrical energy, acoustic energy and vibration, thermal energy, fires, explosions, pressure, electromagnetic energy, and severe weather and geological events. Kinetic energy transferred to humans with frequency, such as in repetitive strain injuries; or a high rate, such as an impact or fall, can damage the body and can result in occupational injuries or fatalities (Jensen 2012). Though workplace injury, when described in this manner, seems relatively straight-forward, the theory of injury causation is still an unsettled science. There are at least 25 models of accident or incident causation that have been enumerated, coming from diverse perspectives including physics, epidemiology, and systems theory (Manuele 2013). Some authors, including Hale et al. (2010) and Rasmussen (1997) have reviewed the history of safety research, and determined that safety progress can be divided into about three (overlapping) eras. Until the Second World War, safety was concerned with barriers and structural solutions – technical measures such as railings and saw guards. This was the first era, and it was thought that if an accident could not be prevented with a technical measure, it could 21 not be prevented at all. Later, human factors came into play, and it was thought that ‘accident prone’ or ‘unmotivated’ workers associated with higher risk of injury could be mitigated through personnel selection, instructional campaigns, and management theories (Rasmussen 1997; Hale et al. 2010). These two approaches were merged during the 1960’s and 70’s, leading to advances in risk analysis and ergonomics (Hale et al. 2010). There is a focus by Human Factors Specialists on the concept of ‘human error’ whereby actual behaviour is described by some deviance from a normative model of rational behaviour (Rasmussen 1997). The models were further developed by studies of cognition and adaptations to environmental constraints. Because management was responsible for many of these environmental constraints, accidents were thought by some researchers to be caused by inadequate management and organizational factors (Rasmussen 1997). By the 1980’s the limits of these approaches was starting to show – after decades of prevention efforts based on barriers and technical measures, counteracting human error as identified by causal analysis appeared to be ineffective (Rasmussen 1997). It was recognized that “(a)t any point in the causal analysis, a failure or an error can be conceived of as a ‘result’, not a ‘cause’” (Saleh et al. 2010, p. 1107). Thus, even accidents18 that were considered to be caused by “direct and immediate” causes could be viewed as induced by underlying local conditions, such as technical, management or environmental characteristics and more global conditions such as weak safety culture or production pressures (Dien, Llory, and Montmayeul 2004). Occupational safety was now generally studied without reference to errors. Safety professionals were concerned with culture as well as management systems, safety monitoring, and safety auditing. Large corporations, such as DuPont, took this approach to safety and were held up as a role model to other companies (Hovden, Albrechtsen, and Herrera 2010). 18 The word “accident” is often discouraged in occupational safety literature but was used by the authors of this review as often happens when occupational injuries are grouped with large scale industrial disasters. 22 Today, the sociotechnical view of accidents considers an organization’s culture as “the primary determiner with respect to the avoidance, elimination, or control of hazards and whether acceptable risk levels are achieved” (p. 294, Manuele 2013). This view puts management as the driver of culture and maker of decisions regarding policies, workplaces, work methods, social atmosphere, accountability, and resource allocation. In response, safety programs integrated both the technical and social aspects of work, with the understanding that management decisions create and control the socio-technical operations and that the social and technical aspects are interdependent (Manuele 2013). As safety management programs have integrated both the technical and social aspects of safety, it is important that regulations deal with both of these aspects as well. In the next section, types of regulation that have been used in the past and today are discussed in their relevance to today’s regulatory system. 2.4.1.2 Matching regulation type to policy aims Regulations have historically been developed from an accident causation point of view, resulting in prescriptive regulation. Prescriptive regulations state precisely what is to be done and how work should be carried out. As such, it demands arrangements (for example, the creation of safety committees) or installations (for example, machine guards) (Government of Ontario n.d.). Regulators send a clear message of what is expected, firms are expected to know exactly what the requirements are, and compliance should be straightforward. Workplaces will be deemed safe by the regulators if they complied with the regulations (Cliff 2012). Prescriptive regulation can be uniformly applied and thus lends itself to a system of regulatory inspections and is appropriate where work is particularly unsafe due to equipment or the work environment (Government of Ontario n.d.). However, it can be difficult to develop prescriptive regulations for all types of workplaces and to keep these regulations up-to-date. Prescriptive regulations can inhibit innovative approaches to workplace safety with no incentive to solve problems in a more effective or holistic way (Cliff 2012). Additionally, some aspects of safety, such as ensuring safety systems have redundancies in case of errors, providing effective 23 training, and mitigation in the wake of a workplace accident, are also important for a safe workplace, but are difficult to regulate with prescriptive regulation. Prescriptive regulation can also be susceptible to “regulatory mismatch” wherein a regulation is too broad (or sometimes too narrow) to fit the problem it is supposed to correct (Lambert 2007). The Robens Report in the United Kingdom (UK) in 1972 (Robens 19732) suggested that regulators shift the focus to goal-setting legislation and encourage self-regulation in a move that would allow flexibility and avoid regulatory mismatch. The Report’s recommendations led to a shift in health and safety legislation first in the UK, and soon after also in other countries (Walters 2003). Goal-setting, or performance-based, regulations provide an “endpoint” or goal that allow a firm to develop their own solutions to achieving safety goals. The classic example of performance OHS regulation is that of a general duty of care (Hopkins 1994). Another example might be a goal that a worker’s fingers be protected from the table saw, with resulting interpretations ranging from automation that keeps the worker separated from the saw, to a safety saw that stops when it no longer feels the resistance of wood, to chain mail gloves. In contrast, traditional prescriptive regulations might require the table saw be outfitted with a guard with certain dimensions and made of a specific material. Performance-based legislation provides flexibility in compliance because it focuses on outcomes rather than on the precise technical methods of achieving safety (Government of Ontario n.d.). However, it is difficult to monitor compliance with performance regulation and, as a result, it is often used retrospectively during incident investigations more than during routine enforcement (Hopkins 1994). In the 1980’s, a series of serious industrial accidents forced a new way of looking at safety within firms via self-regulation and management systems because it was thought that these accidents occurred due to deficiencies in the management of safety and health (Cliff 2012). It was thought that self-regulation would allow the knowledge a firm has of its own internal operations to come up with superior solutions that they are more likely to follow since they are more likely to view their own standards as reasonable (Gunningham 2010). This self-regulatory approach works in tandem with other management systems of quality and improved business 24 performance, allowing regulators to argue that it is in the best economic interest of organizations to adopt self-regulatory approaches. There has also been extensive discussion of ways of inducing employers to adopt such schemes, including reduced regulatory surveillance and further encouragement towards self-regulation (Walters, Johnstone, and Frick 2011a). Regulating through safety management systems can go some way to incorporating the sociotechnical factors discussed above (le Coze et al. 2017), but this is not necessarily a comprehensive solution to the address the need for a sociotechnical approach. In some cases, safety management system (SMS) audits became a surrogate for regulatory inspections (Zanko and Dawson 2012), although statistics do not support the notion that this is effective (Walters, Johnstone, and Frick 2011b). In a series of case studies, Walters and colleagues found that inspectors received little advice and guidance on how to critically examine SMS systems, even though they believed inspection was crucial in the sound application of SMS standards. Inspectors took account of the procedural requirements such as OHS policies and written procedures, but did not assess the larger issues of the operation the SMS, resulting in firms achieving less than full compliance with the SMS regulation (2011a). An additional problem with self-regulation is that it can fail to generate compliance. In a study of air pollution data from United States industrial facilities, the researchers determined that heavy regulatory surveillance was necessary for firms to fulfill self-regulation commitments. Having an appropriate legal environment in which the self-regulation policy was instituted appeared crucial, including immunity from prosecution for self-disclosing offences or having inspections in addition to audits (Short and Toffel 2010). Even in a regime of self-regulation, it may be that inspections are still necessary (Gunningham, Phillipson, and Grabosky 1999). While SMS certification programs are showing promise with reductions in injury rates in firms in British Columbia, (McLeod, Quirke, and Koehoorn 2015), they are not a complete replacement for enforcement. It is suspected that SMS audits may be manipulated by firms, and audit systems remain unable to uncover organizational problems that may be leading to unsafe conditions (F. Hedlund 2014). 25 Parker (2014) goes further and states that to work correctly, self-regulation should integrate – be a “marriage between” – law, corporate self-management, and external stakeholders. With the regulation to ensure openness, particularly to stakeholders, management can critically assess performance of responsibilities. This version of self-regulation can be compared to “Smart Regulation”, coined by Gunningham and colleagues (2010), which is another way to decrease state regulation, in this case, by augmenting regulation with markets, civil society, international standards associations, industry associations, or other institutions that can help reach policy goals. Those in support of smart regulation say it is more effective, less expensive, and more palatable for those being regulated (Gunningham, Phillipson, and Grabosky 1999). A key requirement for the success of self-regulation to succeed is that firms default to a compliance without a great deal of additional outside oversight. Legitimacy of the regulatory bodies and the regulation is important in this case. 2.5 An Effective Enforcement Regime “Historically, efforts to prevent illness and injury at work have come from a combination of political activities, regulatory intervention, labour market action, professional and managerial initiative and expertise as well as from the impact of technological innovation and economic restructuring. In most countries the role of regulatory inspection and enforcement has been central to these efforts.” (Walters, Johnstone, and Frick 2011b, p. 4) The above section was about designing laws, regulations and regulatory tools in a way that would encourage firms to follow the rules therein. To promote public policy goals using regulation, governments and their agencies have several tools at their disposal to promote compliance with these regulations. These tools range from cooperative to punitive, from education and consultation, to inspections with orders and penalties, and ultimately to (in extreme cases) criminal sanctions. The next part of the model is effectively carrying out inspections. This part of the inspection relates to both identifying the right firm – a firm that can improve its safety, and the right infractions – those causally related to injuries. The following section will highlight the tools 26 and strategies used by authorities and highlight their connection to theories of firm behaviour. Underlying each approach are different theories on how firms respond to regulatory enforcement that in turn influences regulatory strategies, enforcement and compliance, and eventually injury rates. Firm targeting For a workplace inspection to cause a meaningful reduction in injuries, the workplace conditions must be such that there is a possibility of injury, and the inspector must identify the unsafe conditions to be corrected. Inspecting a workplace where workers do not engage in hazardous activities or a workplace that is in complete compliance with effective safety regulations19 would not be effective in reducing injuries. The targeting of firms for inspections, based on the safety record of the firm or the industry the firm is one way to try to identify the firms that would benefit from an inspection. Firms may also be chosen randomly for inspections which, while giving an appearance of fairness, will be less efficient at finding firms that have a need for an inspection. In a regulatory agency with limited resources, there will always be a tension between providing increased resources for enforcement and budgetary constraints. This tension has been increasing with calls for more resources associated with a decrease in unionization and an increase in informal work arrangements, combined with for smaller government, deregulation, and increased scrutiny of regulatory systems. In response, the International Labour Organization has called for better training and support for inspectors and more distance between the political process and regulatory authorities ((International Labour Organization 2006b) referenced in (Weil 2008)). Weil (2008) argues that in addition to these steps, inspections should become more strategic by explicitly and systematically prioritizing industries and workplaces and activities that have the most and longest lasting effects. 19 Of course, this assumes that the regulations do, in fact, prevent injuries 27 In a study of construction contractors, Weil (2004) found that large construction contractors were more commonly inspected by OSHA, though they had higher levels of compliance than other firms in the construction industry that received less enforcement, and these large firms tended to not improve compliance on repeat inspections. Weil goes on to suggest that “ideally, OSHA would focus its resources on construction projects that subject the largest number of workers to the most severe safety and health risks.” In the United States, courts have required transparent policies around the selection of firms for inspection, what is to be inspected, and the responsibilities of the during the inspection. It is recommended that these policies are written and detailed as inspectors often operate independently of supervisors when in the field. In some cases, this requirement for transparency has been interpreted as choosing firms at random, rather than purposeful targeting, to ensure there is no untoward activity in relation to firm selection (Diver 1983). A superior targeting strategy might identify establishments that have unusually high injury rates within their industries. This may be more effective than a strategy of targeting high-risk industries that ‘penalizes’ firms for being in a high injury-rate industry rather than being an unsafe firm (Haviland, Burns, et al. 2012). Risk-based targeted inspections that target firms and industries that create the most health and safety risks, rather than randomly choosing firms for inspections, are found in the United Kingdom, the USA (see OSHA’s Site-Specific Targeting Inspection Program (SST)), Denmark, and Australia, among others. Risk-based inspections focus on firms and resources that need inspection as a means of improving effectiveness and reducing the costs of compliance and enforcement (Walters, Johnstone, and Frick 2011a). Another proposed strategy is exploring the characteristics that tend to be associated with lower compliance and targeting those types of firms. For example, targeting of smaller employers and medium firms with several small locations, who tend to have lower levels of compliance (Mendeloff 2006). This might, however, be a localized effect. In an era of computerized record keeping and data analyses, it is likely there are effective strategies that could be developed using this data for each regulatory jurisdiction. 28 In determining a method or system for risk-based inspection, it is important to note that the concept of risk-based regulation is not static or objective (Almond and Colover 2010). Concepts of what is “risk based“ can differ based on the political environment and can change based on the values and agendas of the prevailing government. Risk-based targeting can vary from a system that takes the individual inspector’s views and experiences into account when choosing a firm to inspect, to a system that looks at groups of firms in aggregate much as an actuary would do. Though the latter method seems objective, it can mask components that are normative or political in nature, from the discounting of inspector expertise and their regulatory profession, to the very reason inspection resources have become limited (Almond and Esbester 2018; Almond and Colover 2010). For illustration, one can look at the wide variety of targeting programs that have been implemented by regulators. Regulators can implement risk-based targeting as a guideline, a commitment, or a suite of management tools. The nature of the programs depend on the resource constraints of the regulator, the policy and legitimacy needs, and the risks the organization is regulating (Almond and Esbester 2018). In an extreme version of targeting in 2013, “low risk” firms were generally exempted from regulatory health and safety inspections in the United Kingdom, leaving the vast majority of employers in that country to self-regulation (Tombs and Whyte 2013). In addition to some form of risk-based targeting, it may be more effective to reduce the number of repeat inspections in favour of inspecting more firms for the first time, or for the first time in a long time. In a 2010 study by Ko, Mendeloff, and Gray on inspections in manufacturing plants, the number of violations declined from first to second OSHA inspections by 28% to 48%, and the number of violations then increased slightly for each additional year past that second inspection. While the above strategies have worked in the past, it is important to note that, as workplaces change, the targeting strategy must change as well. Work hours are becoming more fractured (Johnson and Lipscomb 2006) and the gig economy is rising (Wright 2018a), 29 regulators will need to become more sophisticated to target and reach workers most vulnerable to workplace safety violations. Quality and scope of inspection It is vital that the firms that need improvement receive comprehensive inspections. For an inspection to be effective at preventing injuries, the inspector needs to find the deficiencies that may cause injuries. For example, a study of United States Navy civilian plants found that a lower score on a workplace inspection was predictive of future higher lost time injury rates at a plant (Lindell 1997). It may also be important to prioritize inspections in the areas of the most concern. Analyzing data from OSHA, Weil ( 2001) compared the causes of injuries and fatalities in 1994 to the number of standards cited and found that the frequency of citations did not match the frequency of injuries. For example, the most common injuries were due to being struck by an object, but citations related to this issue were only 4% of the total. Overexertion, not covered by regulation, created almost one quarter of the injuries and fatalities. As the nature of work changes due to technological advances and automation (Wright 2018b), it is important that research and training are continually updated to ensure that inspectors are able to react to the new nature of work. In addition, inspectors have differing styles that may affect comprehensive inspection and ultimately compliance. One study found that relative to coercive inspectors, autonomy-supportive inspectors (those that provided rationales for their actions and offered choices) achieved compliance after fewer worksite visits (Burstyn, Jonasi, and Wild 2010). Similarly, a study of inspectors in California showed some inspectors were more effective than others, and determined that inspector experience was related to improved prevention, albeit with small effects (Haviland, Main, et al. 2012). Conversely, a study of building inspectors showed that the style of interaction, depending on whether the inspector was facilitative or formalistic, did not affect compliance (May and Wood 2003). Transmitting information regarding compliance is also an important part of a successful inspection. Conversely, limited interaction between inspectors and worksites, or too much 30 elapsed time between encounters, may hinder effective communication channels and the clarity of the message (Mascini 2013). 2.6 Motivating Firms Beyond choosing firms for inspections, conducting inspections, and finding contraventions, regulators also need a strategy to deal with non-compliance when it is found. Next in the model is motivating compliance by a firm in these non-compliant firms. If the firm is receptive to improving safety, then persuasion by the inspectors should be sufficient to facilitate safety at that firm, usually by providing information to firm decision makers regarding non-compliance or unsafe practices or conditions. If it is not receptive, other strategies might be required. Motivating firms through Rational Choice Theory Traditional models of firm motivation are based in the rational choice theory of the firm, a theory of decision-making based in classical economics. In this model, maximizing utility20 is the sole motivation of the decision maker. The “rational firm” calculates the value of the outcome of each possibility and chooses the one alternative that will maximize utility. Utility maximization is seen as equivalent to profit maximisation in the vast majority of business decisions. (Opp 2012). Those decision makers that behave completely rationally will be motivated by incentives to comply with regulations and will perform cost-benefit analysis when deciding on compliance or non-compliance with regulations, considering incentives to comply and punishments for contraventions along with the probability of being caught (Feldman 2011). This model assumes that the decision makers are making conscious decisions with behaviour 20 Utility is more complicated than profit, as it includes satisfaction with how a good or service fulfills a need or demand. Utility maximization is a more useful measure than profit maximization because: it can explain why two individuals, faced with exactly the same situation, might rationally respond quite differently, and it still includes profit maximization as a special case (Lin, Dean, and Moore 1974), and profit maximization may be assumed for much of this discussion. 31 that is determined by opportunities and constraints, and that they have full information, the cognitive resources and the time to make decisions. Wilde (Wilde 1998) describes a framework of utility factors in risk taking that can be applied to compliance with workplace safety regulations. He describes four factors that one will consider when making these decisions:  The expected benefits of non-compliance (speeding up production)  The expected costs of non-compliance (fines, increased insurance premiums, lost time)  The expected benefits of compliance (better reputation, better worker morale, lower accident rates)  The expected costs of compliance (hiring safety consultants, installing safety devices, buying personal protective equipment) The expected utility model (that informs most studies of deterrence) assumes that safety in a plant (risk) reflects the optimal level of safety expenditures. This optimal level is a factor of the marginal cost of the expenditure compared to the expected savings from avoided accidents. Also factored into this cost are safety expenditures to reduce or avoid penalties for noncompliance, with inspections, citations, and penalties incentivizing safety expenditures. A main attraction of the rational choice model of behaviour is the model’s simplicity. Models based on rational choice are appealing because they tend to be more parsimonious models with core assumptions that are consistent and widely used (Wittek, Snijders, and Nee 2013). Although decision makers may not have full information or the time to make proper decisions or lack the opportunity or preference to make the decision with maximum utility, in theory, the overall aggregate effect should be the same. That is, some decisions will be more or less profitable than predicted (Wittek, Snijders, and Nee 2013). There are many alternative theories to rational choice theory that add to the discourse on decision-making and explanations for business behaviour. Even champions of rational choice theory acknowledge that some firms do not follow the rational models, though they insist that these firms will eventually go out of business as they are less efficient in a competitive marketplace (Pfeffer 1997). 32 Thus, some academics are critical of this model of behaviour, finding it reductive. They note that these models require much stronger assumptions about human behaviour than more “realistic” models. In reality, decision makers may not act entirely consciously and may be motivated by more than just financial considerations (Bruns 2009; Pfeffer 1997). It is nearly impossible to enumerate all the relevant possible decisions. In addition, even if all the possible options were outlined, very few people understand probabilities enough to apply them in real life situations. However, Pfeffer (1997) considers the most persuasive critique of these models is that they do not bear out in making predictions about empirical results. Though many economists model decision makers using rational decision making, decision makers do not use rational decision making all the time. The bounded rationality theory was developed to address some of the limitations of the standard rational choice theory: decision makers aim to act rationally and maximize profit, but they are hampered by incomplete information and resource constraints (Simon 1979). Bounded rational behaviour is rational because it is intentional and guided by utility maximization, but it cannot be substantively rational because decision makers are not omniscient (Tomer 1992). The decisions made at an organization may be considered boundedly rational if decisions are made that are conducive to the organization’s goals; however, only procedural rationality is possible. As Tomer (Tomer 1992) described, only the omniscient make optimal decisions as typically decision-making is done without the knowledge and tools necessary for optimal decision making. In addition to the cognitive and resource constraints listed above, people generally have biases in decision-making. For example, the strategies people use to deal with complexity introduce bias to the making of decisions (Tomer 1992). Etzioni (2011) states that biases are inherent in both decision making and available choices, preventing utility maximization. He notes that research in the fields of sociology, psychology, and behavioural economics has shown that many choices are not based on reasoning or deliberating. However, when reasoning does happen, it is marked by cognitive biases. When reasoning does not happen, the “intuitive” choices are “deeply affected by emotions and norms” as well as social factors (Etzioni 2011 p. 1114). 33 Pfeffer (Pfeffer 1997) highlights several models of behaviour that are alternatives to the economic model. The social model of behaviour considers that humans do not function in isolation. People affect, and are affected by, the behaviour of others. This includes workers influencing how other workers feel about their job, and company directors influencing the corporate strategies of peers at other firms. Other motivations include being a good corporate citizen, morality and fairness, and reason. Under these motivations, the regulator/legislative process is perceived to have calculated acceptable levels of risk, and that guidance to reduce these risks is provided in the form of regulation (Feldman 2011). Feldman (2011) took the theories of firm behaviour and applied them to the question of what motivates compliance with regulation (described above). Based on behavioural studies and psychology, including compliance for moral reasons or for deference to authority, he notes that it can be difficult to predict how to motivate an individual. Thus, “a policy maker may be forced to speak with many voices” (Feldman 2011) – highlighting the need for a well-trained inspectorate. He also notes that these models are not mutually exclusive and may even be in competition – by attempting to increase one motivation intentionally, others maybe decreased unintentionally. Some researchers also consider economic models to not reflect current management practice. Management today has less emphasis on hierarchy and pure economic incentives for workers. In addition, this theory does not fully align with ideas from social psychologists, sociologists, and organizational theorists. The following section discusses the deterrence model, which is based on the rational choice theory – it considers that firms make rational calculations in the face of compliance issues. Firms must be given strong motivation to comply so that compliance becomes the option that provides the most utility and it becomes more “expensive” to be out of compliance. The deterrence model In the enforcement or deterrence model, firms are compelled to comply with regulations due to the pressure from inspections and penalties (specific deterrence), or voluntarily comply 34 due to the general deterrence effects from the perceived threat of inspections and penalties (Becker 1974). The objective of deterrence law enforcement is to secure conformity with the law by detecting violations of the law, determining who is responsible, and penalizing violators to deter violations in the future either by the punished or those who were not penalized (Reiss 1984). This model relies on theories of rational choice, that is, a decrease in the utility of neglecting safety is achieved by an increase in the probability of the detection of non-and of non-compliance penalties. The more severe forms of prevention can be found in the deterrence effects of criminal punishment though there has been a reluctance to apply criminal laws to workplace issues. Historically in the United Kingdom, an ambiguity of factory crime (that is, the question of whether factory crime was really a crime), led to factory owners frequently breaking safety and worker protection laws (Carson 1979). Part of this ambiguity arises from the fact that these offences have been dealt with by administrative agencies, ever since the introduction of the Factories Act 1833 that emphasized prevention and education, rather than the punitive aims of the criminal justice system (Walters, Johnstone, and Frick 2011a). Many countries treated workplace safety laws similarly, including Canada (G. C. Gray 2009). Much of the above is applicable to both specific and general deterrence. Specific deterrence is pressure from inspections and penalties at a firm and general deterrence results from the perceived threat of inspections and penalties, and thus relates directly to the probability of an inspection or penalty (Becker 1974). In general deterrence, the perceived utility is modified by the probability of being caught. General deterrence in regulation (rather than criminal law) is not often studied. Looking at the regulation of safety plans, Mendeloff (2012) found little evidence for general deterrence. Indeed, the rate at which firms were found in violation of written safety program infractions had not changed in 20 years, and newly inspected establishments were no more likely to have written programs now than newly inspected establishments 20 years ago. Specific deterrence did seem to be in effect in safety plans as studied by Mendeloff. In other words, once an establishment has been cited, the likelihood of finding another violation at that establishment declined substantially. 35 In a study of environmental regulations enforcement, Thornton and colleagues (2005) found that there was only weak support for general deterrence theory. Most of the respondents at surveyed firms did not remember the particular “signal case” that was intended to deter businesses from contravening environmental regulations, and companies where the respondent did remember the signal case were no more likely to change environmental measures than those who did not remember. However, most businesses surveyed did remember some other firm receiving a penalty for an environmental violation and changing their environmental protection measures after learning about the penalty. This led Thornton et al. (2005) to conclude that the function of general deterrence is often to remind those firms that intend to comply, to check their environmental performance and to reassure those that intend to be in compliance that the non-compliant firms are, in fact, getting caught and punished (that is, the system is working fairly). This is in addition to the classic deterrence function of signaling to those willingly in non-compliance to acknowledge the risk of getting punished and improving their behaviour. While often studied and written about, punitive enforcement is not common in workplace safety regulation and policy (Tombs and Whyte 2013). Rather, with a few exceptions related to corporate crime laws that have introduced harsh penalties, deregulation with prosecution and an accommodative attitude are the norm in workplace safety regulation (Almond and Colover 2012). This deterrence model is predicated on theories of rational choice, which as outlined above is often not consistent with how firms make decisions and consequent behaviour. The compliance model is the converse of the deterrence model, assuming firms are willing to comply but are non-compliant due to reasons other than utility. The compliance model The compliance model21 is a model that assumes that decision makers prefer to comply with regulation but are somehow unable or unprepared to meet the requirements of the 21 Also sometimes referred to as the persuasive, advise and persuade, or cooperative model 36 regulations. This model is ultimately focused on the desired outcome of the regulatory system, rather than the punishment of firms that are out of compliance with regulation (Walters, Johnstone, and Frick 2011a). Under this model, firms may act responsibly above and beyond the traditional economic incentives of merely pursuing profit. Leadership at a firm may have social motives for the success of the firm – the need to maintain approval from the public, the leadership at other firms, and perhaps even regulators. Another possibility is the normative motive to comply with the regulation due to a sense of duty or an agreement with the regulation. The decision makers at a business may want to fulfil their obligations under the regulations and may believe themselves to be following occupational health and safety regulations. However, health and safety efforts may be overlooked due to inattention or competing interests (for example, technological change). With this in mind, regulators approach firms with a “spirit of cooperation”, and the firm is given the benefit of the doubt when issues of non-compliance arise, with the assumption that decision makers have good intentions but lack the knowledge to comply (Scholz 1984). Regulators rely on persuasion to achieve compliance, and emphasize co-operation rather than confrontation, and conciliation and negotiation rather than coercion. The threat of enforcement remains in the background, to be used where all other strategies fail. The goal is that leadership at firms will be more willing to provide the regulators with accurate information about their internal operations and that regulators, in turn, will be more receptive to acting on this information. (Rubin 2005) Compliance-based law enforcement systems seek to achieve compliance with a law by using preventative methods without having penalize violators. These systems use rewards to gain compliance or in some cases use penalties as a threat rather than a sanction; the penalty is withdrawn if compliance is achieved (Reiss 1984). Since there is a belief that non-compliance is a consequence of a lack of information or know-how, consultation and education initiatives are main tools in compliance based systems (Weil 2006). Inspections are relatively infrequent and excuses for non-compliance are accepted if legitimate. If there is a serious violation, penalties are likely to be minimal with a healthy abatement period available to the firm (Scholz 1984). 37 Gunningham and colleagues (2009) emphasized that the best way to motivate compliance is to promote legitimacy of the regulator and to enhance morality through procedural fairness. There is, however, little, if any, empirical evidence showing that the ‘advise and persuade’ model on its own leads to reduced workplace injury and disease (Walters, Johnstone, and Frick 2011a). The following is regulatory approach that is meant to address this critique by combining it with the deterrence model to make a more flexible system for regulating various workplaces with differing motivations. Inspector discretion: responsive regulation The two regulatory approaches discussed above, deterrence and compliance-based models, are considered opposite styles of enforcement, and proponents argue for one or the other based on the pros and cons for each. Deterrence is perceived by some as overly legalistic and strict in interpretation and heavy-handed and encourages corporate resistance via lobbying and legal challenges. In contrast, negotiated persuasive enforcement is perceived by others as failing to achieve the goals of regulations. Proponents are generally aligned politically with either a distrust of business and increased preference for deterrence strategies22, or with a distrust of government involvement and where the cost of compliance is seen as disproportionate 23 with an increased preference for cooperative enforcement (Scholz 1984). Even among compliant firms, relying entirely on penal enforcement can lead to regulatory resistance. However, relying on persuasive informal measures would provide no deterrence to those firms, that would only comply if subject to harsher penalties (Walters, Johnstone, and Frick 2011a). To balance these extremes, some inspectors began to intuitively combine the persuasive and deterrent approaches. Researchers examining inspectors in the field termed this combined approach “responsive regulation”. This regulatory framework was based on 22 This was seen in the 1960’s in the United Kingdom (Walters, Johnstone, and Frick 2011a) 23 Viewed in the “government small enough to drown in a bathtub” (Grover Nordquist, 2001) agenda of many of today’s conservatives in the United States. 38 observations of mine safety inspectors, and theories of game theory and restorative justice (Braithwaite 2011); as well as on regulations in pharmaceutical, nursing home, and trade industries. As such, responsive regulation is a flexible tool that can enforce the regulation of firms that are out of compliance for various reasons, including a lack of information, lack of focus, or a deliberate attempt to circumvent regulations. It is graphically demonstrated with a pyramid – an “enforcement” pyramid. This pyramid is illustrated in the model presented in Figure 3 above. Responsive regulation enforcement starts with a persuasive approach at the base of the pyramid and the assumption that firms will willingly comply. Deterrence is used when persuasive methods fail, generally when a firm refuses to participate in negotiations with a regulator and/or otherwise refuses to comply with regulations (Silbey 2013). This escalation to punitive approaches should be rare and only occur when all dialogue fails. When more moderate sanctions fail to have an effect, harsher punitive methods are applied. For example, when dealing with a recalcitrant firm, regulators may move from a request to a warning to civil penalties. These penalties can be reduced as a firm agrees to comply or can escalate to criminal penalties as a firm continues to refuse to comply. These methods can fail when it is nearly impossible to set financial penalties high enough to deter a highly profitable firm or where the firm cannot comply; in these cases, criminal penalties or firm closure at the apex of the pyramid are the relevant sanction (Braithwaite 2011). The main components of responsive regulation are the possibility of large penalties for recalcitrant firms, and discretion, where an inspector can make trade-offs so that small infractions of safety are not stringently so that focus can be put on more serious infractions (Scholz 1997). The actual mix of tactics should be adjusted to the circumstances and motivations of the firm under consideration (Gunningham 2010). In this way, responsive regulation was designed to be applied and figured out by inspectors on-the-ground, rather than though a top-down design of regulations. Responsive regulation was adopted by many agencies that had accepted that a punitive approach may “turn off” some employers that otherwise would have complied voluntarily, while motivating others with the threat of penalty (Silbey 39 2013). Responsive regulation is influential because it reconciles the fact that both persuasion and punishment seem to work at times and not at others (Braithwaite 2011). It also provides both instrumental (threats of punishment) and deontological (appeals to morality) aspects that the influential study by Paternoster and Simpson (1996) demonstrated (theoretically) were necessary in preventing corporate crime. An advantage of responsive regulation is that unwanted effects of the enforcement model can be minimized, such as resource intensive legal proceedings, tension between inspectors and regulated bodies, and the withholding of information from inspectors (Mascini 2013). Just the possibility of harsh punishments at the apex of the pyramid means that regulatory action can be taken care of persuasively, and inexpensively, using approaches at the base of the pyramid. With this possibility, regulators can be “threatening in the background” (Braithwaite 2011) rather than confrontational. There are a few requisites for this type of regulatory regime to work. This type of enforcement requires inspectors that are trained and mobilized for this type of responsive practice (Silbey 2013). In some cases, the inspectorate does not have the political support that discretionary methods of enforcement require. The media and public may view the regulator as an obstacle to economic activity, yet quickly blame the inspectorate when an accident occurs. Inspectors may not legally be able to choose what they feel is the most appropriate option. In addition, it is necessary to have severe penalties available and operable should the situation arise when they are needed. Without these, the system becomes untenable. Thus, a fairly common criticism of responsive regulation focuses on how difficult it is to implement successfully (Mascini 2013). Responsive regulation would also be highly ineffective without follow-up visits to determine the necessary next steps. Choosing the right enforcement style is an ability that is difficult to train. For example, it can take a great deal of skill to distinguish between an honest mistake and a calculated decision. Braithwaite has responded that there is a great deal of common sense that is used in this method and inspectors can get a feel for it if the method is presented as a natural social skill and inspectors are encouraged to lose the focus on regulating strictly ‘by-the-book’ 40 (Braithwaite 2011). In addition, the pyramid can only be used where parties have a continuing relationship (Gunningham 2010). Without it, there may not be enough interaction between inspectors and firm to clearly send messages of what is required. However, this continuing relationship may also lead to a sort of regulatory capture (as discussed above), affirming the need for independent and well-trained inspectors. This balance will vary from location to location. Rubin (2005) notes that cultural context, both surrounding culture and internal-to-the-firm culture, are relevant. Copying strategies from one location to another may not work as behaviour will also differ according to situational context, for example a punitive strategy that is effective in a culture where there is distrust of regulators and little internal motivation to comply may backfire and cause unnecessary dispute in a culture where compliance is the norm and non-compliance is usually the result of misplaced priorities rather than avoidance of implementing safety requirements. 2.7 Internalizing and Operationalizing the Results of Inspections in Organizations In the theories described above, the firm is conceptualized as a singular entity. Indeed, some economists view firms as more rational than individuals or other types of organizations, with executives having goals of monetary gain aligned with the firm, supported by departments that can explicitly calculate the costs of any decision (Sutherland 1983). Even though firms seek to be rational, the reality may be inconsistent decision making (Tombs and Whyte 2013). If the decision makers of a firm support improving safety after an inspection, but the firm cannot implement what is necessary, it is likely that the firm will not become safer. This last step in the model begins to show the limits of the inspection system in the cases where inspections may influence the motivations of the decision makers at the inspected firm but are not implemented at an operational level. There are a range of internal factors that determine a firm’s response to regulatory action. The organization of a firm is a complex combination of individuals and groups whose values may or may not be aligned with upper management decisions. In addition, individuals can come and go from a firm, and the composition of groups within firms changes (Bang 41 Dyhrberg and Langaa Jensen 2004). Those who are expected to implement the decision may not have had a say in whether or how to implement changes in the work environment, (Brunsson and Brunsson 2018a) which may lead to an unsuccessful implementation. Depending on the size of an organization, there can be multiple workplace cultures that can vary within the organization by department, hierarchy or other strata in which people are divided (Hoch and Kunreuther 2016). The following section takes a closer look at the inner workings of an organization, particularly the actors within a firm. The goals and values of the social actors in a firm contribute to a firm’s culture. It is possible that ignoring the internal workings of a firm may be appropriate in very specific scenarios: sole proprietorships, small owner-operator companies, firms with a very specific and defined hierarchy, or firms with very flat management structures with no middle management. In these types of arrangements, there may be a direct link between decisions made at the top, and the safety performance at the “shop level”. A firm’s employees will rarely have interactions with inspectors, since inspections are rare and only some firm representatives will be present for the inspection (Gray and Silbey 2011). In firms other than those described above, safety outcomes will depend on how the regulations and compliance filter down from the top levels to the frontline workers. Yet organizations can be quite complex: individuals may have interests that compete with others at a firm or with the interests of the firm itself, and the firm composition changes with some regularity as people are promoted, laterally moved, or leave the firm altogether. It is important to consider the functioning of an organization when discussing the safety outcomes of regulation and the response of management to regulation. Heimer (2013) suggests that understanding the middle manager, an informational conduit that translates information to workers, and taking time to contextualize regulation to regulated organizations will lead to better regulation. However, this may not work in all cases, as firms take many forms. Organizations’ behaviour is directed by both external factors, such as government regulation, and internal factors of the organization, such as size or corporate 42 structure. Although whether internal or external features are the dominant factor, depends on which researcher you are talking to (Rubin 2005). The structure of workplaces is changing, and the way that firms are regulated and dealt with may need updating. Workers at the same may be employed by several different firms, with many firms acting as subcontractors for several tasks. Within an organization, workers may be coming and going more quickly, as the gig economy shortens the duration of contracts (Wright 2018b). Regulators will need to respond with systems that can deal with this increased complexity. Note that regulators are also part of organizations subject to the complexities of any other organization as described herein. This means that these members may also act in contradiction to the goals of regulatory organization, and their decisions may be compromised by their own position in the organization or other personal limitations (Rubin 2005). Thus, critical analysis of the regulator’s functions to ensure that the responsive regulation is functioning as designed is warranted. Theoretical models of the firm The firm as a rational actor within the model of deterrence assumes that management is paid to protect the interests of the firm and that their actions and motivations always align with those of the firm. When the benefits of avoiding the risk of punishment of a firm outweigh the costs, management advises staff to take action to avert that risk (Tomer 1992). However, there are often other motivations for decision making by management and they may not act as a rational actor. In addition, there is variability between employees – not everyone in a firm shares the same objectives, and it is sometimes not possible to translate motivation into behaviour (Hutter 2001). Organizations are social constructions that contain individuals. They are based on the idea that decisions control the activities that are undertaken (Brunsson and Brunsson 2018a). Organizations appear to make decisions, but in fact it is individuals or groups of individuals that make decisions on the organization’s behalf. Even when speaking of “decision makers”, there 43 may be several people involved, each constrained by rules on the scope and type of decisions they can make. In the face of difficult decisions, leaders might avoid making a deliberate decision and instead go behind the scenes to achieve goals in intermediate ways. In addition, some possibilities will not even be thought of and considered in the analysis. Decision makers may also ignore information or make decisions before pertinent information is available. Accordingly these type of decisions may be seen as chaotic and emerging from a decision making process that is not orderly or logical; this type of decision making process is called the “garbage can model” (Brunsson and Brunsson 2018a; Cohen, March, and Olsen 1972). Once a decision is made, implementation is not a foregone conclusion. Decision makers have power over decisions, but not necessarily over actions of individuals in the firm; the interests of decision makers and their colleagues may diverge. Over-reliance on rational decision making may make decision making uncertain. Employees develop shared beliefs about the work, its performance, and which problems are a priority. They may seek to safeguard the best interests of their own activity, or act in accordance with their profession, or accept the goals of the decision makers, but not their methods of implementation. A further complication in organizations is that implementation of decisions can take a long time (Brunsson and Brunsson 2018b). Organizations are complex and economic models of organizations, particularly those that rely on the rational choice theory, tend to ignore important factors such as differing goals and values of the actors involved. However, it is important to try to understand their operations. From a legal studies standpoint, Rubin (2005) has attempted to apply organizational behaviour to responsive regulatory design to predict how different firms may react to the application of responsive techniques. Moreover, Rubin emphasized that a firm would need to be assessed thoroughly before it could be determined which theoretical model of organizational behaviour a firm would fit into. The first model, the Nexus of Contracts Theory Model, relies heavily on rational choice theory: each actor in an organization is motivated by self-interest and there is a series of 44 contracts between these actors within the firm. To affect change would require a great deal of information to optimize the intervention to the preferences of the many actors in the firm. The next model is the Decision Theory Model, where the firm is made of up individual decision makers but the way the firm is organized influences individuals greatly. Decisions are boundedly rational, with the bounds determined by an individual’s place in the hierarchy. Merely cosmetic compliance can occur where procedural rather than substantive changes are made, for example, workers affected by the regulations may decide to ignore rules to focus exclusively on the tasks directly related to their job function. Responsive regulation may be effective with this type of firm which would prefer to retain the status quo of a preference of getting along with the regulator. The third model is the Systems Theory Model. In this model the firm is like an organism with an internal system and a boundary separating it from the environment, desirous of maintaining equilibrium. The motivation of an individual accounts for very little as the organization is a unified entity with its own motivations and capacity to learn. To be effective on this closed system, any environmental stimuli, such as sanctions, must be the translated into a form the system can understand or absorb, and regulations must induce internal processes of change to be effective. As the use of responsive regulation can penetrate the organizational boundary via relationships with decision makers, it can effective. The above is not an exhaustive list of theoretical models of organizations. However, it is evident from the models that organizations are multifaceted and decision making in organizations is complicated. There is likely no one-size fits all method for achieving compliance. Sometimes penalties need to be applied to rational firms that have previously found it profitable to ignore safety, and sometimes a more complex organization may need a more holistic approach by addressing compliance issues at the core and the operational levels of the firm. It is difficult to determine which strategy must be applied without research; thus, it is necessary to be flexible, observant, and open-minded in approaching enforcement. Responsive regulation appears to be at least as effective as traditional enforcement methods when considering each of the preceding organizational models. Even if the motivation 45 or structure of the firm is not known to the inspector at first (or perhaps ever), the flexibility of the approach, along with the building of relationships that can occur with responsive regulation, means that it can be applied to most firms. This effectiveness can arise partly because some firms are generally amenable to this strategy, and partly because the strategy can be adapted to other firms that do not immediately respond. Once again, the need for a perceptive and well-trained inspectorate is clear. When looking into the interior workings of an organization, the presence of a safety culture within the organization is also an important and related consideration. Compliance and safety in an organization: safety culture Safety in an organization can be complex; social interactions and individual reactions are some of the many factors that may affect the implementation of management actions. An organization’s values influence the level of effort given to safety matters and plans, and the initiatives used to manage safety. There are many actors and levels within the hierarchy involved in creating safe workplaces; and each of these actors and levels takes information, passes on judgement in the form of regulation or instructions, for example, and ultimately “seek(s) to motivate workers and operators, to educate them, to guide them, or to constrain equipment design, so as to increase the safety of their performance” (Rasmussen 1997, p. 184). These factors come together as culture, meaning both shared values by the members of the organization, and patterns and organization styles that are passed onto new members (Kotter 2008). If procedures, meetings and assessments are in place, but not integrated into the firm’s culture, they will be ineffective in preventing injuries (Walters, Johnstone, and Frick 2011b). Culture can be viewed variously as: identical to the organization, a variable in an organization, the glue or orientation/compass of the organization, a series of subcultures that are distinct but interlinked, or a web of varied individuals with loose connections. The latter approach embraces the inconsistency that can arise from a group of individuals in an organization. It may be possible to change culture from the level of decision makers, but 46 generally a change in culture may need more of a bottom up approach, even though this targeted approach can yield unpredictable results (Hoch and Kunreuther 2016). Culture shapes the attitudes of employees regarding the importance of safety and how they approach safe work practices (Tharaldsen and Haukelid 2009). As Törner (Törner 2011) sees it, mutual trust and a good relationship between workers and management is key to contributing to organizational goals; if these goals are demonstrated to include safety as a high priority, this would incent workers to behave safely. In a qualitative study of inspections of Ontario manufacturing plants, researchers found lower lost-time injury rates were associated with paternalistic initiatives, record keeping of occupational health and safety (OHS) measures, greater involvement of workers in decision-making, better managerial attitudes towards the importance of OHS, and a higher engagement of workers versus management members on the Joint Health and Safety Committee (Geldart et al. 2010). Safety culture can be considered (in a commonly cited definition by Hoch and Kunreuther (2016)) as: “…the product of individual values, attitudes, perceptions, competencies, and patterns of behaviour that determine the commitment to, and the style and proficiency of an organization’s health and safety management” Culture can also defeat the implementation of safety rules. In a practical example, Huising and Silbey (2013) conducted an ethnographic study in university laboratories and concluded that, even in this highly supervised and supported environment, those with higher status, such as physicians or executives, can avoid rules and regulations via their privilege. Organizational cultures that may contradict directives from management that are misapplied. In some cases directives from management are adapted by supervisors who need to take into account competing demands such as safety versus productivity) resulting in differential implementation of formal procedures by department within an organization (Zohar and Luria 2005). Further, an organization’s culture that leans towards a more individual responsibility for safety approach, can result in workers that disregard safety as it is considered a low priority for the organization. This means that sometimes people bypass their own personal safety for other 47 types of safety, such as the safety of equipment (Turner and Gray 2009). In a study of safety in a molecular biology laboratory, (Bruns 2009) noticed that the concept of workplace safety was intertwined with the “scientific objective of experimental accuracy”; some safety routines were adhered to more strongly, often depending on how that safety routine meshed with laboratory tasks. Employee empowerment and participation may then contribute to the realization of intentions for a safe workplace into good safety behaviour. This effect can be seen in a study by Gunningham and Sinclair (Gunningham and Sinclair 2009). When looking into the implementation of management-based regulation in mining firms, they found that the implementation was far more effective at mines with higher trust levels between workers and management. With a higher functioning safety culture, the requirements for compliance after an inspection will more easily integrate into the firm, reducing the probability of non-compliance and future escalations up the pyramid. 2.8 Implementing Safety at the Worker Level Power imbalance between workers and management Many discussions of organizations, workplace safety, and regulation miss an important argument about the issues of power dynamics within a workplace. Researchers may recognize that management has greater power, but do not always acknowledge the counterpart of “the diminished power of those in subordinate positions in firms” (Gray and Silbey 2011, page). Power dynamics and the influence of power conflicts can affect all aspects of organizational culture (Hoch and Kunreuther 2016). Antonsen (Antonsen 2009), in describing power and safety culture, considered that power was neglected in cultural discussions of safety. Pragmatically, culture is of interest to firms because it is understood and is applicable to safety management. Safety culture is intrinsically related to power as it is fundamental to the processes that create a culture in a workplace. Also often neglected in the study of culture is the fact that it will vary according to levels or parts of 48 an organization. Power is difficult to define, but it can be described as an expression of one of three dimensions as outlined by Antonsen. The first is intentional power, based on advantages of position, expertise, resources, coercion, networks, and personal power and exercised in a rational, calculated manner. This may manifest most obviously in the power employers have over employees. The second dimension of power is less visible. It is the ability to keep issues out of the decision-making process, excluding them from the agenda. For example, issues such as the workplace effect on mental health were kept out of regulatory overhauls until recently. The final dimension is the symbolic power that perpetuates bias in favour of those holding power. Since safety culture and management were based on a top-down hierarchical view of the organization, any discussion of power in relation to safety culture could only address the first dimension. Ultimately, neglecting power reduces the scope of safety culture in a way that ignores important concepts and the fact that conflict between management and the shop floor is inherent in safety management and culture. Crucially, safety management and other attempts to control the narrative of safety culture can become manipulative (in the third dimension) and silence important voices, opinions, and organizational learning. This in turn can reduce the safety for the organization or at least render safety management approaches less effective. As reduced regulation has become more prevalent in higher income countries, there has been a renewed focus on individual responsibility, which may cause concern due to these power imbalances as worker may not have the agency to comply with regulations. An example of this individual responsibility is a ticketing program where workers are ticketed for health and safety violations. This can lead to uncomfortable situations where workers can either refuse unsafe work and risk the ire of supervisors and perhaps coworkers or risk a financial harm in the form of a ticket. It also casts employers and employees as “equal partners” in striving for safety. This assumes an equal power balance that is likely not the case as workers may need the firm more than the firm needs an individual worker. It also assumes that workers have enough information about the full risks of workplace hazards in order to do a cost-benefit analysis of 49 compliance or non-compliance (Gray 2006). The equal responsibility given to employer and worker for safety may not benefit the worker maximally as it neglects to address the power imbalance inherent in work hierarchies. Individual workers A threat to the successful implementation of safety interventions is a factor known as “risk homeostasis”. This is a theory that describes a tendency to push boundaries when safety measures are introduced. Or stated another way, people change behaviour when their environment changes, and safety measures change our environment, thus potentially changing behaviour. At a firm level, the protection provided by evolving safety technology has been converted into “productive advantages”. For example, mine owners opened mines to deeper exploration when new lamps were introduced that did not ignite combustible gases, and marine radar encouraged ship owners to travel more quickly through confined seaways (Reason 1997). Drivers are thought to adapt their driving to safety features in order maintain an ‘acceptable level of risk’ or ‘safety margins’, though recent studies found that drivers adapt their behavior based not on the perceived risk but on the perceived task difficulty (Mitropoulos 2009). Risk compensation occurs if the reaction to safety measures is to “use up” the additional safety through more risky actions to a safety law or regulation is by acting less safely. Though risk compensation can be evaluated using individual or aggregate before and after regulation, it is difficult to measure. It is thought that risk compensation occurs in response to only some safety measures, those which are more visible, for example. Thus, it is preferred to change safety measures to those that are effectively invisible, do not impact motivation in a way that conflicts with safety, does not affect tasks significantly, and that are in a more controlled environment (Hedlund 2000). Organized labour Another part of the workplace that is important to safety is the presence of organized labour. Collective action be an important tool to improve safety. Unions can raise political awareness and lobby for changes that can bring about improved OHS regulations (Donado and 50 Wälde 2012). The presence of unions can have an impact on safety at the firm level as well: both the safety at a firm and the effect of an inspection on safety. Firms that are unionized have been shown to be generally safer. It has been found that adherence to regulations is generally higher in the presence of organized labor (Morantz 2017). A study of the effect of union membership on injury claims in Ontario construction firms demonstrated that unionized workplaces have lower lost time claim rates (Amick et al. 2015). Another study found fewer severe injuries and fatalities at unionized firms (Morantz 2017). While the evidence shows that unions further the objectives of safety regulations, the relationship between unions and safety is not universal, depending on jurisdiction, industry, employment rates, and union leadership (Morantz 2017). There are several reasons that unions work to improve safety. Collective bargaining can be used to allow union members the right to refuse unsafe work in areas where this is not enshrined in law. Unions can also provide safety information and training, provide credibility to safety programs that they co-develop, and the very presence of unions with the possibility of work stoppages can increase management awareness of safety concerns. Among workers, unions can facilitate active employee involvement in workplace safety (Sinclair, Martin, and Sears 2010) and increase the effectiveness of occupational health and safety committees (Weil 2014). Besides improving safety at a workplace, unions can also mediate the effect of inspections on injury rates. Unionized workplaces are more likely to have an employee representative accompany an inspector during the tour of a facility (Morantz 2017). Walters (2006) goes as far as saying non-unionized workplaces should have additional support to be able to engage and have representation with inspectors. Unions can help to keep firms accountable for safety: unions can help workers report unsafe conditions or file claims and provide information on safety and worker rights with regards to reprisals (Mishel and Walters 2003). This may increase the likelihood that someone is watching to ensure recommendations from orders or citations issued to a firm are implemented. There is evidence that unionized establishments are inspected more often, more intensively, and with higher penalties. Union membership can also 51 have an impact on reporting rates, which may affect the reported injury rate, biasing it upward when studies are conducted (Hirsch, Macpherson, and Dumond 1997; Amick et al. 2015). The support of a union has become more crucial as workers have less contact with the inspection system due to self-regulation and dwindling inspection resources in some jurisdictions (Tombs and Whyte 2013). Indeed, Ayres and Braithwaite argue that tripartite efforts with workers, unions and employers, improve responsive regulation and prevents regulatory capture (Ayres and Braithwaite 1992). 2.9 Discussion The foundation of the model proposed in this dissertation is a responsive regulation regime that is viewed as legitimate by the firms being inspected. Part of this legitimacy is being consistent as well as being responsive to firms, which is a difficult line to successfully navigate. Inspections should be looking for compliance with regulations that were designed (ideally evinced) to result in a safer work environment. They may be prescriptive or performance regulations, but ideally there is a sociotechnical component to help address the fact that there are social aspects to safety. It is important to target firms for inspection in a strategic manner; the use of data analysis is likely to be a valuable tool here. If firms are not at risk of having unsafe conditions, it is less likely that the inspection will lead to a measurable improvement. In addition, a transparent and fair targeting program will add to the legitimacy of the regulator. The probability of inspection relates to general deterrence and inspections should be frequent enough that firms feel inspections are a real possibility and that other firms are likely to be inspected, which should instill a sense of fairness and increase legitimacy. Once on site, high quality inspections are needed to identify unsafe conditions and areas that need improvement. This highlights a need for a well-trained, professional group of inspectors. During the inspection process, both deterrence and compliance methods can work to achieve compliance, depending on the firm. The combination of compliance motivations may vary from firm to firm and responsive regulation. Firms may even have motivations that 52 compete, and policy makers need to speak with voices that appealing to morality, the bottom line, or both, for example. An effective inspector will consider compliance and deterrence methods during inspections and dialogues with the firm to find the right balance. If the firm is motivated only by maximizing utility, the deterrence model will be the preferred method as the firm will only comply if the cost of compliance is lower than the cost of being out of compliance. If the firm is well-meaning but lacks the motivation or ability to comply, the compliance model will be more effective, and the deterrence approach may cause these firms to become adversarial and reluctant to comply. However, responsive regulation can be useful since it is likely unknown what type of firm, with what motivations, inspectors are dealing with. With responsive regulation, firms are assumed to be willing to comply with regulation. In the case that the firm does not comply, the discretion of inspectors and a relationship with firms will help the inspectors to determine a path to achieving compliance. The inspector would begin the process with the assumption that the firm is well-meaning and that persuasive methods be the starting point. If this fails, it is important that the inspector can escalate to punitive methods. These methods should always be in the background, available if the situation calls for them, but noting that legitimacy can be gained when a punitive style is used sparingly because this back and forth can impart fairness (Braithwaite 2011). Particularly in an era where self-regulation and management systems dominate, the regulator may need to penetrate the organization boundary and speak the language of the firm to motivate management. In the case that firms have enough motivation, but lack know-how or have competing demands for attention, regulators may need to move beyond motivating firms, towards facilitating safety. Responsive regulation can be a useful instrument to address these issues, with the caveat that a professional inspectorate with a high level of specialized training is necessary. However, it is possible that inspections are not the correct tool for improving safety at organizations with complex internal systems. Or, in the case that inspections do help, the 53 changes at these firms may take a long time to implement; in this case the effects could be long term, gradual, and very difficult to measure. Ultimately, the effective inspections have several requirements that boil down to the appropriate application of responsive regulation with a knowledgeable inspector armed with the appropriate regulatory tools for the cultural and organisational characteristics of any firm. From a theoretical perspective, for an inspection to be successful at reducing injuries at a firm, it must:  Be enforcing legitimate and technically effective regulations, with  An inspector that has the skills to capture unsafe conditions, at a  Firm targeted for maximizing efficiency, with  Motivation (fiscal or otherwise) or resources provided as necessary to help the firm implement the required changes. Inspections may not be the most appropriate intervention at firms with hard to penetrate boundaries or very complex internal workings, in which case the addition of self-regulation activities such as safety management programs may be more effective. Another limitation of this model is that, though it is likely to work in a similar manner for occupational diseases, the time periods required for diseases to develop (sometimes on the order of decades) are much longer than the hypothesized time that the effects of an inspection last (see section 3.8 for details). This chapter summarized a model that explained and incorporated the most important components of the inspection process. This model may be used to determine why inspections may or may not be effective. The next chapter is an examination and deeper interpretation of previous studies of inspections to determine what part of the regulatory context may be important in explaining the results of these studies. 54 What does an inspection mean? Putting previous research in context 3.1 Introduction As Almond and Ebester (2018) note, the “processes of regulatory inspection are highly variable in practice, differing according to the degrees of formalism, coerciveness, intensity, discretion, and prioritization used.” When studying an enforcement program, it is important to know the characteristics of the enforcement process, particularly if that system is persuasive, deterrent, or responsive. The probability of inspection is also key as it can affect general deterrence. As such it is crucial to consider the regulatory context of an inspection in understanding what features of inspections and under what circumstances they may lead to improved health and safety outcomes. The focus of this chapter is an examination of the previous studies of inspections and how the characteristics of these inspections and the environment in which they operate may impact the outcomes of inspections and the results of those studies. This is important information to policy makers attempting to apply the results of these studies to other jurisdictions. This chapter will begin with a detailed summary of each study and a short review of the regulatory system in the jurisdictions of these studies. Then descriptive statistics will be applied to publicly available data to determine if any of the differences in findings between the studies may be explained by differences in the way that inspections and enforcement differ between the jurisdictions. By comparing the outcomes of each study, in concert with a summary statistical analysis of enforcement data provided online by OSHA for each jurisdiction studied, a more detailed overview is provided. This background can be used to describe the regulatory systems that may be relevant to those interpreting the results of the reviewed studies for use in other jurisdictions. This background is not meant to be exhaustive; rather, this chapter is a complement to recent systematic reviews of the effectiveness of occupational health and safety interventions to provide more detail and context to the most relevant studies on 55 inspections. The effectiveness of inspections has not been studied in most jurisdictions and only a few studies are examined here. The studies examined were one of penalty inspections of manufacturing facilities in Pennsylvania (Haviland, Burns, et al. 2012), one of random inspections in California (Levine, Toffel, and Johnson 2012b), and one of inspections and consultations of firms in Washington (Foley et al. 2012). The results of this chapter can be used to provide a better comparison of previous research to the British Columbia inspection context. In addition, the results can be a useful guide for future intervention studies. Finally, the review conducted in this chapter, along with framework presented in Chapter 2 forms the basis of the hypotheses that will be tested in Chapter 5. 3.2 Background Occupational Health and Safety Regulatory Agencies generally have broad powers to enter and inspect workplaces, impose sanctions, and even to prosecute health and safety offences as a criminal matter (Walters, Johnstone, and Frick 2011a). How these broad powers are used, and the processes involved in firm targeting, inspection activities, and citation and appeals process vary from jurisdiction to jurisdiction. Often, when the effect of these inspections on injury rates are studied and published, little information is given on how the mechanism of inspection and what tools inspectors can and do use. The included studies in the literature review represent three jurisdictions in the United States – California, Washington State, and Pennsylvania – that have similar regulatory systems, due to the requirement that the regulations in State plans (California and Washington State in this case) must at least be as effective as those set by the Federal Occupational Health and Safety Administration states (Pennsylvania). Though many State Plans adopt standards identical to OSHA, State Plans have the option to promulgate standards covering hazards not addressed by OSHA standards (“Directorate of Cooperative and State Programs | State Plans | Occupational Safety and Health Administration” n.d.). 56 Given that the conclusions of systematic reviews on the effect of inspections have been equivocal (Mischke et al. 2013; Tompa, Trevithick, and McLeod 2007; Tompa et al. 2016), the regulatory context may be a key factor in understanding whether an positive intervention effect is observed in a particular that workplace safety inspection study. This can make the results of these studies more useful to other jurisdictions and help to clarify why inspections may or may not work to reduce injuries. This information should also be included in systematic reviews as they have tended to be focussed more on the quality of the study included, rather than the characteristics of the inspection and the jurisdictional context. Of importance in analysing regulatory interventions for the prevention of workplace accidents is an explanation of whether the regulatory systems studied are responsive, deterrent or persuasive. Deterrent systems, in the context of workplace safety regulators, are those that rely on penalties, or other forms of punishment such as closure orders, for achieving goals. Persuasive systems will have very few penalties and mostly rely on consultations, education, and persuasion, rather than using punishments. A hallmark of responsive systems is that penalties are infrequent, but can be considerable, and there is flexibility in the methods inspectors may use to achieve compliance. Also important in describing inspections are the following characteristics:  the frequency and probability of being inspected, as when there is greater general deterrence due to higher probability of inspection, the impact of the specific deterrence of an inspection may be a greater shock or wake up call,  the type of inspection that is included in the study (for example, programmed or complaint),  how a firm is chosen for inspection in planned or programmed inspections, and  what types of firms were studied (particularly industry sector and size). 3.3 Occupational Health and Safety Regulators and Inspections in the United States The Occupational Health and Safety Administration (OSHA) was created in 1970 by the United States Congress “to assure safe and healthful conditions for working men and women by 57 setting and enforcing standards and providing training, outreach, education and compliance assistance.” The agency covers most private sector employers and workers in the United States. Coverage is provided either through federal OSHA, or through a state OSH plan that has been approved by the federal OSHA. The state agencies relevant to this study are Cal/OSHA in California and the Division of Occupational Safety (DOSH) in the Department of Labour and Industries (L & I) in Washington State. The State plans are monitored by the Federal OSHA, that also provides some funding for State OSH plans, and the programs must be “at least as effective” as the Federal OSHA program24 (Occupational Safety and Health Administration n.d.). Nevertheless, OSHA does not rigorously evaluate the effectiveness of the Federal OSHA or any of the State OSHAs are (Gingerich 2008). In overseeing State OSHA plans, OSHA's monitoring has been reduced from a system of intensive on-site reviews of state files and observing inspectors at work, to a goal-based system with federal OSHA merely ensuring that states developed performance plans and ensuring the states met their own goals. This changed in 2009, with changes to increase oversight of State plans, though this falls beyond the time period examined here (Gingerich 2008). As of 2008, the United States had, in aggregate, less than one inspector per 75,000 workers (Weil 2008) although the ILO standard suggests a minimum of one per 10,000 workers (International Labour Organization 2006b))25. All state and federal OSHA plans have workplace safety inspections as part of their prevention and enforcement programs. OSHA, Cal/OSHA and Washington DOSH all have priorities in allocating inspection resources. Generally, compliant and serious accident investigations are prioritized ahead of programmed or targeted inspections (Occupational Safety and Health Administration 2016; Safety 2009; Cal/OSHA 2017). Federal and state OSH inspections are similar, and are conducted as follows: 24 This is vaguely defined by OSHA. 25 Using 2017 data from the US Census at factfinder.census.gov(Bureau n.d.), as well as OSHA statistics(“Commonly Used Statistics | Occupational Safety and Health Administration” n.d.) there were 2100 inspectors for 109,307,428 full time employed persons 16 and over, which means one inspector for every 52,000 workers. If including all workers, including part time and seasonal, this becomes one inspector for every 76,500 workers. 58 1. The inspector conducts background research on the worksite, and the compliance and inspection history of the site, presents credentials, and conducts an opening conference with the employer or representative. 2. A walk through and review of records is conducted. 3. In the case a violation is found, the inspector can issue a fine or a warning that has no financial penalty but is formally recorded. 4. Officers may also simply request that the employer correct identified apparent violations on the spot in a show of good faith, though the violation will still be recorded. 5. Finally, a closing conference is conducted. After the inspection, if the employer is unsatisfied with the citations, they will have an opportunity to arrange for an informal conference to discuss citations, penalties, abatement dates or any other information pertinent to the inspection. If a citation is issued, the agency and the employer may work out a settlement agreement with a main goal of correcting hazards and maintaining compliance, rather than collecting fines. If an agreement is not found, the employer may formally contest the citation and/or penalty (Jung and Makowsky 2014). The ability to have citations or penalties, that can range from serious (maximum $13,260 US for national OSHA violations), willful ($9,472 US to $132,598 US), repeat ($132,598 US), or de minimis ($0), are a strong indication that some sort of penalty pyramid is used in the United States (Occupational Health and Safety Administration n.d.). Though inspections are similar from jurisdiction to jurisdiction, there are also differences in the operating of OSH programs. Most notably is the amount of resources spent on OSH inspections. In 2007, the 203 inspector positions (17 of which were unfilled) meant there was an inspector to worker ratio of 1:84,860 in California. This is compared to 1:26,904 in Washington, and 1:50,166 on average in other state OSH plan states26 (Brown 2007). These varying inspector to worker ratios across states may mean that the general deterrence effects of inspections vary with lower inspector to worker ratios leading to smaller general deterrence 26 According to the same author, the ratio was about 1:10, 564 in British Columbia that year. 59 effects. Specific deterrence, or the impact of an inspection on an individual firm, may be more effective in jurisdictions with a low inspector to worker ratio. There are also administrative differences in OSH programs. Federal OSHA directors and inspectors are employees of the Department of Labor and are part of the Executive Branch of the federal government, with overseers appointed by the President of the United States. State agencies that are overseen by OSHA but are not part of the federal government, have a more complicated hierarchy. This enables greater connections to other stakeholders, including political bodies at the state and local levels, businesses and their representatives, and communities. The net result is that state OSH agencies have independence and can sympathize with local labour forces and businesses operating in those states. (Jung and Makowsky 2014). Another way in which OSH regulatory programs can differ from state to state or region to region is the way inspectors use their discretion. With the opportunity for inspectors to choose between a citation with no penalty and a fine of varying amounts creates the opportunity for OSH agencies, through their inspectors, to wield a significant amount of discretion. Jung and Makowsky (Jung and Makowsky 2014) examined the effect of politics on discretionary enforcement. They found that there is some influence of local and presidential politics on violations found during inspections. When a Republican presidential administration was in power, there was a slightly higher chance of inspectors finding a violation in federal OSHA states, and an even higher chance in State plan states. In states with State plans, higher unemployment was associated with fewer violations found per inspection, with greater and more fines to firms with identified violations. State OSH agencies also tended to issue smaller fines and to reduce them less on appeal. This can lead to fewer challenged fines and thus fewer legal proceedings (Jung and Makowsky 2014). In sum, though State and Federal plans are mandated to be similar, in practice the way inspections are executed in each jurisdiction differs. The probability of a firm being inspected varies greatly from state to state, affecting general deterrence and creating a possibly higher specific deterrence impact of an inspection in states with a lower frequency of inspection. In addition, the administration of the Federal and State plans via inspections can be impacted by 60 external forces such as the government in power, economic situations, and unemployment. These factors can influence the way inspectors in each state decide whether to impose financial penalties on firms that are found in violation. 3.4 Summaries of previous studies The three studies of inspections in California, Washington, and Pennsylvania were chosen for inclusion here. The studies are summarized in Table 1 and described in following sections. Table 1 Previous studies on inspections examined in this chapter The three included studies looked at similar time periods in the late 1990s to early 2000s, though the number of inspections examined varied. The type of firm studied also varied from study to study. While the California and Washington State studies examined firms from most industries, the Pennsylvania Study examined only manufacturing firms. Smaller firms of 10 or fewer employees were excluded as these firms generally do not receive programmed inspections under OSHA. Study Reference State Inspecting Agency Time Period Number of Firms Inspected Randomized Government Safety Inspections Reduce Worker Injuries with No Detectable Job Loss(Levine, Toffel, and Johnson 2012b)CaliforniaDivision of Occupational Safety and Health, aka Cal/OSHA1996-2006 389The Impact of Regulatory Enforcement and Consultation Visits on Workers’ Compensation Claims Incidence Rates and Costs, 1999–2008(Foley et al. 2012) WashingtonDivision of Occupational Safety and Health, part of the Department of Labor and Industries 1999-2008 7112A New Estimate of the Impact of OSHA Inspections on Manufacturing Injury Rates, 1998–2005(Haviland, Burns, et al. 2012)PennsylvaniaFederal Occupational Safety and Health Administration1998-2005 2,18361 California: Cal/OSHA and the 1996-2006 study California has been a State plan since 1977. Targeting for inspection by Cal/OSHA is performed using a risk-based system. It begins with a list of industries with high rates of preventable injuries and workers’ compensation losses27. This list is then limited to firms with more than 10 employees, and firms are chosen randomly from that list. Within each district, managers can also prioritize based on time since last inspection and industry. Inspectors attempt to inspect all the randomly chosen establishments, although managers may choose to leave out industries they deem less dangerous. Workplaces that had already had an OSHA inspection in the prior two years may also be skipped. Cal/OSHA also does not consider as many hazards as serious as OSHA does28. This has led OSHA to conclude that Cal/OSHA’s Program Targeting System is not identifying and targeting industries where serious hazards are more likely to exist (Occupational Safety and Health Administration 2009). In 2009, California had a lower rate of serious violations than most other states, perhaps because of the way that serious injuries are classified 29. The Californian commission that reviews appeals of citations considers a violation to be serious only if the violation was “more likely than not” to lead to a serious injury. Federal OSHA, and most other states, only look at the possible injuries caused by the violation, and do not consider the probability of injury. However, California levies substantially higher fines for serious violations than other states do. Willful, repeat, and failure-to-abate violations are also rarely cited by Cal/OSHA. In California, there is often no follow-up of citations. For the 2006-2007 fiscal year, officers only verified that 61% of the citations issued were abated. In addition, citations are often appealed. As of 2007, there was a more than a two-year backlog of appeals of citations. 27 From California Labor Code, Section 6314.1 28 Cal/OSHA does not ensure violations that would be considered “Serious” under the Federal Field Operations Manual are classified as Serious. 29 Cal/OSHA does not ensure violations that would be considered “Serious” under the Federal Field Operations Manual are classified as Serious. 62 This backlog was created following a significant increase in civil penalties in 2000, without a concomitant increase in the staffing required to keep up. Since employers are not required to abate citations under appeal unless there is a rare repeat visit30, changes required by citations are often not actually complied with until years later, if at all (Brown 2007). The study on workplace inspections in California was conducted by Levine et al. (Levine, Toffel, and Johnson 2012b) using data from inspections by Cal/OSHA during the period 1996-2006. Follow up was for one to four years after the inspection. The researchers not only followed up on injury claims, but also costs of injuries and survival rates for the firms. The 409 firms that were randomly inspected in that time period were compared to 409 matched firms that had not undergone an inspection. The matching process (matched to region, industry code, and employee numbers) led to a loss of some firms; the net result was 389 treated and 376 untreated firms. Injuries at the randomly inspected firms declined by 9.4% if inspected in that year or the previous year. Injury costs were also reduced significantly (26% reduction) after inspections. Inspected firms did not tend to lose employees or close more frequently than the control firms. Washington State: WISHA 1998-2008 study Washington State has had a State plan since 1982. The Washington plan (referred to as WISHA in the article, now referred to as DOSH – Division of Occupational Safety & Health) covers private employers, and state and city governments, but not federal government worksites. The DOSH targets firms for inspections using risk-based methods of claim history, injury and illness rates, and the safety performance of the industry to which a firm belongs. Inspections are prioritized by industry membership and time elapsed since the previous inspection, as well as complaint inspections, rather than company-level claims rates. Occasionally, a special emphasis program may be established by the state or federal OSHA. 30 Repeat visits would be conducted under imminent hazard laws. 63 After an inspection, the hazards found by the inspector and reported in the citation and notice document must be corrected within the time period specified. If this is not possible, an extension may be applied for, or an appeal may be registered, though the hazard must be corrected by the abatement date unless a stay is also requested (Workplace Safety and Health Council 2010). Foley and colleagues (2012) examined 10 years of data to investigate the effects of consultation and enforcement visits on injury rates. They looked at single location firms with at least 10 full time equivalent employees that had not received a consultation or enforcement visit in the previous two years. The analysis evaluated programmed inspections (68% of total inspections), complaint inspections (26%) and referral inspections from other agencies (6%). Fixed and non-fixed work sites31 were examined separately, as were consultation and enforcement (and consultation plus enforcement). The results were that at fixed worksites, non-musculoskeletal lost workday injuries decreased by 26.9% after consultation and 9.5% after enforcement. At non-fixed worksites, the injuries decreased by 11% after consultation and 3% after enforcement. When looking at enforcement visits with or without citation, firms that had inspections without a citation saw a non-significant decrease in non-musculoskeletal disorder (MSD) lost-workday claims. Firms that received a citation saw a 22.1% (fixed site) or 21.2% (non-fixed) decrease in non-MSD lost-workday claims. The authors also looked at MSD claims and found that enforcement at fixed-site workplaces was associated with a decline of 11.5% in claim rates in the second year after an inspection, though not in the first year after the inspection (non-MSD claims rates were not studied in this second year). This was hypothesized to be due to the longer latency period of these types of injuries. 31 Non fixed sites are those firms in the construction and transportation industries. 64 Pennsylvania: OSHA 1998-2005 study Pennsylvania is a state that relies on federal OSHA for regulation and enforcement. Like targeting in the state OSH plans, imminent danger situations, complaint and serious accident investigations are prioritized ahead of programmed or follow up inspections. An inspection may result in a pass, a citation(s) with a warning, or a citation(s) with a penalty. The citation and proposed penalty, with a deadline for abating the hazards, must be issued within six months of the inspection, or from the violation’s occurrence if it was at another time (Jung and Makowsky 2014). Haviland et al. continued a series of studies on OSHA inspections on single location manufacturing firms in Pennsylvania32 with a 2012 paper, updating results that showed inspections with penalties reduced injuries, though the effect over three studies since the 1970’s had been decreasing. By the 1990’s, the results appeared to show that penalty inspections were no longer effective at reducing injuries. However, in the 2012 study it was found that, for firms with 21 to 250 employees, inspections with penalties reduced injuries by an average of 19% to 24% annually in the two years following the inspection. The researchers found no change in injury rates associated with inspections that did not levy a penalty. There was also no significant effect on firms with more than 250 employees and 11 to 20 employees. The study looked at programmed, complaint, and referral inspections, though only about two-thirds of the inspections were programmed inspections. This contrasts with the California study described above, where all the inspections evaluated were programmed inspections. During the time period of the study, firms were targeted for safety inspections using lists of employers in industries with high injury rates and more specifically targeting the most hazardous workplaces using injury data (Occupational Health and Safety Administration n.d.). This contrasts with the inspection targeting systems that were utilized during the previous time 32 Manufacturing is a significant contributor to the Pennsylvania economy, though it decreased to about 15% of the labour force by 2005, down from 20% during the earlier time periods studied. 65 periods studied in Pennsylvania – before 1995, employers in high risk industries were targeted regardless of their individual safety performance. However, in the sample looked by Haviland et al., only 10% of the programmed inspections were part of the Site-Specific-Targeting program (in contrast, 30% of programmed inspections are initiated by OSHA are part of this program). When looking at the complaint and programed inspections separately, the results for complaint inspections were different. The programmed inspections resulted in similar effects to the whole sample (not surprising as they comprise two-thirds of the sample) but there was no effect over two years for complaint inspections. When the researchers investigated in more detail, there was an increase in injury rates in the year of an inspection with no penalty, though in the following year, there was a decrease in injury rates regardless of whether there was a penalty. The authors suggest this could be due to either regression to the mean after an injury due to the unsafe conditions triggering the complaint, or that the inspection helped to decrease the injuries. Since this drop is the same regardless of penalty, the authors preferred the regression to the mean explanation. However, in previous Pennsylvania studies it was argued that this similarity in results is merely due to the fact that complaint inspections act through a different mechanism than programmed inspections, where the employer is responding to the fact that an employee complained, rather than to the findings of the compliance officer. Summary of previous studies results Generally, it appears as if inspections with penalties are more effective than those without penalties, and usually in the year after an inspection, although modest injury reductions were also found in the third and fourth year after an inspection in California. Consultations may also be effective in some circumstances, although this is only based on one study, and future research is warranted. Table 2 below shows a summary of the results of previous studies. 66 Table 2 Summary of results of previous studies of the effect of inspections on injury rates In the study of Pennsylvania manufacturing firms, Haviland and colleagues (2012) found that inspections without penalties did not lead to a decrease in injury rates. Inspections with a penalty were followed by a 13.4% decrease in injuries in the following year. The results for two to four years after an inspection with penalty were reported as insignificant and the authors of the study did not publish the change values for these results. They also found that inspections with penalties had no significant effect in the two-four years after an inspection. Foley and colleagues (Foley et al. 2012) found that Washington State DOSH enforcement inspections were linked to a 3% decrease in non-MSD lost-workday claims at non-fixed sites and a 9.5% decrease in fixed sites. The effect of enforcement was much greater if a penalty was involved: 22.1% and 21.2% decreases in fixed and non-fixed sites, respectively. Consultations were more effective than enforcement inspections at fixed sites; the effect was also greater at non-fixed sites, but the result was non-significant. Levine, when looking at Cal/OSHA inspections, found that programmed inspections, without stratifying into inspections with citations or penalties, were linked to a decrease of 14% in the year after inspection, and decreases in the third and fourth year after as well. Year of Insp.Year After Two Years After Three Years After Four Years After Levine et al.CaliforniaAll Workers' Compensation ClaimsProgrammed (Random) All14.1%** 2.30% 3.20% 12.6%+ 23.4%**Fixed Site 9.5%**Non-Fixed Site 3%+Fixed Site 26.9%**Non-Fixed Site 11.20%Fixed Site 6.80%Non-Fixed Site 5.20%Fixed Site 22.1%**Non-Fixed Site 21.2%**Haviland et al. PennsylvaniaLost time (at least one day) With PenaltyFirms 20-250 Employees 13.4%**Enforcement with Citation**P < 0.01, +P < 0.10Type of Injury Type of Inspection Type of FirmInjury Reduction in Follow up PeriodFoley et al.Washington StateNon-Musculoskeletal Disorders, lost workday claimsEnforcement Consultation Enforcement with no Citation67 In sum, it appears that inspections with penalties or citations are effective while inspections without penalties are not, particularly in Washington State. Consultations can also be very useful in injury reduction in some cases. The Cal/OSHA study did not provide information on citations or violations, but inspections in that state do appear to impact injury rates. Following is an analysis of inspection data in the states of Washington, Pennsylvania and California was completed to determine if differences in the frequency and type of inspection related activities might explain the differences in the effects of inspections observed in the published studies outlined above. The key goal of this part of the review of existing evidence on inspections is to examine the details of workplace safety inspections that were not available in the original scientific articles identified above, as possible explanations for the differences in the impact of inspections on workplace injuries across jurisdictions. The first sections of this chapter detailed the results and methods of previous studies in a more comprehensive way than presented in published systematic reviews. 3.5 Materials and Methods Summary statistics were performed on the number of inspections, citations, penalties, amount of penalties. Basic descriptive statistics on the penalty appeals process were also calculated. The studies were chosen for three main reasons: because they are recent studies using observational data, because the United States OSH inspection data is publicly available, and because the data and reports are available in English. Because the inspections were all in one country, the regulations and targeting methods can be viewed as relatively constant which leads to more comparable results than comparing studies between different countries, though there are differences between states that have various state OSH plans. An effort was made to draw links between the contexts of each study to the results, to determine if common threads 68 may help to draw conclusions about the characteristics of each OSH regulatory system that can help make safety enforcement interventions more effective in other contexts. California and Washington have State OSHA plans whereas Pennsylvania does not, but all three have their inspections process tracked by OSHA and provided online (United States Department of Labor n.d.). The following variables were extracted from publicly available websites:  Number of inspections per year  Number of penalties per inspection  Amount of penalty  Number of serious violations per inspection  Number of violations contested  Dates of start and resolution of appeal to citation and/or penalty  Penalty amount before and after appeal The relevant time periods for data extraction were from 1998 to 2005 for Pennsylvania, from 1996 to 2006 for California, and from 1999 to 2008 for Washington State. These time periods were selected to align with the time periods of the published studies evaluating the effect of inspections in the three states respectively. Summary statistics were completed on the OSHA data for the time periods of interest for each state, restricting analysis to private (rather than government) firms only to mirror the study samples in the published studies. Statistics were further stratified by manufacturing only for Pennsylvania, and by programmed inspections only for California, to mirror the published studies for these two states. Inspections that were administrative records only, accident investigations, variance applications, and monitoring were excluded from the current analyses. Census data was also used in determining the number of firms and workers in each state for summary statistics 33 where appropriate. 33 From the data retrieval tools at https://www.bls.gov/cps/tables.htm 69 3.6 Results Inspections data The trends in the number of inspections per year per state is shown below in Figure 4. Washington has a significantly higher number of inspections than either Pennsylvania or California, though it has a smaller worker population. This difference is amplified when the ratio of inspections per firm are plotted (shown in Figure 5). The lower number of inspections per establishment in Pennsylvania and California shows a lower probability of inspection. Figure 4 Number of inspections per year in each state 70 Figure 5 Number of inspections per year in each state, for each 100 establishments Citations and penalties Table 3 shows the summary statistics on the use of citations as part of the inspection process. The use of citations is consistent from state to state, ranging from 64% to 75% of inspections having a citation. When looking in more detail at the summary statistics, clear differences emerge between the states. There are significantly more citations in the Pennsylvania manufacturing firms than in other states and in other industries in Pennsylvania. The average number of citations issued in an inspection is 2.5 for California and Washington State, but higher at 3.3 in Pennsylvania. This increases to 4.8 citations per inspection in Pennsylvania when looking at inspections with at least one citation. When restricting to manufacturing only it is 6.6 citations. 71 Table 3 Summary statistics of citations by state Figure 6 Comparison of inspection type, by state Figure 6 shows that the fraction of inspections with a penalty has a greater range across states than those with citations. It ranges from a low of 47% in Washington to 58% in Pennsylvania and 58% in California. Manufacturing firms in Pennsylvania are even higher at 65% of inspections with a penalty. In addition, inspections in Washington State result in fewer penalties per inspection and average penalty amounts that are less than half of those issued in Pennsylvania. This means that Washington State is more persuasive than the other states, though still punitive with an Number of InspectionsNumber of CitationsNumber of Inspections with a CitationFraction of Inspections with Citations Average Number of Citations per InspectionAverage Number of Citations if CitationsCA 64,018 168,257 42,191 66% 2.6 4.0CA Random only 26,257 63,768 16,845 64% 2.4 3.8PA 21,498 71,225 14,945 70% 3.3 4.8PA Manufacturing 3,640 18,003 2,715 75% 4.9 6.6WA 62,111 155,400 44,530 72% 2.5 3.5 - 10,000 20,000 30,000 40,000 50,000 60,000 70,000CA CA Random only PA PA Manufacturing Only WANumber of InspectionsNumber of Inspections with One or More Citations (Fraction of Total Inspections Provided Above Bar)Number of Inspections with One or More Penalties (Fraction of Total Inspections Provided Above Bar)72%63% 69%74%71%58%56%58%65%47%72 average of around one penalty per inspection, as seen in Table 4. When awarded, the penalties are much lower as well in Washington, with a median of $450 per inspection when a penalty was applied, much lower than the medians of California at $700 and Pennsylvania at just over $1000. Table 4 Summary of penalties in California, Pennsylvania, and Washington State Nearly 70% of citations in Pennsylvania are for serious violations, contrasted with 43% in Washington (see Table 5). California has an even lower fraction of serious citations. Table 5 Information on serious citations in California, Pennsylvania, and Washington State Appeals and adjustments after the fact Table 6 shows the average amount of time it takes to resolve an appeal to a citation, from the date of the issuance to the final order date. It takes nearly double the amount of time for contested citations to be finalized in California than in the other states. Total Number of InspectionsNumber of Inspections with PenaltyFraction of Inspections with a PenaltyAverage Number of Penalties per InspectionMedian Number of Penalties per InspectionAmount of Penalties Levied in Inspections Where One Was Levied MedianCA 64,018 38,463 60% 2.1 1 $1,865 $700CA Random only 26,257 15,084 57% 1.9 1 $1,953 $750PA 21,498 12,526 58% 1.5 1 $2,536 $1,040PA Manu 3,640 2,376 65% 2.3 1 $3,147 $1,375WA 62,111 29,226 47% 1.0 0 $1,231 $450Fractions of citations that are seriousFraction of Inspections where at lease one citation is seriousCA 20% 24%CA Random only 25% 26%PA 68% 54%PA Manu 70% 62%WA 42% 42%73 Table 6 Contested citations: average time to resolve contested citations in months In California, 34% of citations are contested, and the citations are often not resolved for over a year. As a result, the injury prevention effects of an inspection could be subject to a significant delay. In Washington, fewer citations are contested, and abatement must be completed by the deadline in the case of an appeal, though a stay may be requested (Workplace Safety and Health Council 2010). Table 7 summarizes the fraction of penalties adjusted after an appeal and the changes in penalty amounts after an adjustment. In California, penalty reductions are common, but in Pennsylvania they are the norm. The situation is completely different in Washington State, with a clear minority of only 17%. Penalty adjustments leading to increases are very rare, though the increase can be quite large. This is especially true in Washington State, and this may be related to the fact that when an appeal ends in a penalty increase, it is quite a large increase. Table 7 Penalties changes after adjustment in United States Dollars Fraction of Citations ContestedFraction of Inspections Where at Least One Citation is ContestedAverage Number of Months to ResolveCA 33% 19% 13.8CA Random only 36% 20% 13.9PA 11% 5% 6.7PA Manufacturing 11% 4% 6.4WA 28% 15% 5.5Fraction of Penalties reducedAverage Amount of DecreaseFraction of Penalites IncreasedAverage Amount of IncreaseCA 47% -$980 0.2% $762CA Random only 50% -$1,027 0.2% $620PA 87% -$718 0.7% $696PA Manu 92% -$671 0.9% $788WA 17% -$819 0.1% $2,11774 Industries Using data from the supplementary materials (Levine, Toffel, and Johnson 2012a), the industry make-up of the matched pairs was as follows in Table 8. Table 8 Industry make up of firms in California studied in Levine and colleagues (2012) Foley and colleagues note that within the firms studied, 9% if made up of manufacturing firms. However, when looking only at firms that have been inspected in that time period, 32% of fixed site firms that were inspected were in the manufacturing industry, as shown in Table 9. Table 9 Industry make up of firms in Washington State studied in Foley and colleagues (2012) As stated above, the studies of firms in Pennsylvania are limited to those in the manufacturing industries. 3.7 Workplace Safety Regulatory Systems in Canada Regulation of Occupational Health and Safety in Canada is based on a system that assumes a shared responsibility between workers and employers for health and safety, known as Internal Number of Matched Pairs Percentage of TotalAgriculture, Forestry, And Fishing 6 1%Construction 276 67%Manufacturing 36 9%Transportation, Communications, Electric, Gas, And Sanitary Services 5 1%Wholesale Trade 41 10%Services 18 4%Various other industries with only 1 or 2 pairs 27 7%Total 409 100%IndustryPercentage of Fixed Location Firms Percentage of Non-fixed Location Firms Primary Resources 13%Manufacturing 32%Construction 90%Transportation and Warehousing 10%Trade 25%Public Service 6%Service Sector 24%100% 100%75 Responsibility System (IRS). Employers are required to keep a “safe as reasonably practicable” (p. 22) workplace but are generally able to determine how they choose to address workplace hazards. If they use due diligence in dealing with workplace safety, this can be a defense against penalties. To balance the power of employers under IRS, workers have the right to know about hazards in their workplace, the right to participate tin workplace OHS activities, and the right to refuse unsafe work. The regulator’s role in this IRS system is to use inspections and other forms of enforcement to ensure that employers follow the OHS rules (Foster and Barnetson 2016), though this role can be impacted by political climate (Barnetson and Matsunaga-Turnbull 2018). Another role of the state in OHS systems in Canada is that of the workplace compensation insurance administrator. Workers who receive injuries on the job during the course of employment are entitled to receive wage replacement, medical, and rehabilitation benefits, but for historical reasons, these workers are not entitled to sue the employer for workplace injury. (Foster and Barnetson 2016) Under the Canadian Constitution, the provinces have authority over both labour and many health issues (Braen 2002) making occupational safety largely a provincial matter 34. There is a wide variation in OSH regulatory systems across Canada. For example, the way the workers’ safety and compensation systems are administered varies from province to province. In Alberta and Ontario, for example, the workers’ compensation and worker safety regulation and enforcement are separated into two separate divisions of government, whereas they are combined in British Columbia into one body. WorkSafeBC prevention activities background In British Columbia, the province has granted authority to WorkSafeBC, also known as the Workers’ Compensation Board of British Columbia, to administer the Workers’ Compensation 34 Except for a small number of federally regulated industries, such as aviation. 76 Act. WorkSafeBC’s stated priority is to prevent workplace injury and the organization works to prevent injuries by:  Providing health and safety information and access to prevention resources  Establishing standards and guidelines for occupational health and safety, and  Conducting educational presentations and work site inspections35 Though WorkSafeBC commonly uses language that emphasizes cooperation between workers and employers and cultural change, prevention officers use deterrence tools such as orders and penalties36. Most of the time that is dedicated to prevention activities is spent on traditional enforcement activities such as inspections. British Columbia, unlike many other jurisdictions in North America, meets the ILO’s guideline for developed countries of a minimum of 1 inspector per 10,000 workers (Committee on Employment and Social Policy 2006; Brown 2007). Table 10 highlights the recent division of prevention division hours by specific activity. 35 See glossary for definitions of these terms 36See, for example, the WorkSafeBC website “WorkSafeBC is most effective when it is dedicated to the WorkSafe initiative, facilitating the co-operation of workers and employers in preventing workplace injuries” and “Societal and cultural change is essential for creating a culture of health and safety in the workplace and we play a principal role in effecting this change”(WorkSafeBC 2005) 77 Table 10 Person hours dedicated to prevention activities at WorkSafeBC, by year (2007-2011) Summarized from (WorkSafeBC 2012; WorkSafeBC Policy and Regulation Division 2015; WorkSafeBC 2010a) During an inspection, inspectors may find violations of the regulation or conditions in need of improvement. In this case, the inspectors may issue orders37, written directives for a person or firm to take measure to comply with the Workers’ Compensation Act or its regulations, or levy financial penalties against employers for safety infractions (WorkSafeBC 2011). Orders can be oral or written. Oral orders can be issued for “minor low-hazard violations that are corrected before the end of the inspection and occur in a workplace where cooperation and compliance are generally present” at the discretion of the prevention officer. However, the officer is expected to check for compliance before completing the site visit; if compliance is not found, a written order will be issued (Item D12-187-1, WorkSafeBC Policy and Regulation Division 2014). More serious infractions, such as violations that may result in a high risk of serious injury, repeated violations, or failure to comply with orders, may warrant the imposition of financial penalties to “motivate the employer receiving the penalty and other employers to comply with the Act and regulations” (Item D12-196-1 WorkSafeBC Policy and Regulation Division 2014), 37 “… current policy allows WorkSafeBC only minimal discretion over whether to issue orders. It requires WorkSafeBC to issue orders to whomever is responsible whenever violations are found.” (WorkSafeBC Policy and Regulation Division 2012) 78 that is, to promote both specific and general deterrence. Prior to a penalty, a warning letter may be sent to the employer, warning that in the case of continued non-compliance administrative penalties may result. There is no requirement that an administrative penalty be preceded by a warning letter. A stop work order that shuts down part or all a work site, is meant for cases of an immediate danger that might result in serious injury, illness, or fatalities to workers. An injunction is an additional, but rarely used, tool. It is meant for extreme cases of refusal to follow a stop work order and may be used in conjunction with penalties or even prosecution (WorkSafeBC Policy and Regulation Division 2014). Regardless of how punitive the tools available to inspectors at WorkSafeBC, the reality is that inspections are generally more persuasive than deterrent. Orders, a written document requesting that an employer resolve a hazard or implement a safety program, are common, with about 60,000 orders per 90,000 inspections during 2005 to 2012 (see Table 21). However, actual punitive activities are less common. WorkSafeBC levies penalties infrequently (see Table 21), with just over one penalty for every 100 inspections, and the amount of the penalties tends to be relatively large. These penalties had a median value of $500038. This range of actions following an inspection, from an order to a warning letter to a penalty, demonstrate that WorkSafeBC prevention activities are part of a penalty pyramid, much as the firms in the OSHA studies are. This shows that WorkSafeBC uses a persuasive rather than a deterrent version of responsive regulation, as described by Ayres and Braithwaite (Ayres and Braithwaite 1992). Previous research has found that only inspections with penalties seem to have an impact on reducing injuries. Penalties are rare enough that there is not enough data to stratify and examine the effect of inspections with penalties. Since WorkSafeBC inspections rarely have penalties, it is likely that inspections will not be effective in reducing injuries, as shown in Table 11, a table derived from the annual statistics reports from WorkSafeBC ((2015b), for example). 38 This is the median value of penalties; the average is much higher. 79 Table 11 Number of WorkSafeBC inspection and enforcement activities, by year and type of activity, for the years of inspections studied (2005-2012)39 There is no specific data on reviews of enforcement decisions. However, it is known that the Review Officer must decide within 150 days. Though they can ask for an extension to this time limit; this will only be approved in cases of complex cases (Columbia n.d.). It is also unlikely that many orders will be contested as they are not linked to penalties. Prevention activities across Canada A short summary of prevention systems in Alberta and Ontario are given here as a short comparison to the system in BC40. These two provinces have proactive inspections are conducted to monitor compliance with regulation. Orders, fines such as tickets and/or penalties, and stop work orders are used during inspections (Ontario Ministry of Labour Training and Skills Development 2012; Alberta OHS 2019), as they are at WorkSafeBC. But these enforcement systems are different form WorkSafeBC as outlined below. 39 In the study in Chapter 5, inspections from years 2005-2012 are studied (the entire time period of study, including baseline and follow-up is 2004-2014) 40 There is a great deal of information from Alberta due to publicly available information and the work of Bob Barnetson (e.g. (Barnetson 2010)) Athabasca University, and it is quite distinct from BC, so it was chosen as a comparison province. Ontario is included because there is recent research from that province (Hogg-Johnson et al. 2012), however, there is little public information available on the Ontario system. 2005 2006 2007 2008 2009 2010 2011 2012Total 2005-2012Average per year 2005-2012 Inspections 20,066 26,249 31,649 35,414 38,520 43,570 40,260 38,770 274,498 34,312 Orders 33,414 46,843 55,438 65,231 69,934 37,207 31,942 32,079 372,088 46,511 Stop Work Orders 17 30 58 95 77 91 80 108 556 70 Penalties 87 75 221 150 211 256 352 260 1,612 202 Education 800 835 875 939 1,054 1,018 1,047 911 7,479 935 Consultation 11,320 9,724 9,893 10,166 10,896 13,043 11,185 9,833 86,060 10,758 Warning Letters 200 234 338 243 299 431 460 447 2,652 332 80 In Alberta, the enforcement system has fewer resources than in BC. In 1988, the safety inspection activity was greatly reduced after an experience rating system and other incentive programs were introduced (Auld et al. 2001). Around 2017, was Alberta was spending about $45 million each year on enforcement and injury prevention, including employing about 130 OHS inspectors who visit workplaces, respond to complaints, and investigate injuries and fatalities41 (Barnetson and Matsunaga-Turnbull 2018). With about 2 million workers in Alberta during this time period (Statistics Canada 2019), this is about 0.65 inspectors per 10,000 workers. In contrast, from Chapter 1: British Columbia has about 2.5 million workers and WorkSafeBC spent about $75 million on prevention in 2017. In 2010, the only year this statistic was available, it was calculated that it would take approximately 14 years to inspect each Alberta workplace once (Barnetson 2010). Using data from Table 11 of 38,770 inspections per year in 2012 (the most recent data in this document) and BC Stats statistics of 175,950 employers in BC 2012 (BC Stats 2019), the comparable statistic would be 4.5 years to inspect every employer in BC. Of course, this is not a true measure as there are often repeat inspections and many employers in “safer” industries will not receive an inspection during this time period. Barnetson (2010) also mentions significant lags in time between a safety complaint and an inspection in Alberta, and a long time passing between orders being issued and compliance being achieved. Along with having fewer resources than workplace safety regulators in British Columbia, the Alberta system appears more use fewer punitive measures than in than the British Columbia workplace safety enforcement system. In the 2016-17 fiscal year, there 8,648 inspections leading to 7,848 orders being written (orders in Alberta are very similar to BC). That same year, there were 54 tickets issued to employers, with a maximum value of $575, and 75 41 The budget nearly doubled between 2010 and 2017 to upwards of $47 million. 81 tickets being issued to workers42. Employers were also issued 9 administrative penalties with values ranging from $500 to $42,50043 (Alberta Labour 2017). Ontario’s enforcement system, administered by the Ontario Ministry of Labour, was researched by Hogg-Johnson and colleagues (Hogg-Johnson et al. 2012) (see section 1.2.2), and it was found that inspections in that province did not provide an injury prevention effect. There had been an initiative during the period of that study to increase resources to the labour safety inspection program. The ratio of inspectors increased from 0.38 to 0.54 inspectors per 10,000 workers (Hogg-Johnson et al. 2012). The above brief summary of statistics from two other provinces shows that the regulatory systems vary widely by jurisdiction within Canada. 3.8 Discussion A few conclusions can be made from the closer look at previous studies. In the study of Pennsylvania manufacturing firms, only inspections with a penalty were associated with a decrease in injuries in the following year. This was not found in the second to fourth years following. The study of Washington State DOSH inspections found that enforcement and consultation inspections were linked to small decreases in non-MSD lost-workday claims; the effect was greater if a citation was involved. Programmed inspections in California were linked to a decreased injury rates in the year after inspection and decreases in the third and fourth year after, as well. This study did not have stratified results for inspections with penalty and inspections without, though it is likely that the results would be the same as the other two states in that penalty inspections would be found to be more effective. This range of actions following an inspection, from an order to a warning letter to a penalty, demonstrate that OSHA prevention activities comprise a penalty pyramid 42 Since January 1, 2014, 327 tickets have been issued. 43 Since October 1, 2013, 25 administrative penalties have been issued. 82 Inspections with penalties appear to be more effective than inspection without penalties for two main reasons. The first is specific deterrence and the fact that the penalty makes non-compliance less attractive. A second hypothesis is, as Scholz and Gray (1990) suggest, that penalties may focus attention on risks that need improvement. In Washington State, inspections with a citation had a greater impact than inspections without, so this lends credence to the Scholz and Gray theory, though many of the cited firms likely also had a penalty. In sum, it appears that inspections with penalties or citations are effective while inspections without penalties are generally not. Consultations may be useful in injury reduction in some cases based on the results from Washington State. There are a few inferences that can be drawn from the detailed look at workplace inspections in the three United States of Washington, California and Pennsylvania. The regulatory system is similar between these three states as they are all located in the same federal system. Targeting was risk-based in all jurisdictions. In addition, penalties were common in each scenario, though the percentage of inspections with penalty varied by state, and the median amount of the penalty ranged from $450 to $1375. However, the specific characteristics within each regulatory system differs in several important ways. There is a lower number of inspections per establishment in Pennsylvania and California versus Washington State shows a lower probability of inspection; accordingly, there would be a smaller general deterrence effect in these states compared to Washington. However, whether general deterrence would have an impact is not known as it has not been studied. The third difference is that penalties are higher and more likely to be appealed in Pennsylvania and California than in Washington. These appeals take much longer in California than in any other state, which may delay the effectiveness of inspections due to firms not having to comply until the appeal is adjudicated. 83 The conclusion drawn from the US OHSA studies can be applied to the British Columbia context. WorkSafeBC prevention activities are part of a penalty pyramid with a range of actions following an inspection, from an order, to a warning letter, to a penalty. Inspections with orders are common, while inspections with penalties are very rare and penalty amounts are higher, with a median amount of $5000. This shows that WorkSafeBC uses a persuasive rather than deterrent version of responsive regulation as described by Ayres and Braithwaite (Ayres and Braithwaite 1992). While penalties are larger, they are rare enough that they may not transmit to employers the possibility of serious repercussions for non-compliance. Additionally, there are few consultations in BC, an intervention that appears to be effective in Washington State, so the most persuasive part of the penalty pyramid does not play a large role. Finally, BC has fewer appeals and as such the length of time for appeals may play a smaller role in mitigating or delaying compliance. The fact that general deterrence varies from jurisdiction to jurisdiction, as the probability of inspection varies, should be considered. If decision makers at firms that are aware that similar workplaces have been inspected and may have experienced penalties, they will adjust firm function (make the workplace safer) in reaction to a higher probability of inspection. When an inspection occurs at that firm, it will appear safer than those firms that are not expecting a higher probability of inspection. The marginal difference that an inspection makes (the specific deterrence effects) will then be reduced. The above information can be used to inform a main dissertation hypothesis on the effect of inspections on firm injury rates in BC: Inspections in BC are unlikely to lead to a decrease in injury rates. It is possible that inspections with orders may lead decreased injury rates by drawing a firm’s attention to issues that require improvement. If there is an effect, it will occur in the year following the inspection and likely not later, due to the short length of any appeals. Finally, it is important to suggest that more detail should be made available in published intervention studies. This will help to provide more complete and relevant results to policy 84 makers and researchers when attempting to implement interventions or replicate studies in other jurisdictions. 85 Choosing an Analysis Strategy for the Inference of Causal Effects 4.1 Introduction This chapter is a critical examination of the analytical methods used in previous studies of workplace safety inspections, along with alternative analytical methods, to determine the most appropriate method to use to evaluate the effect of WorkSafeBC inspections on injuries. Each jurisdiction has unique characteristics related to the data collection, sample selection, and time period of study must be accounted for when considering an analysis method. The strengths and drawbacks of using each analysis method, in the context of the characteristics of the WorkSafeBC data are also examined, to determine which of the methods are appropriate for use here in this PhD program of research. 4.2 Background Several studies of workplace safety inspections have been conducted over the past few decades. The previous studies of injuries and workplace safety inspections have each used a different analytical method. The results of an intervention study will be most useful to government agencies and other policy makers if the study is designed to examine a causal relationship between the intervention and the outcome of interest, to ensure that the relationship is not merely correlative. Thus, a method that allows the strongest causal inferences, without violating the assumptions of that method, would be ideal. An analysis method also needs to consider how firms were selected for inspections, the characteristics of the firms studied, and how samples of firms were selected for study. This chapter beings with a review of issues regarding validity arising from observational studies and the statistical methods used in previous studies. In addition, there is a description of the data available for the PhD program of research, and an overview of some of the methods available to analyse these data, with the intent of using all this information to choose the best methods applicable to the WorkSafeBC data. 86 4.3 The Challenge of Observational Studies It is commonly accepted that experimental studies and randomized controlled trials provide the clearest and most unbiased evidence of causal impact. These study designs minimize threats to internal validity, and reduce the probability that the observed differences between intervention and control subject outcomes is due to something other than the intervention (Gottfredson et al. 2015). Unfortunately, these studies are costly, may be politically inadvisable, not permitted by policy or regulation, or logistically impossible; and can also be impractical, particularly if the outcome is relatively rare. In these situations, an alternative is to study a situation where a treatment is applied to a group, with an available control group comprising those not receiving the treatment. This control group can be individuals that are eligible for treatment, but do not receive it, or are somehow ineligible for treatment, but can be compared or made comparable using various statistical methods. These are known as observational cohort studies. Observational cohort studies are like randomized studies in that there is a treatment group that is exposed to a state, event, or outcome, and a control group that is not exposed. However, bias may result due to the way treatment is assigned to individuals (Rosenbaum 2015). Care must be taken to ensure that observational studies are designed to mimic a randomized study as closely as possible. The intervention should be specific and well-defined, and temporal information must be available to ensure that post-treatment measurements are truly post-treatment. There is also a need to ensure that plausible alternatives to treatment effect are identified and investigated (Rosenbaum 2010a). In their synthesis of the longitudinal research in criminology, Loeber and Farrington (2008) note several threats to the inference of causality based on work by Shadish, Cook, and Campbell (2002). These “threats” may indicate a causal effect in the results of an analysis, when in fact there is none. The threats applicable to this study are shown in Table 12. 87 Table 12 Summary of threats to causal inference in observational studies from Loeber and Farrington (2008) history the observed effect is caused by other explanatory variables changing in the same time period; maturation the observed effect reflects a pre-existing trend; testing the observed effect is caused by previous testing of the participants; regression the observed effect is caused by statistical regression of extreme scorers to the mean; selection the observed effect is caused by pre-existing differences between the groups being compared; mortality the observed effect is caused by differential attrition from experimental and control groups; instability the observed effect reflects random variation; and causal order the true causal order is opposite to that hypothesized. Summarized by Rosenbaum (2009), a “better” observational study would be similar to a randomized experiment in these crucial ways:  The study would be designed beforehand.  The treatment would be well-defined.  The treatment would commence at a well-defined time, with outcomes and covariates measured before and after treatment. Craig and colleagues (2012) suggest multiple measures before and after treatment to control for secular trends.  The treatment would be assigned “haphazardly44”, not relative to outcomes.  The covariates in the treated and control groups would be demonstrated to be similar.  Possible alternative explanations for treatment effects would be recognized, and the study design would address these explanations In addition, Craig and colleagues (2012) mention that methods must address sources of bias in the analysis or design stage. For example, bias could be addressed by having multiple exposed and unexposed groups that are stratified according to a variable that may affect both exposure and outcome to determine if the variable could be a source of bias. 44 Not randomized, but at least not obviously related to the outcomes subjects would exhibit under treatment or under control 88 In the case of this dissertation research, it would be ideal to incorporate all these criteria. However, not all the principles for a model study from Craig and colleagues (2012) and Rosenbaum (2009) are attainable. Certain characteristics of an ideal observational study would be impossible, such as designing the study beforehand, given that it is retrospective. It is also WorkSafeBC policy to target firms for inspection through programs such as the High Risk Strategy and the Serious Injury Initiative (WorkSafeBC 2019a; 2019b), and not to choose them haphazardly or randomly. Fortunately, other criteria can be incorporated into this study. There is data from before and after treatment available for a longitudinal study and stratified analysis may be carried out to identify sources of bias. Methods to demonstrate that the covariates were similar can be applied, and alternative explanations can be investigated. 4.4 Approaches to analytical methods in previous studies Several different approaches to evaluating workplace safety interventions using observational data are discussed below based on four published studies of inspections or inspections with penalties, and one of a safety management system intervention program. Inspections at Pennsylvania manufacturing firms: Scholz-Gray change model In 2002, Gray and Scholz published a study of OSHA inspections from 1979 to 1998, which was an update of a study from 1993 (W. B. Gray and Scholz 1993). The authors of the 1993 study described several methods of addressing sources of bias including omitted variables and regression to the mean. Gray and Scholz (W. B. Gray and Scholz 1993) chose a specific panel data technique from Chamberlain (1984). Unfortunately, since this technique requires observations for every time period for each firm in the study, the authors were unable to use this method in follow-up studies because the subset of firms with balanced data was small and not representative (W. Gray and Mendeloff 2002). Gray and Scholz developed a new analysis strategy that could handle unbalanced data. In 2002, Gray and Mendeloff (W. Gray and Mendeloff 2002) tested various methods using the data from the 1993 study (W. B. Gray and Scholz 1993) and found that, unless the dependent 89 variable was analyzed in “change in injuries” (difference) form, endogeneity45 was present. Endogeneity was an issue because there was a relationship between injuries and inspections whereby OSHA targeted inspections of firms with higher injury rates. This is a common tactic with many regulators, and ignoring the endogeneity is inadvisable because the results may seem to indicate that inspections cause injuries. The analysis method developed by Gray and Scholz has also been used in follow up studies by others including Haviland et al.(Haviland, Burns, et al. 2012), and Mendeloff and Gray (W. Gray and Mendeloff 2002). The most recent study, by Haviland et al. (2012), was conducted on Pennsylvania manufacturing firms with more than 10 employees from 1998 to 2005 (Haviland, Burns, et al. 2012). The researchers used the following model with the change of injuries as the outcome, to be able to compare their results to earlier findings: Change in (Log Number of (lost time) Injuries) = α1 + β2 Inspection with Penalty it + β3 Change in (the Change of Log Employment) it + β4 SIC (two-digit industrial category) it + β5 Year + ε it where t refers to the year and i refers to the firm. This model was used to create an estimate of the outcome twice for each firm by year of observation: first as if the firm was inspected, with the relevant inspection variable set to one, and second as if the firm was not inspected, with the variable set to zero. The second step involved back transforming these predicted outcomes to estimated injury count in the current year using actual counts in the prior year, thereby creating the missing counterfactual for the firms that were not inspected. Then, the mean predicted injury counts under each inspection condition is calculated. This is divided by the mean injury count under no inspection with a penalty, estimating a percent change in injury counts due to an inspection with penalty. Washington State inspections: generalized estimating equations Two papers have been written on the effect of inspections on injury rates in Washington workplaces, one in 2003 (Baggs, Silverstein, and Foley 2003) and one in 2012 (Foley et al. 2012). 45 Endogeneity results from omitted variables correlated with the error term in a model (Schroeder 2004), leading to a potentially biased estimate. 90 In the 2012 study, the researchers looked at 10 years of data from single location (but not necessarily single jobsite) firms with 10 or more full time employee equivalents. The outcome variable was the change in claims injury rates, stratifying into time-loss and medical only, as well and musculoskeletal versus non-musculoskeletal injuries. The independent variable was prevention activities classified as either enforcement without citation, enforcement with citation, or consultation. Firm size and claims injury rates (prior to the prevention activities) were controlled for. The researchers attempted to control for North American Industry Classification System (NAICS) industry, but industry sample sizes were too small in the final analyses and firms were combined into non-fixed site (construction and transportation) versus fixed site (all others). The years of follow-up were combined into four-year time periods consisting of a 2-year pre-study period (firms had to have 10 or more employees and no prevention activities during this time to be included in the study), a 1-year baseline period, and a 1-year or follow up period. As such, the observations of claim rates were not independent. To account for this, a multilevel Poisson model (generalized estimating equations approach with an autoregressive correlation matrix) was used46. California randomized inspections: fixed effects with exact matching Levine, Toffel, and Johnson (2012a) examined 10 years of data to research the effect of random inspections of California firms in high injury rate industries. The cohort consisted of single location firms of 10 or more full time equivalents that had not received a random inspection in the two preceding years. Exact matching with fixed effects was used for the analysis. Inspected firms were matched with potential controls that included all single location firms that were not inspected in that time period; firms were matched by region and industry code. When this resulted in more than 46 Note that the randomized study of health and safety interventions at Ontario manufacturing firms used very similar analytical methods (Hogg-Johnson et al. 2012) and thus is not discussed separately here. 91 one control for each treatment firm, the number of employees was used as a criterion to choose among the potential matches. If there was still more than one control for each treatment, ties were broken by random selection. If no match was found at that point, the treated firm was dropped from analysis. A common support restriction was also imposed to exclude any matched pairs, though the method of determining the region of common support was not identified. The analysis was conducted using conditional fixed-effects negative binomial regression (Levine, Toffel, and Johnson 2012a). Inspections at Italian manufacturing plants: interrupted time series and survival analysis In 2016, two studies were published of inspections and injuries in Italian manufacturing plants. One of the studies (Farina et al. 2016) used survival analysis and these methods are not appropriate for the current PhD research. Time to event is not directly comparable to the study at hand as this does not answer the research question of interest. In the other study Agnesi and others (2016) compared pre-intervention and post-intervention injury rates during the years 2001 to 2007. The cohort of nearly 5000 firms was made up of manufacturing firms, 795 firms with inspection and 4205 firms without an inspection. Two analyses were completed. First, an interrupted time series design that examined rates of severe injuries and trends in rates for time periods before and after an intervention. Second, segmented Poisson regression was used to examine if inspections reduced injuries and the trend in injury rates after inspections. Certificate of recognition intervention study, British Columbia: matched difference-in-differences In an examination of the effects of a WorkSafeBC safety management system certification program (certificate of recognition or COR), McLeod and colleagues (McLeod, Quirke, and Koehoorn 2015; C. Mcleod, Quirke, and Aderounmu 2017) studied 5000 COR certified firms and 200,000 non-COR certified firms. The intervention group was defined as all firms who became 92 COR certified between 2003 and 2011. The non-certified firms were included if they had three years of active workers’ compensation registration in a sector covered by a COR program, but were never COR certified themselves. Since COR certification is voluntary, it follows that the type of firm to choose to become COR certified may differ from non-participating COR firms. This self-selection raises issues in the interpretation of any intervention effects as causal. To deal with this issue, the researchers used a difference-in-difference analysis, implemented with population-averaged (GEE) Poisson regression, applied to the following model: Yit = α + βTi1*t + ρTi1 + γt + εit Where Y was the workplace injury of interest, T is the treatment variable to indicate if the firm is in the COR group or control group, and t is whether the time period is before or after the intervention is applied. The coefficient β gives the average difference-in-differences effect of the intervention, or the effect of being in the treatment group (T) in the time period after the intervention occurs. An update to the report was published in 2019. In this new analysis, coarsened exact matching was added to the methods (McLeod et al. 2019). 4.5 Model Selection As mentioned above, there are three key issues that must be addressed when analyzing inspections and claims data: the data is count and has a large proportion of zeros, the data is longitudinal and thus the observations on the same firm may be correlated, and the treatment (i.e. inspections) is applied in a targeted fashion that may cause selection bias. Each of the three issues are examined below, with a list of some analyses that may work to address these issues. Dealing with count nature of data Injuries, when not expressed as a rate, are a type of count data. Count data has special characteristics that must be considered when analyzed – it is always positive, is made up of discrete whole integer numbers, and can be over-dispersed. Work-related injuries that result in 93 a day of wage loss are generally rare in the working population and there are many zero counts. These characteristics mean that count data cannot be analyzed with linear regression models and cannot be transformed to make it fit the requirements of linear regression models. Fortunately, the process of choosing a count data model is relatively straightforward. The Poisson and Negative Binomial distributions are the most commonly used models for count data (Trindade, Ospina, and Amorim 2015). Poisson models require that the data have a variance roughly equal to the mean. If the data does not fit this requirement, usually due to an excess of zeros, it is considered over-dispersed and the estimated standard errors and p-values would be too low. An effective alternative is negative binomial regression that generalizes the Poisson regression model by introducing a dispersion parameter. The likelihood ratio test is a useful parameter to decide between the Poisson and negative binomial models (Allison 2012). Zero-inflated models can be used in certain cases when there is a group of subjects in the dataset that have zeroes due to a different process or reason than the rest of the group. For example, in a theoretical study of number of university students and their reasons for purchasing a parking pass, students will have very different reasons for not purchasing a parking pass. Some students do not a pass because, even though they own cars, they take public transit or walk for environmental or financial reasons. However, many students do not have cars. These people will have a structurally different reason for zeroes than those people that could purchase a parking pass but choose not to. If there is reason to suspect the zero inflated model may work, the Vuong test (Vuong 1989) can provide information on the suitability of these models. Hurdle models are similar to zero-inflated models, but operate with the assumption that all zero data, rather than just the excess zeros, are the result of a structural source. An example of hurdles models can be found in a study by Hu and colleagues of a sample of drug users which also examines cigarette smoking. The only participants that will have smoked zero cigarettes are the non-smokers; smokers will be unable to record zero cigarettes in the past month. In that case non-smokers are the only reason for zeros and this is a structural reason (Hu, Pavlicova, and Nunes 2012). 94 Table 13 below summarizes the choices when analysing count data, and its applicability to the dataset of inspections and claims for the current PhD dissertation. Table 13 Summary of count data choices Model Description Poisson Poisson requires variance to equal the mean. Negative Binomial For over-dispersed count data with high numbers of zeros, use negative binomial rather than Poisson. Zero-inflated and Hurdle Count Models Requires a different process for generating the excess zeros (zero-inflated) or for generating all the zeros (hurdle). Dealing with longitudinal nature of data Longitudinal data, that is, data where a sampling unit has repeated measurements over time, must be analyzed differently than cross-sectional data (one measurement at one point in time). Longitudinal data is an informative tool for researchers with many benefits. However, by definition, repeated measurements are clustered by the unit, and these measurements will be correlated (there would be an expected degree of similarity between measurements on the same unit). This cluster or correlation characteristic violates an assumption of analytic models that may lead to biased standard errors and potentially biased estimates (Dieleman and Templin 2014). Both the correlation characteristic and the temporal nature of the data must be accounted for in the analysis (Fitzmaurice, Laird, and Ware 2004). Common methods to account for the issues with longitudinal data include random effects, fixed effects, generalized estimating equations, and clustered standard errors. These are described in more detail in the Table 14 below. 95 Table 14 Description of the applicability of longitudinal data models Possible Model Description Conditional Model: Random Effects (RE) and Fixed Effects (FE) Longitudinal data that may have unmeasured covariates can be analysed using random effects models or fixed effects models. Both allow a (random) cluster-specific effect to be added to model, but the FE approach allows that effect to correlate with the predictors, while the RE does not, as this will lead to inconsistent estimates. However, RE estimates can be more efficient because these models use information both within and between individuals (Allison 2011b). It is often preferable to run fixed effects models when there is regular data collection on many subjects, with low dropout and exposures change over time for at least some respondents. Random effects may be preferred with a large number of observations for a smaller number of subjects (Gunasekara et al. 2014). To decide between fixed or random effects, a Hausman47 test is useful in determining whether the errors are correlated with the predictor variables and are thus inappropriate for a random effects model (Allison 2009). Marginal Model: Generalized Estimating Equations. An extension of Generalized Linear Models, GEEs allow the correlation that accompanies longitudinal data. It is robust, with only the mean structure needing to be correctly specified, which makes it less susceptible to bias from model misspecification. However, this robustness comes with a downside: this method is less efficient than other approaches.(Ziegler and Vens 2014; Heagerty and Kurland 2001) The results of this method provide a population averaged estimate and thus cannot be used to predict the response of an individual. Standard Error Adjustment: Clustered Standard Errors Primo et al. argue that adjusting standard errors for clustering in data may often be an appropriate method to model longitudinal data. They consider it an easy-to-implement methodology that requires fewer assumptions than other longitudinal models and note that the calculation of these standard errors is not subject to the current computing 47 The Hausman test was used on this data to confirm that a fixed rather than random effects model should be used. This test looks at whether the error terms (it) are correlated with the regressors. The Hausman test was performed on the cohort with inspections only, acute injuries, and it was found that fixed effects were more appropriate than random effects. 96 Possible Model Description limitations. However, if there is reason to believe there is high within-individual correlation, this may lead to a biased estimate. (Primo, Jacobsmeier, and Milyo 2007) Interrupted Time Series Strong quasi-experimental research design that involves analyzing trends, with a series of data, before and after an intervention. Usually eight time periods before and after the intervention are needed for analysis. The trend can change in slope, or there may be a jump or drop resulting from the intervention. Usually used at population level but can be used at individual level. ITS can control for secular trends in the data and is easily understood and implemented (Penfold and Zhang 2013). Dealing with Selection Bias A key issue in observational studies is selection bias, where the intervention and comparison groups can differ in ways that are related to the outcome. The data is from groups that have not been randomized, so the outcome has the potential to be correlated with group assignment rendering it difficult to get a consistent treatment effect estimate (Winship and Morgan 1999). This selection bias can also obscure or over-estimate the relationship between the intervention and the effect (von Elm et al. 2008). To control for the selection bias introduced by the targeting of firms to investigate the effect of inspections, two main methods can be used: selection on observable information, or selection on unobservable information. A list of the main ways to deal with selection bias are listed in Table 15 below, with the application of these methods to the investigation of inspections described in detail in the sections following. Table 15 Methods for addressing selection bias Type of Correction Description Propensity Scores Propensity score matching is commonly used in improving a control group. Generate a comparison group (or control for differences) based on a score that probability of treatment. Can theoretically reduce selection bias to zero if the selection process is 97 completely known and measured well (Cook, Shadish, and Wong 2008). Can be used with matching, weighting, stratification, or as a covariate in regression. Heckman Two Stage Correction Used for bias due to a non-random sample of a larger population when one wants to make inferences on the larger population (Bushway, Johnson, and Slocum 2007). The two stages are: 1: the probability of being in the sample group is predicted. 2: the main model is estimated with a control variable representing the difference between treatment and control group that resulted from unmodeled sources of variance in the selection process. Instrumental Variable An instrument is a variable that causes the independent variable to change but does not affect the outcome in any way, other than through the independent variable. Use of instrumental variable analysis reduces the correlation between the dummy treatment variable and the error term. Use of an instrumental variable (IV) that satisfies these assumptions should provide an un-confounded estimate of the effect of the intervention. Such variables are rare, and not all of the assumptions can be tested directly, in consequence, the IVs chosen often fail to meet the requirement of independence (Craig et al. 2017; Steuerle and Jackson 2016). This is especially the case in purely observational studies (Greenland 2000). Coarsened Exact Matching CEM can be used to generate a comparison group based on similar, but not exact, characteristics as the treated group. How similar the comparison group needs to be is dictated by the researcher. Stratification Grouping subjects into categories for analysis. Synthetic Controls Trend in the outcome of interest compared in an intervention area and a synthetic control area, representing a weighted composite of real areas that mimics the pre-intervention trend. 98 Regression discontinuity Looks at the differences in outcome between those who almost qualified for a treatment and those that barely qualified. For example, could study the difference in outcomes between children whose parents have might be considered for a childcare program but have an income slightly too high to qualify, compared to children whose parents were at the upper level of income to qualify for the program. These methods have also been shown to provide unbiased causal estimates Well-conducted regression discontinuity designs are second only to random assignment studies in their ability to generate unbiased causal estimates.(Gottfredson et al. 2015) Difference-in-differences Compare the difference in the changes between the two groups over a defined time period. This method can control for time-invariant unobserved characteristics. If it can be assumed that trends in injuries between the inspected and uninspected groups would be the same, DiD method can reduce bias. Not commonly used in longitudinal studies. Pipeline Methods Pipeline comparisons use delayed implementation of treatment. The comparison group is eligible observations that have not yet received the program. Fixed Effects See description above. By allowing each individual to act as their own control, the issue of treatment group being different than the control group is no longer of concern. As it only looks at cases where there is a change, it may not be useful in situations where outcomes are rare. The most appropriate methods: matching, difference-in-differences, and fixed effects models are described in the following sections. 4.5.3.1 Using observable data - propensity score methods and coarsened exact matching Matching methods using pre-treatment variables can help to control for the bias introduced by non-random treatment selection in observational data. This is accomplished by removing observations to improve similarity of observed variables between the treated and control groups. This method can mimic random assignment, but unobserved differences may remain between the treatment and control groups. This approach assumes that there are no omitted variables that affect both the treatment and outcome variables (Ho et al. 2007b). 99 If the data can be perfectly matched, controlling for further variables is not necessary and a difference in means on the matched data can be used to estimate the causal effect. Imperfectly balanced data would require controlling for the unbalanced variables with a model to further reduce residual imbalance. Even if this model is the same as the model that would have been used without matching, matching would lead to less sensitivity to model specification and reduced bias (Ho et al. 2007a). The use of a matching process to a model can help address the tendency of researchers who, perhaps unconsciously, choose a model that suits their hypothesis (King and Nielsen 2016). In the words of Stuart and colleagues (2010), “matching methods are not designed to ‘compete’ with modeling adjustments such as linear regression”; the two methods work best in combination. Since it is often impossible to find exact matches based on measured values for each treatment group member, a common method of generating an improved control group is through propensity score matching (King and Nielsen 2016). Propensity score methods, as originally proposed by Rosenbaum and Rubin (1983), involve estimating the probability of receiving treatment, using probit or logit estimations with covariates, and under the assumption that there are no unmeasured variables that influence treatment selection. Observations with similar propensities to be in either the treatment or control group will also tend to have similar covariate distributions (Crown 2014). The treated observations are then matched to untreated observations with similar propensity scores, using methods such as nearest neighbour matching, Mahalanobis matching, or simply stratifying observations into groups with similar scores. Matching can be one treatment matched to one control, or k-to-1 matching, when each treated observation is matched to multiple control observations. In the latter case, if controls are not removed from the pool of possible matches (matching with replacement), weighting in the regression is necessary (Stuart 2010). There are several considerations when implementing propensity scores. It has been suggested the matching variables should be limited to those that are important to balance, in other words that are “prognostically important covariates” (Austin and Stuart 2015). Since valid 100 treatment effects can only be estimated, it is also important to consider the propensity score distributions in the treatment and comparison groups, generally with a visual check of the plotted propensity scores. If the groups are not similar enough for comparison (that is, they lack a “region of common support”), strategies such as trimming48 can be applied (Caliendo and Kopeinig 2008). Finally, it is necessary to compare the covariate distribution between the two groups and determine if the covariates are sufficiently balanced. A commonly used alternative to matching is to use the propensity scores in a model as inverse probability weights. This has the advantage of using all available data, since no observations are dropped. Stuart et al. noted that the two methods, weighting with propensity scores and regression models with matched treatment and control groups, work best in combination (Stuart 2010), with regression models adjusted for the covariates used for matching. The estimate derived from this combination is consistent (robust) even if one of the models is mis-specified (Tan 2010). This “doubly robust” method can even be used in the case of randomized experiments to improve efficiency (Hirano, Imbiens, and Geert 2003). However, one of either the regression models or the propensity score models must be correctly specified or the technique can cause estimation problems, as weighting can increase random error (Freedman and Berk 2008). Propensity score matching is popular and has a solid theoretical basis. However, a main practical difficulty of these methods is that the propensity score is an estimate and not a measurement, which means misspecification and residual bias are possibilities (Imai and Ratkovic 2013). In addition, propensity score matching does not necessarily reduce imbalance as an estimated average across observations (Iacus, King, and Porro 2012); this balance must be checked and the propensity re-estimated as necessary. In response, an alternative to the propensity score method, called coarsened exact matching (CEM), was developed by Iacus, King, and Porro (Iacus, King, and Porro 2009). This process uses a matching algorithm to assemble a control or comparison group from the pool of 48 Trimming involves removing extreme values, also known as outliers, from the dataset. 101 untreated individuals. In this method, variable values are sorted into bins. For example, a continuous variable can be divided into bins based on the quintile distribution of the variable, or another set of bins as identified by software based on the distribution of the variable. An exact match is then made based on one of the five values in the quintile bins or one of x values based on bins identified by software. If no suitable match can be found, even if the coarsening is changed to reduce the number of bins, the treatment group member is not used in the analysis. Benefits of CEM include being able to control which variables are important to match on more closely and which can be matched on more broadly. Without having to estimate propensity scores, then check balance, then re-estimate until a satisfactory balance is achieved, the imbalance of one variable can be adjusted without affecting the balance of other variables. Importantly, the method is more intuitive and easier to explain to the public and other stakeholders. Since the groups will be approximately, rather than perfectly, matched, a regression model controlling for observed covariates can be used with the matched sample using CEM. 4.5.3.2 Difference-in-differences Difference-in-differences (DiD) models, also known as double difference models, are an extension of simple before-after estimations. Before-after is an estimate of the difference of the outcome of those treated, before and after treatment (Lee 2016). The DiD estimator is the difference calculated between the observed mean outcomes for the treatment and control groups before and after program intervention and the difference that would have occurred had no intervention happened and the trends remained the same (see Figure 7 below) (Khandker, Koolwal, and Samad 2010). DiD models of observational data estimate the average treatment effect on the treated (ATT), rather than the average treatment effect on the entire population (Ryan, Burgess, and Dimick 2014) but policy makers are often interested in how an intervention will affect those targeted by the intervention (Guo, Barth, and Gibbons 2006). 102 Figure 7 Graphical explanation of difference-in-differences method An advantage of the difference-in-differences method is its ability to deal with unobserved confounders. DiD models can be implemented with repeated cross-sectional or panel data (Lee 2016). If the composition of the two groups changes, leading to changes in the distribution of variables between groups, these variables and potential confounders of the main relationship can be controlled for in analytic models (Lee 2016). This is done by including the confounders in a regression DiD model, as follows. Yit = β0 + β1Ti1 t + β2Ti1 + β3t + εit The coefficient of interest is β1, the interaction between T, which is the treatment variable equal to 1 for treated observations, and time, which is generally defined as zero before treatment and one after, though it can be generalized to cases with more time periods. The variables Ti1 and t are included to pick up time effects and the effects of being in the treated versus untreated group (Khandker, Koolwal, and Samad 2010). Note that if a variable is unmeasured, its effect will be still be controlled for in DiD, by nature of the estimate design, as 01234567890.5 1 1.5 2 2.5 3 3.5Outcome VariableTimeObserved Trend in Control GroupAssumed CounterfactualObserved Trend in TreatmentGroupDifference in differencesTime of Intervention = 2103 long as the effect of the variable is the same between the treated and untreated groups (Lee 2016). There are three key assumptions that must be when using DiD models to deal with the effects of selection bias. The treated and untreated groups must have adjusted parallel trends in outcome. It is also important that, when comparing the observed covariates, there are control firms that are like the treated firms. And finally, it is important that diffusion effects of treatment are not present in the control group (i.e. the control group is not affected by treatment in other firms; for example, the assumption that general deterrence is not a significant effect when examining inspections). (Chabé-Ferret and Subervie 2013) The parallel trends assumption is more likely to be valid when comparing outcomes over a short time period, rather than over a long time period. The validity of the parallel trends assumption can be examined graphically by observing past trends, though past trends may not necessarily be indicative of the future trends. It is also prudent to consider adjusting standard errors for serial correlation when using DiD (Bertrand, Duflo, and Mullainathan 2003). This method is difficult to apply in a situation where the effects of the intervention is transient, and the data is longitudinal. This is due to difficulties in applying the before and after labels to the control group members without an intervention or treatment over time. However, with matching and limited reuse of the control group members as matches, this preceding challenge can be addressed. 4.5.3.3 Fixed effects models Fixed effects models are useful in longitudinal observational studies because these models enable control of unobserved time-invariant covariates without including them in the regression equation. These models holds constant unmeasurable and perhaps innumerable influences at the unit level (Kaufman 2008). This is accomplished by using sampling units as their own control; only variation within individuals is used to create estimates that are then averaged across the sample (Allison and Waterman 2002; Allison 2009). Dropping the between-104 individual variation eliminates what Allison (2011) calls the “contaminated” variation that is likely to be confounded with unobserved characteristics (Allison 2011b). Though a useful statistical approach, there are several limitations and drawbacks to fixed effects. By design, fixed effects cannot estimate the effects of time-invariant variables, only time varying variables (Gunasekara et al. 2014). Since only information on individuals that change over time is kept for analysis, and a great deal of information is dropped, particularly differences between individuals. Thus, if characteristics vary across individuals, but do not vary much across time, this can lead to imprecise estimates (Allison 2011b). In cases where the outcome is relatively rare, there may not be enough data points for the model to be effective. The results of fixed effects models can also have large standard errors (and thus wider confidence intervals). However, Alison notes that “in non-experimental studies … this is a good trade-off” (Allison 2011b). The above section described the possible models that might be used in this situation. The following section is a discussion narrowing down the options to the most appropriate model for this situation. Discussion of models In looking at the models for count data, the negative binomial is clearly the most appropriate model. The variance is not equal to the mean in this case – there are relatively few injuries, so the data is over-dispersed. There is also no theoretical reason for the excess zeros to be due to a different process, so the zero-inflated models are not applicable either. Thus, the best model to account for the count nature of the data is the negative binomial model. In choosing a method that can take advantage of the benefits of longitudinal data, there were a few options. The conditional fixed effects model may be appropriate for use here, but the random effects model, as does not allow the effect to correlate with errors, it not of use here. The Hausman test was conducted, and this confirmed that the random effects model was not appropriate. There are likely not enough data points, due to the small firms having rare events, for the interrupted time series model. If another model could not be used due to 105 assumptions not holding, the standard error adjustment may be suitable for use in its place. The Generalized Estimating Equations may also be appropriate for use here. However, the fact that the fixed effects model allows a firm to be used as its own control to control for unobserved, time-invariant characteristics makes it the most useful given the research question and structure of the data. There were many different methods available to deal with selection bias, each with their own drawbacks and benefits. The following Table 16 is a summary of the major considerations when dealing with each of the models. Table 16 Discussion of models to deal with selection bias Type of Correction Suitable for this study? Propensity Scores Possibly. Selection process is well, but not completely, known. Coarsened Exact Matching Yes. Will depend on goodness of match can be achieved (that is, how may treated are lost because there is not an appropriate control). Heckman Two Stage Correction No. Meant for selection-into-sample bias, rather than selection-into-treatment bias. Instrumental Variable Unlikely. Difficult to find instrumental variables. One possible IV would be if inspections are more likely the closer a firm is located to a WorkSafeBC office; distance would be a useful instrumental variable. However, it is likely that the two are not strongly, if at all, correlated. Stratification Not ideal. There are many variables that are involved in the selection of a firm to target for inspection, creating too many possible strata. Synthetic Controls Possibly, but more suitable for few comparison groups, for example a comparison of a few provinces, not thousands of firms as here. Regression discontinuity No. Needs a cut-off, which is not available in this data. Might be possible in with OSHA inspections which have a cut-off of 10 employees for more for programmed inspections. 106 Difference-in-differences Possibly suitable. Can be adapted for use in longitudinal analysis. Pipeline Methods No. In this case, the comparison group is still nearly all non-inspected firms, so not an improvement on regression. Fixed Effects Suitable if Hausman test shows FE is more appropriate then RE. Model selection Considering the nature of the data used in this investigation of the effect of inspections on work-related injuries, and the models described above, there are a few options that may be considered. A test can confirm whether negative binomial or Poisson is appropriate, though negative binomial analysis is almost certainly the more appropriate analysis since injuries are relatively rare and the mean of injury counts is unlikely to be equal to the variance. Both difference-in-differences with matching, or conditional fixed effects with or without matching, are appropriate for the current study. These can both be combined with negative binomial, though estimators from count fixed effects models are more sensitive than linear fixed effects models if assumptions cannot be maintained (Gunasekara et al., 2014). The method that many statistical programs use to calculate conditional negative binomial fixed effects is controversial to some statisticians (Allison 2011a) because the fixed effects estimator is treated differently from other regressors in that model. One suggestion by Allison (2011a) was that the use of an unconditional fixed effects model49 with the negative binomial model may produce the most accurate results. This approach to dealing with this controversial methods has been used in some studies (Baltagi, Cameron, and Trivedi 2015; Wan Yaacob, Lazim, and Bee Wah 2012). Other researchers choose to use negative binomial models with conditional fixed effects, then use other methods to verify consistency, and conclude that the results are similar enough to use their method of choice: negative binomial with conditional 49 Unconditional fixed effects is the use of a dummy variable for every individual in the sample. 107 fixed effects (Furman and Stern 2016; Murray and Stern 2007; Van Ommeren and Gutiérrez-i-Puigarnau 2011). Still other researchers turn to the less desirable random effects methods (Sweeten, Piquero, and Steinberg 2013)50 or Poisson fixed effects models with adjusted standard errors (Brahm and Singer 2013). Representatives of StataCorp have stated that if the fixed effects estimator is used as a model that will allow for panel-level heterogeneity without meeting the requirements of random effects estimators, then the conditional model implemented by Stata is appropriate (“Re: St: Nbreg with Fixed Effect vs Xtnbreg,Fe” n.d.; K. Mcleod 2017). With these considerations in mind, the conditional fixed effects negative binomial model appears to be a valid choice for the investigation of the effect of inspections on work-related injuries. For the investigation of impacts on injury rates, the DiD method considers the fact that rates change over time due to reasons independent of the intervening prevention activities, such as industry booms and busts, shifts in worker demographics, and technology changes. The method does not consider the unique aspects (correlation) of longitudinal data, but clustered standard errors can be used or combined with generalized estimating equations to account for correlated errors. By including matching with difference-in-differences and creating a control group like the treatment group, the assumption of parallel trends of injuries becomes more tenable. It is important to note that confounders in difference-in-differences studies are those variables related to both selection into treatment and the trend in the outcome variable, rather than variables related solely to the outcome variable (Daw and Hatfield 2018). Ultimately, the choice is narrowed down to conditional fixed effects and difference-in-differences in ability to account for unobserved covariates, combined with matching to reduce bias via similar treatment and control groups. Note that with fixed effects, double robustness is not attainable as time-invariant covariates cannot be included in a conditional fixed effects model, but time-invariant characteristics such as sector must be used for matching. In addition, 50 The number of data points makes the unconditional fixed effects model is untenable for this scenario, and the use of a random effects estimator would not be appropriate in this case, as discussed above 108 weighting is the preferred method to incorporate matching techniques into a model. However, the weight of each subject would vary by sampling period and weights may not vary by time period in a fixed effects model – each subject may have only one weight that is applied for the entire time period. Thus, the next best option is dropping the unmatched treated and control subjects. 4.6 Replication of Previous Studies To help guide the selection of appropriate analytic methods for the current study, this section replicates the results of several published studies of workplace safety interventions using their methods and the data from WorkSafeBC for the period 2001-2014. The reasons to replicate the previous studies are twofold: 1) To make the current findings comparable to previous findings by using the same methods; and 2) To provide new evidence, as the replication of studies and synthesis of evidence is a method to increase support for causal inference (Craig et al. 2012). However, it is not advisable to reproduce studies without scrutiny. There may be reasons to discount the methods of previous studies. Even if the new data consists of the same types of measurements and variables, the method of collection or sample selection may be different enough to warrant a completely different approach to analysis. Thus, a discussion of the benefits and drawbacks of each method follows the results of the study replications. Data description In British Columbia, WorkSafeBC both regulates workplace safety and administrates workplace injury claims. The administrative claims data for these replication analyses was collected by WorkSafeBC, and provided by Population Data BC51, under appropriate privacy protocols. The data includes information on firms that are covered by WorkSafeBC’s workers’ 51 Population Data BC (PopDataBC) is a data resource facilitating in British Columbia providing access to linkable data sets to facilitate research on the population health and well-being. 109 compensation insurance program (firm level data), as well as information on injuries to workers and the resulting claims (claims data). The multiple data tables are warehoused in tables in a WorkSafeBC data warehouse and extracted and merged into one dataset for analysis (that is, individual workers with claims nested in firms matched to their firm-level data). Ethics approval was obtained by the University of British Columbia Office Of Research Ethics (H12-02635). Injury information was provided at the level of the firm in terms of total claims per firm. Prevention activity information was provided at the level of a combination of the firm and the industry classification. Firms were followed from 2004 to 2014 providing ten years of inspection data from 2005 to 2012 and two years of follow-up data on injury claims after an inspection. Firm size was measured using a “full-time equivalent” (FTE) variable derived by WorkSafeBC. FTEs are calculated using the payroll of each firm, as reported to WorkSafeBC, and the average earnings of employees in that industry52. This method is an estimation and may not measure of the actual number of employees working at each firm, though it does provide an estimated relative measure of the firm size. Cohort, description, summary statistics and trends The cohort included firms had at least one full time equivalent (FTE) employee for at least four years. This allows one year for baseline, one year for the intervention, and up to two years for follow up. Smaller firms were included relative to previous studies (Haviland et al. used greater than 10, for example) because firms of all sizes are inspected in British Columbia. In the United States, OSHA and many state OSHAs require a minimum of 10 employees before a random or program inspection can take place. It is not possible to accurately link injuries at a firm to a specific firm location if a firm has multiple locations. So, the study cohort was limited to single location firms only. In firms with more than one classification unit (CU), used by WorkSafeBC to classify the nature of work for 52 Based on Statistics Canada data 110 insurance purposes, the classification unit that had the most FTEs was used for the whole firm. However, multi-CU firms were rare (~5% of firms in BC). Finally, firms inspected in the two years (i.e. 24 months, 2003-2004) prior to the start of follow-up were excluded. This requirement was used in previous studies. Both Foley and colleagues (2012) and Levine and colleagues (2012b) required firms to have a pre-study period of two years free of any enforcement activity in an effort to standardize the treatment effect. 4.6.2.1 Injury data and trends Injury rates and trends over time were examined in order to understand how the cohort inclusion requirements affected comparability to the general population of firms in British Columbia (Figure 8). Firms in British Columbia had an acute injury rate53 that averaged around 1 injury claim per 100 FTE, with a downwards trend during the study period. The cohort included in the current analysis has an injury rate of less than 0.5 per 100 FTE with a slight upward trend during the same study period. The figures provided in Appendix D show that the decrease in the injury rate for the firms included in the current analyses compared to all firms is BC is explained by removing firms with less than one FTE or those with more than one location. 53 Acute injuries include the types of claims would be more affected by inspections. Injuries and illnesses with a long latency period were excluded. 111 Figure 8 Injury rate over study period, full cohort firms and final cohort firms, acute injuries per 100 FTE Table 17 provides the distribution of all BC firms and the included firms by sector and FTE characteristics. In particular, the service sector increases from just over 50% to nearly 70% of the total when comparing the distribution of all BC firms to that of firms included in the current analyses. Construction, transportation and warehousing, and primary resources represent a smaller proportion of the distribution of firms in the analytic sample compared to all BC firms. 1.3 1.3 1.21.20.90.9 0.9 0.90.40.4 0.40.50.4 0.4 0.4 0.40.00.20.40.60.81.01.21.42005 2006 2007 2008 2009 2010 2011 2012ACTUE INJURY RATE PER 100 FTEFull Cohort Final Cohort: Single Location, More than 1 FTE, No Inspection in Previous 24 months112 Table 17 Percentage distribution of all BC firms and analytic sample of firms by sector and FTE characteristics 4.6.2.2 Cohort definition and variables – treatment, outcome, and covariate The outcome for the replication analyses was claims for acute injuries, including for short-term disability, long-term disability and fatal claims, as used in a previous study of the effect of a policy on workplace injury rates (McLeod et al. 2015). Acute injuries and illness were used as it is thought that these types of claims would be more affected by inspections and less likely to have a long latency that extended beyond the follow up period. Short-term, long-term and fatal claims were included for comparison of the results to previous studies. The intervention, or treatment, was defined as new inspection. It is a binary variable of yes/no inspected, rather than a count variable of number of inspections. Note that the way inspections are defined by WorkSafeBC includes some activities, such as communication with employers that may not necessarily involve site visits. In 2008 - 2011, only 75 to 77 percent of inspection reports involved a worksite visit by a prevention officer. In addition, the data are unbalanced in the sense that some firms are followed for longer than others, due to ceasing to exist or becoming ineligible for the cohort. However, firms should not be lost to follow up, for the most part, as they are required to report hours to WorkSafeBC while they are operating. Table 18 describes the variables used in this study. All Single Location Only One or more FTESingle Location and One or more FTE Final CohortSector Primary Resources 5% 4% 4% 3% 3%Manufacturing 6% 4% 7% 5% 5%Construction 18% 18% 13% 10% 8%Transportation & Warehousin 10% 10% 4% 3% 3%Trade 10% 9% 14% 13% 13%Public Sector 0.4% 0.2% 0.6% 0.1% 0.1%Service Sector 51% 54% 57% 66% 68%Fraction113 Table 18 Variables available for use in statistical analyses of the impact of inspections on injury rates in British Columbia (replication studies) Variables Firm Size/ Exposure Person Years Quantity: An estimate of the employer's number of full-time equivalents (FTE). A person year, or FTE, is one person working full time for one year. Based on gross payroll for the previous year estimated on previous year’s payroll and weekly wage information from Statistics Canada and WorkSafeBC. Industry The sector that the firm does business at. The value of this is used by WorkSafeBC to determine the level of risk for premium payments. 2- and 4-digit levels were used for this study. Base Rate The premium payment amount for the 6-digit sector. Used as a proxy measure of riskiness of classification unit within 4- or 2-digit sector. Year Used to control for secular (generally economic) trends Injury Rate Measured as the number of acute injuries each year, per firm per 100 FTE. An important aspect of this study is that treatment is not random. In fact, firms are targeted based on industrial sector and other criteria, and firms that are thought to be more likely to have an injury due to these characteristics are chosen to be inspected. This means there are fundamental differences between the treated and untreated groups, possibly leading to endogeneity if some of the targeting characteristics are unknown/unobserved/unmeasured. Thus, due to size and/or industry, some firms will have a high likelihood of being inspected and some will almost never be inspected. The two groups are the opposite of randomized with firms targeted for inspection (the intervention) that leads to observable and some unobservable (differences between the treated and untreated groups. For an analytical strategy to be successful, this selection bias must be dealt with. However, endogeneity is not the only possible source of bias in an observational study. Since firms with high injury rates in the previous year may be selected for inspection this year. In the following years, the injury rates may naturally regress to the mean. This decline in injuries may erroneously be attributed to the inspection rather than regression to the mean. In sum, in choosing a model to analyze this data, it is important to address these three issues: that the data is count, it is longitudinal, and the treatment is highly targeted. 114 Analyses The methods of previous studies described in Chapter 3 were used with data from 2001-2014 from WorkSafeBC, with some modifications. The study of Italian manufacturers was not replicated because there were not be enough injuries to investigate a trend in a time series analyses limited to this one industry; and if the firms were pooled, the advantage of using longitudinal, firm-level data would be lost. An attempt was made to use the same variables in every analysis, rather than the variables used in the specific study being replicated. Variables included: firm size in Full Time Equivalents (FTE) categorized in to 5 and 7 categories, industrial sector as characterised by WorkSafeBC at the 4-digit level or 2-digit level of the classification unit (save for fixed effects model that cannot include a time invariant variable), and base injury rate (based on two years prior to follow-up). See Appendix B for a detailed description of data source and variables. Sometimes the models did not converge with these variables. In these cases, variables were removed from the model until the model converged. For fixed effects models, as used in Levine et al. (Levine, Toffel, and Johnson 2012a), time-invariant covariates were not used, and FTE was changed to a continuous variable to ensure some variation. Each analysis was run unmatched and with coarsened exact one-to-one matching. Three matches were conducted as a sensitivity analysis, each with a different random number seed, in case the random selection of matched controls made a significant difference in the results.54 The resulting match was performed with base injury rate, sector at the 4-digit level, firm size as Full Time Equivalents categorical (five categories: 1-3 FTE, 3-5 FTE, 5-10 FTE, 10-15 FTE and 15 FTE and larger) and experience rating as a categorical variable. Variables were removed one by one to examine the results of how many treatment observations were gained. The balance between control and treatment after matching was also examined. 54 The CEM add-in for Stata works by creating strata, or groups of similar characteristics. To get a one-to-one match, the k2k argument is used, which randomly prunes control observations from each stratum until there is the same number of treated and control units. 115 4.7 Results Comparing Analytical Methods of Previous Studies and Fixed Effects with Data from WorkSafeBC Difference method: Scholz-Gray and Haviland et al. The results of the replication of the methods from the study of inspections of Pennsylvania manufacturing firms are shown below in Table 19. Generally, the results of using these methods on the WorkSafeBC data, for both the unmatched and matched analyses, show a decrease in injuries in inspected firms, with a 7% reduction in acute injuries in the year following an inspection. The effect in the matched analysis is larger at 11%. Table 19 Results of Scholz-Gray and Haviland change models, percent change in acute and short-term, long-term, and fatal (SLF) injuries after inspection, unmatched and matched Generalized estimating equations: Foley, Baggs, Silverstein The results of the GEE methods used by Foley et al. applied to WorkSafeBC data, are shown below in Table 20. The results appear to show that firms that are inspected experience a significant increase in injuries in the calendar year following the year of an inspection. The matched results tend to show a smaller increase in injuries, of about 1.2 times in the year after the inspection and 1.3 times in the second year after an inspection, significant to the 0.01 p-level. 116 Table 20 Results of GEE Poisson models as incident rate ratios, matched and unmatched Exponentiated coefficients; 95% confidence intervals in brackets + p < 0.10, * p < 0.05, ** p < 0.01 Fixed effects: Levine et al. The main interpretation of the results from the fixed effects with exact matching analysis (Table 21) is that inspections have little effect on acute injuries. Selection bias from both observed variables and unobserved time invariant variables should be dealt with in the matched analysis. The fact that there is little difference between the results of the matched and unmatched analyses indicates that, by only using within firm variation adjusted with relevant covariates, the fixed effects method considers the differences that matter to the effects on injury prevention. Table 21 Results of fixed effects models as incident rate ratios, matched and unmatched Exponentiated coefficients; 95% confidence intervals in brackets + p < 0.10, * p < 0.05, ** p < 0.01 117 Matched difference-in-differences The matched DiD results (Table 22) also indicate that inspections have no effect on injury rates, a result that could be due to the reduced sample sizes that accompany matching. Once again, perhaps due to the relative rarity of injuries in this cohort, there is variability between the matches. Taking this variability into account, the results resemble the fixed effects method used above. Table 22 Results of matched difference-in-differences models as incident rate ratios, acute and short term, long term, and fatal injuries Exponentiated coefficients; 95% confidence intervals in brackets + p < 0.10, * p < 0.05, ** p < 0.01 4.8 Discussion In this instance using WorkSafeBC data, it is important to address three issues: that the data is count, it is longitudinal, and the treatment is highly targeted. When dealing with these issues, and choosing a method, there trade-offs. After examining the suitability of each analytical method and the trade-offs inherent in each approach, it was decided that fixed effects or difference-in-differences with coarsened exact matching would each be appropriate in this situation. Tests should be conducted to demonstrate and fixed (vs. random) effects and negative binomial or Poisson models are preferred. The results of the many analyses completed above using WorkSafeBC data are varied. 118 The results of using the methods from Haviland (2012) methods on the WorkSafeBC data showed a decrease in injuries in inspected firms. This analysis method does attenuate selection bias by looking only at the change in injuries within a firm; in this way this method is like fixed effects. One caveat is that the size of the firm is not considered in the model and injuries are not standardized by firm size; if larger firms are inspected more frequently and tend to be safer, this selection bias would not be accounted for. In addition, the longitudinal nature of this data and its effect on standard error is not considered. In this case, matching by firm size should help reduce the effects of selection bias, so the matched results should be closer to the true effect. The Difference/Scholz-Gray method is useful when the study group is homogenous but matching or another technique would be necessary when firm size or industry vary within the group. While the method is quite intuitive, it is also rarely used, so it is somewhat less useful for comparison. It is based on the assumption that the injury counts are log-normally distributed, which may not be a tenable assumption to make for this data. There was a treatment effect found with this method, but the fact that firm size is unaccounted for makes this a less ideal choice. In the case of British Columbia data, there is a greater range in firm size, so the size may make a larger difference than in Pennsylvania. The difference-in-differences (DiD) method controls for the fact that injury rates change over time due to reasons independent of the intervening prevention activities, though it must be assumed that the rate of change is the same in both the treatment and control groups. By using matching techniques with difference-in-differences and creating a control group like the treatment group, the assumption of parallel trends of injuries would become more tenable. DiD deals with the long-term confounders while matching can deal with bias due to transitory shocks (Chabé-ferret 2014), however it is necessary to take care when matching on pre-treatment outcomes (Chabé-Ferret et al. 2017; Daw and Hatfield 2018). Upon analysing the WorkSafeBC data using previously applied analytical methods, it was concluded that not all the methods seemed appropriate. The GEE method by Foley et al. did not consider the selection bias created by targeted inspections. There was an apparent increase in injuries that may have been because there are targeted inspections; firms with characteristics 119 that tend to increase injuries (such as sector) are more likely to be inspected and thus the inspected firms have higher injury rates. Accordingly, this model is not appropriate for a targeted inspection strategy such as used by WorkSafeBC. The effect was moderated but not eliminated after matching, which may point to an unmeasured variable being part of the targeting strategy, or the fact that sectors are targeted at the 6-digit level, while matching was completed at the 4-digit level, leading to an insufficient matching strategy. The results of the fixed effects method which was used by Levine and colleagues had variability between the results of each of the matches. The results for unmatched and matched results are similar. This is reassuring because in the case of stratification by inspection or firm type, the outcome may become rare enough that the matched results may have no internal consistency and will not be trustworthy. In this case, the unmatched analysis will be superior. The Coarsened Exact Matching method affected the results of every method except for fixed effects when trying to account for targeted rather than random approaches; sometimes this was a change in magnitude, sometimes it was a change from significant to non-significant at the 95% confidence level (and vice versa). As the fixed effects method uses individuals as their own controls, it is understandable that matching does not have a significant effect. The choice of analytic methods for the investigation of inspections on work-related injuries in British Columbia was narrowed down to conditional fixed effects and difference-in-differences as both methods could account for unobserved covariates, combined with matching to reduce bias with similar treatment and control groups. Fixed effects conditions out unobserved covariates on an individual level, while DiD conditions out differences at a group effect level. As things such as corporate or safety culture or technologies used may have an industry wide effect (group-level) but also may vary greatly firm-to-firm (individual level), the fixed effects methods are thought to be more useful in this scenario. This outweighs the disadvantage brought by being unable to use weighing in fixed effects. However, the use of fixed effects is limited when the outcome is relatively rare as the data points that include the necessary changes for using fixed effects are too infrequent. Thus, the most appropriate 120 method of analysis is weighted fixed effects, except in cases where the outcome becomes too rare, in which case DiD may be the next best option. The main conclusion from this chapter is that reproducing models using different methods from previous studies to investigate the effect of inspections on work-related injuries using the same dataset yields a variety of results: one method found an increase in injuries, one method found a reduction in injuries, and two methods found no effect on injuries. It is essential to carefully consider an estimation approach before replicating it. If the assumptions made in the original study are untenable in the new study, the results may be biased and invalid. Thus, it is important to consider what assumptions are made in each model, and whether these assumptions are met by the data and the study design. The many ways in which observational data with the characteristics of the WorkSafeBC data may be analysed were examined. The method I determined was the most appropriate, fixed effects, was used in the following chapter to study the effects of inspections in British Columbia. 121 The Effect of Regulatory Inspections on Workplace Injury Rates in British Columbia 5.1 Introduction This chapter presents the results of an investigation of the effectiveness of inspections on workplace injury rates in British Columbia (BC) based on the conceptual model and the analytic methods identified in the preceding chapters55. 5.2 Background To reduce the social and economic burden of workplace injuries, government and quasi-government agencies regulate employers to make workplaces safer. For safety regulations to be effective, workplaces must comply with these regulations. Inspections are a key part of regulators’ prevention strategies. A systematic review of the impact of OHS regulation, including the introduction of regulation and the enforcement of regulation through inspections, citations, and penalties, was published in 2007 and updated in 2016 (Tompa, Trevithick, and McLeod 2007; Tompa et al. 2016). In the more recent review, the authors concluded that there was strong evidence that specific deterrence from inspections with penalties positively reduces work outcomes such as injuries, but that there was limited evidence of an effect from inspections without penalties. While there is evidence that enforcement activities can lead to declines in injury rates, this has not been examined in British Columbia. There is also no evidence available on many sub-industries studied here, such as the transportation and services industries. This study will provide BC-specific information on the effectiveness of inspections on reducing workplace injuries and whether the effects of prevention activities vary by industry sector, firm size or inspection characteristics. 55 This chapter is meant to be a standalone chapter; thus, there is some repetition as information from previous chapters is from synthesizes and summarized. 122 5.3 WorkSafeBC Prevention and Enforcement Activities In British Columbia, the province has granted authority to WorkSafeBC, also known as the Workers’ Compensation Board of British Columbia, to administer the Workers’ Compensation Act. WorkSafeBC’s stated priority is to prevent workplace injury and the organization works to prevent injuries by, among other things, conducting work site inspections. Though WorkSafeBC commonly uses language that emphasizes cooperation between workers and employers and cultural change56, prevention officers use deterrence tools such as orders and sometimes penalties and most of the time dedicated to prevention activities is still spent on traditional enforcement activities such as inspections. Several strategies at WorkSafeBC are specifically designed to target specific firms due to the chance of injury. These programs have direct extra resources towards firms that are identified as higher risk of injury due to firm statistics, firm characteristics, or risk patterns derived from those statistics and characteristics (WorkSafeBC 2010b; “Focus Firms Committed to Workplace Safety” n.d.). The High Risk Strategy identifies and targets industries, employers, and sometimes specific tasks within those industries, that have a high serious injury risk and incidences of serious injuries and fatalities. For example, in 2019, in the construction high risk initiative, inspections focussed on health and safety planning and supervision and in the oil and gas high risk initiative, inspections focussed on well stimulation and servicing, pipeline construction, and other specific risks (WorkSafeBC 2019a). From 2008 to 2011, 66 to 68 percent of all inspection reports were related to employers within classification units targeted by various strategies57 (WorkSafeBC 2012). This demonstrates that WorkSafeBC targets firms for 56See, for example, the WorkSafeBC website “WorkSafeBC is most effective when it is dedicated to the WorkSafe initiative, facilitating the co-operation of workers and employers in preventing workplace injuries, diseases, and fatalities” and “Societal and cultural change is essential for creating a culture of health and safety in the workplace and we play a principal role in effecting this change”(WorkSafeBC 2005) 57 WorkSafeBC’s High-risk Strategy: A decade-long strategy to focus resources on the industries and employers with the highest number of serious injuries, fatalities, and/or highest claim costs. (http://www.worksafebc.com/about_us/assets/PDF/StrategicPlan.pdf) 123 inspection and accordingly an aspect of the inspections program that needs to be accounted for analytically. During an inspection, inspectors may find violations of the regulation or conditions in need of improvement. In this case, the inspectors may issue orders58, written directives for a person or firm to take measures to comply with the Workers’ Compensation Act or its regulations (WorkSafeBC 2011). More serious infractions, such as violations that may result in a high risk of serious injury, repeated violations, or failure to comply with orders, may warrant the imposition of financial penalties to “motivate the employer receiving the penalty and other employers to comply with the Act and regulations” (Item D12-196-1 WorkSafeBC Policy and Regulation Division 2014). Enforcement from inspections is generally more persuasive than deterrent. Orders, a written document requesting that an employer resolve a hazard or implement a safety program, are common, with about 60,000 orders per 90,000 inspections during 2005 to 2012 (see Table 9). However, actual punitive activities are less common. WorkSafeBC levies penalties infrequently (see Table 9), with just over one penalty for every 100 inspections, and the amount of the penalties tends to be relatively large. These penalties had a median value of $5000. This range of actions following an inspection, from an order to a warning letter to a penalty, demonstrate that WorkSafeBC prevention activities are part of a penalty pyramid. The rarity of these penalties shows that WorkSafeBC uses a persuasive rather than a deterrent version of responsive regulation, as described by Ayres and Braithwaite (Ayres and Braithwaite 1992). Previous research has found that only inspections with associated penalties seem to have an impact on reducing injuries. In BC, penalties are rare enough that there is not enough data to stratify and examine the effect of inspections with penalties. Since WorkSafeBC inspections rarely have penalties, it is likely that inspections will not be effective in reducing injuries. 58 “…current policy allows WorkSafeBC only minimal discretion over whether to issue orders. It requires WorkSafeBC to issue orders to whomever is responsible whenever violations are found.” (WorkSafeBC Policy and Regulation Division 2012) 124 From a theoretical perspective, for an inspection to be successful at reducing injuries at a firm, it must (see Chapter 2 for details):  Be enforcing legitimate and technically effective regulations, with  An inspector that has the skills to capture unsafe conditions, at a  Firm targeted for maximizing efficiency, with  Motivation (fiscal or otherwise) or resources provided as necessary to help the firm implement the required changes. 5.4 Methods and Materials This study will examine firm-level data from WorkSafeBC from 2003 to 2014, with baseline and follow-up injury data measured from 2003 to 2014 with inspections measured from 2005 to 2012. In 2000, several new enforcement and policy initiatives were introduced by WorkSafeBC, including changes to administrative penalties and amounts, and to the experience rating system. To address this issue, the study period began five years after the introduction of these policy changes. In addition, the effects of time were accounted for in the analysis. Data source and sample definition Data collected by WorkSafeBC for the administration of compensation claims was made available for research purposes via Population Data BC59, and held for this specific project by the Partnership for Work, Health, and Safety at UBC, under appropriate privacy protocols. The data includes information on firms that are covered by WorkSafeBC, the provincial workers’ compensation insurance program in British Columbia (herein referred to as firm level data), as well as information on injuries to workers and the resulting compensation claim benefits (herein referred to as claims data). Ethics approval was obtained by the University of British Columbia Office of Research Ethics (H12-02635). 59 Population Data BC (PopData) is a data resource facilitating in British Columbia providing access to linkable data sets to facilitate research on the population health and well-being. 125 Injury information was provided at the level of the firm, or in other words, the aggregate counts of claims at each firm per year. Prevention activity information was provided at the level of firm location (for those with multiple firm locations) and by the firm’s classification unit (for those with multiple classifications of the nature of work for compensation purposes). However, it subsequently proved impossible to accurately link injuries at a firm to a specific firm location in the administrative data, so the study was limited to only single location firms60. In these single location firms with more than one classification unit, the classification unit that had the most FTEs were used to characterize the whole firm for the purpose of analysis61. Firms were followed from 2004 to 2014; this allowed for ten years of inspection data from 2005 to 2012, allowing for a two year follow up period after an inspection. The firms in the cohort had only one location and were included if they had at least one full time equivalent (FTE, a variable estimated by WorkSafeBC) for four years, allowing one year for baseline, one year for the intervention, and up to two years for follow up. Longitudinal data was used so firms were included for each four-year time period where they met the qualifications for inclusion in the cohort. Smaller firms than have been used in previous studies (Haviland et al. (2012) used greater than 10, for example) were included in the current analyses because firms of all sizes are inspected in British Columbia. Outcome and treatment variables Acute injuries, an injury definition previously used by McLeod and colleagues (2015), were examined to investigate the impact of the inspections on injury rates. Acute injuries are defined as any claim for amputations, fractures, dislocations, concussions, cold or heat exposures, burns, abrasions/contusions/lacerations or hernias. This injury definition eliminates claims due to occupational illness or diseases such as cancer, claims for cumulative or chronic conditions such as hearing loss, and claims for injuries with a longer time to develop. The acute 60 Single location is a reference to the number of offices rather than actual worksites. Thus, a roofing company may have several worksites and still be considered single location if there is only one office reporting hours. 61 Single location firms with multiple CUs were rare – 7,536 out of 147,912 firms had more than one CU in our cohort 126 injury definition also excludes injuries as a result of motor-vehicle accidents, as these are generally less likely to be directly influenced by WorkSafeBC regulations and prevention activities but rather governed under federal transportation regulations and prevention activities. All short-term and long-term disability plus fatal injuries (SLF) regardless of nature of injury were also examined for comparison to previous studies.62 The treatment variable was categorized as inspections, inspections with an order, and inspections with fall protection orders. Inspections are defined by WorkSafeBC to include contact with employers, but not necessarily via a worksite visit. However, most inspections do include a worksite visit. From 2008 to 2011, 75 to 77% of inspection reports involved a worksite visit by a prevention officer, and reports not linked to a worksite visit were typically a follow-up to prior prevention activity involving a worksite visit (WorkSafeBC 2012). In order to isolate the effect of an inspection from the effect of previous enforcement activities, a firm was removed from the sensitivity analysis if they had had an inspection in the previous 24 months. As a sensitivity analysis, inspections with worksite visits were analysed separately. The previous studies examined above used varying follow-up periods. One year is a common follow-up period for the studies reviewed, and in cases where the follow-up period is longer, the effects tend to decline significantly after the first year. An exception to this is injuries that take longer to develop. For instance, Foley (2012) found evidence that the second measurement year was the only year where a significant effect of enforcement activities was found for musculoskeletal injury claims. Although the effect was not statistically significant, the finding by Foley also suggests a lag between a reduction in hazards and a corresponding decline in injuries. 62 Though the acute injuries are thought of as a more precise measure of injuries that will be affected by inspections, an additional benefit of using Short term, long term, and fatal injuries is that there are more observations of change – sometimes nearly double the outcome data points. Since fixed effects regression is an analysis method that requires outcomes to change within a studied unit in order to measure change it is useful to increase the observations of a relatively rare outcome such as injuries. 127 The decision for the current analyses was to investigate injury outcomes using a one- and two-year follow-up period post inspection, using monthly follow-up windows during the 12 months and the 13 to 24 months. The 2 to 14 months before an inspection was used for baseline measurement of injury rates. This baseline window, not using the 2 months prior to an inspection, was used in case the inspection being investigated was one of the rare cases where the inspection was part of an earlier accident investigation and where regression to the mean may be an issue. Variables Variables were either used to create a matched control group and to adjust for potential confounding in the fixed effects model. The majority of covariates were used in matching process rather than for adjustment in the regression analyses because it was not of interest to estimate the effects of the covariables on injury rates but rather to adjust for their potential confounding effects when estimating the effect of inspections on injury rates, and also because only time varying variables can be used in fixed effects models. Austin and Stuart (Austin and Stuart 2015) concluded that when choosing covariates for the propensity score model, one should focus on including covariates that should be balanced (“prognostically important covariates”) rather than all covariates that may be important in the treatment selection. That same approach was taken here in the choice of exact matching parameters. Initially the variables for the baseline injury rate, the 4-digit sector (industry) category for included firms, experience rating category, and firm size (both continuous and categorical) were used in the matching process. The size of firm was measured by full time equivalents and was included as the size of firm may effect both likelihood of inspection and likelihood of workplace injury (Sørensen, Hasle, and Bach 2007; Mendeloff et al. 2006). Firm size derived by WorkSafeBC from a combination of firm-level payroll and average wage data by industry (occupation) from census data. Base premium rate (base rate) was included as a measure of the risk of injury at the firm due to the industry; the base rate is the amount a firm pays in workers’ compensation premiums based on the insurance costs of its classification unit. 128 With a large dataset and a complex statistical method, it is important to be judicious in choosing variables to ensure stability of the models. With fixed effects, it is also necessary to ensure that variables are time varying. The Akaike’s Information Criteria (AIC), Bayesian Information Criteria (BIC) and likelihood ratio tests were used to determine that the base premium rate did not contribute significantly to the model and was excluded from further consideration. See Table D1 for the results of these tests. Matching The study is a population-based retrospective observational cohort study of firms in the Province of British Columbia. In this intervention study inspections are targeted – firms are chosen for inspection because they are at a high risk of serious injury due to industry. This leads to selection bias. Methods to deal with selection bias, and the rationale behind choosing the methods in this chapter, are discussed in Chapter 4. Statistical analysis Fixed effects along with coarsened exact matching63 were used to deal with time-invariant unobserved differences between the control and treatment groups. Fixed effects models address omitted time invariant variable bias by allowing individuals to become their own controls64. A limitation is that only those firms that experience a change in outcome are included in the analyses, making estimation difficult as the sample size gets very small and very sensitive to outliers, and particularly a problem if the outcome is fairly rare (Allison 2011a). A more detailed discussion of the statistical methods can be found in Chapter 4. The model below was used, with i indicating an individual firm, and t indicating the year time period of observation. 63 The matched results are the first set random number seed set at 320 unless that did not converge. In that case, the next match that converged was used (set at 230 and 32). 64 The Hausman test was used to confirm that a fixed rather than random effects model should be used. 129 Acute_Injuryit =  +1Inspectionit +2Yeart + 3ln(Sizeit)+ vi + it The acute injury count is modelled as a function of the constant , the coefficients and 1 and 2, corresponding to the variables of inspection (yes/no) and a dummy for year. The size of firm as measured by full time equivalents was included as the size of firm affects both likelihood of inspection and likelihood of accident. There are two error terms: vi is an error term that controls for unobserved time-invariant individual fixed effects and ε it is an error term. Covariates were selected taking the following considerations into account:  whether they were time varying (a necessity with fixed effects),  whether they were prognostically important,  whether the matching process was deemed sufficient in making the treatment and control groups similar on that characteristic, and  whether the inclusion led to instability in the model65. All analyses were performed using Stata 14 (StataCorp. 2015. Stata Statistical Software: Release 14. College Station, TX: StataCorp LP). 5.5 Results Cohort creation and descriptive statistics Figure 9 below shows the result of the development of the cohort, starting with all firms registered with WorkSafeBC in 2005 to 2012 to the final analytic cohort. The cohort used for analysis included 74,394 single location firms in British Columbia with at least one full time equivalent employee. 65 For example, the inclusion of firm size as a categorical variable led to the non-convergence of several models. Changing the FTE to the natural log of a continuous variable was helpful in solving this non-convergence. 130 Figure 9: Cohort creation and final analytic sample for investigation of the effect of inspections on workplace injuries There are some key differences in injury trends among firms included in the cohort as compared all firms in the province of British Columbia, as shown in Table 23 below. Most notably, the injury rate is lower in the final analytic cohort of firms. Figure 10 and Table 24 help to understand how this difference arises. Specifically, the proportion of firms in the analytic sample from the service sector which has a lower overall injury claim rate in the province, increases; while the proportion from primary resources, construction, and transportation and warehousing sectors, with higher overall injury claim rates relative to all BC firms, decrease. Table 23 Changes in cohort characteristics by cohort selection Number of FirmsMean FTE Sum FTESum Acute InjuriesMean Acute Injury RateSum SLF InjuriesMean SLF Injury RateAll firms 2005-2012 327,482 10.5 16,156,464 169,441 1.05 441,121 2.73Single location firms 2005-2012 265,095 3.6 4,138,523 27,297 0.66 56,465 1.361+FTE firms, 2005-2012 132,665 21.0 14,340,130 145,093 1.01 387,235 2.70Single location, 1+FTE firms, 2005-2012 89,593 7.5 3,128,124 16,115 0.52 33,937 1.08Single location, 1+FTE firms, 2005-2012, only firm-years with four year follow up and no inspection in past 24 months 74,394 7.4 2,771,491 11,584 0.42 24,250 0.87131 Figure 10: Changes in distribution of firms by sector by cohort selection As the number of firms decreases in the analytic sample, decreasing by 77% from all firms in British Columbia, the enforcement activities decrease proportionally. For example, inspections decrease by 88%. Accordingly, there too few warning letters and penalties in the final analytic sample of firms to analyse the effects of these more punitive enforcement tools. Table 24 Changes in firm characteristics by sample selection criteria Sum InspectionsSum OrdersSum Warning LettersSum PenaltiesMedian Penalty AmountAll firms 2005-2012 93,402 61,301 1,789 1,264 $ 5,000.00 Single location firms 2005-2012 38,944 24,545 591 404 $ 5,000.00 1+FTE firms, 2005-2012 63,591 42,865 1,346 943 $ 4,847.88 Single location, 1+FTE firms, 2005-2012 18,467 11,933 307 196 $ 4,692.67 Single location, 1+FTE firms, 2005-2012, only firm-years with four year follow up and no inspection in past 24 months 10,485 6,439 130 78 $ 4,562.67 132 Matching results Table 25 below shows the results of coarsened exact matching on the composition of firm level variables in the new cohort. The distribution of all variables included in the matching model became more similar between the treated and control firms, as intended by the matching process. Although injury rate was not included in the matching model, its mean across firms also became more similar treated and control firms66. Table 25 Results of matching firm size, base premium rate, injury rate, and experience rating, using data extract from study Table 26 below shows the results of the composition of the matched cohort by subsector (4-digit sector) as classified by WorkSafeBC. As the exact match was forced for the sector variable, a perfect match on this variable was achieved, though the trade-off is that there will remain some firms that will not have a match and will need to be excluded. 66 Though matching worked well for base rate and experience rating, there remained differences between the groups for firm size and it was important to control for firm size in the regression analysis. Not Inspected InspectedNot Inspected InspectedAverage Firm Size in Full Time Equivalents 7.0 10.6 9.3 10.3Average Base Premium Rate in Dollars 1.11 3.19 2.98 3.00Number of Firms Where Experience Rating is Discount or Equal to 1 332,636 8,259 7,972 7,972Number of Firms Where Experience Rating is Surcharge 5,629 576 397 397Unmatched Matched133 Table 26 Results of matching firms by sector, using 4-digit sector level, number of firms in each category Model results 5.5.3.1 By type of inspection and type of injury The results of the models are shown below in Figures 11 and 12 show the results of the matched fixed effects67 on acute and short term, long term, and fatal injuries, respectively, for all inspections and inspections with orders. 67 The matched results are the first set (random number seed set at 320) unless that does not converge. In that case, the next match that converged was used (set at 230 and 032). Not Inspected InspectedNot Inspected Inspected7010 Agriculture 6306 283 271 2717020 Fishing 108 8 6 67030 Forestry 628 219 175 1757040 Oil & Gas or Mineral Resources 1991 52 51 517110 Food and Beverage Products 1699 69 67 677120 Metal and Non-Metallic Mineral Products 2921 241 222 2227130 Petroleum, Coal, Rubber, Plastic, and Chemical Products 1955 83 75 757140 Wood and Paper Products 3059 274 233 2337150 Other Products (NEC) 4788 161 151 1517210 General Construction 19308 3318 3090 30907220 Heavy Construction 37 11 5 57230 Road Construction or Maintenance 595 85 69 697310 Warehousing 271 30 24 247320 Transportation and Related Services 9586 448 429 4297410 Retail 33682 740 728 7287420 Wholesale 11847 249 245 2457530 Public Administration 445 19 19 197610 Accommodation, Food, and Leisure Services 51076 742 739 7397620 Business Services 63970 238 238 2387630 Professional, Scientific, and Technical Services 29831 387 382 3827640 Other Services 31598 878 852 8527650 Education 5050 81 81 817660 Health Care and Social Assistance 56285 201 200 2007670 Utilities 1229 18 17 17Unmatched Matched134 It was found that inspections are generally not associated with a lower injury rate. Figure 11 Inspection effect on acute injuries, by duration of follow up and type of inspection (with 95% confidence interval bars) 0.950.901.070.9800.20.40.60.811.21.41.61.82I N S P E C T I O N I N S P E C T I O N W I T H O R D E R I N S P E C T I O N I N S P E C T I O N W I T H O R D E R1 2 M O N T H S 1 3 - 2 4 M O N T H S135 Figure 12 Inspection effect on all short term, long term, and fatal injuries combined, by duration of follow up and type of inspection (with 95% confidence interval bars) Table 27 provides the results of the matched and unmatched conditional fixed effects models. Generally, inspections are not associated with a reduction in acute injuries one-year post inspection, at the firm level in British Columbia during the study period. However, inspections with orders are associated with a 10% decrease in acute injuries, although this decrease is not statistically significant regardless of the type of matching used for treatment and control firms. No effect of inspections, with or without orders, was observed for acute work-related injuries at 13 to 24 months post inspection. No effect of inspection, with or without orders, was observed on any work-related injury (short-term, long-term, fatal) at either 12 months or 13 to 24 months post inspection (Table 28). In addition, inspections with fall protection orders are not associated with a change in falls from height injuries (Table 29). Samples of the full output tables from Stata can be found in Appendix D. 136 Table 27 Results of conditional fixed effects model by inspection type, acute injuries, and match (match was performed 3 times, with a random number starting value of 320, 230, or 032) Table 28 Matched and unmatched results of conditional fixed effects model by inspection type, short term, long term, and fatal injuries Results 95% LCL 95% UCL n (obs) Results 95% LCL 95% UCL n (obs)Match 320 0.95 0.86 1.05 52,406 1.07 0.96 1.20 53,818 Match 230 1.00 0.90 1.11 52,484 0.98 0.88 1.10 54,797 Match 032 0.96 0.86 1.06 51,398 1.05 0.94 1.17 54,649 Unmatched 1.00 0.93 1.08 611,022 0.97 0.90 1.04 741,454 Results 95% LCL 95% UCL n (obs) Results 95% LCL 95% UCL n (obs)Match 320 0.90 0.78 1.04 30,640 0.98 0.84 1.14 35,494 Match 230 0.90 0.78 1.04 31,805 0.99 0.85 1.14 34,111 Match 032 0.89 0.77 1.03 30,724 0.94 0.81 1.09 34,332 Unmatched 0.910+ 0.81 1.02 552,235 0.96 0.87 1.07 671,584 + p < 0.10, * p < 0.05, ** p < 0.0112 month followup 13-24 month followupInspections12 month followup 13-24 month followupInspections with Orders137 Table 29 Matched and unmatched results of the conditional fixed effects for inspections with fall protection orders, fall from height injuries only 5.5.3.2 By sector Figures 13 and 14 below show the results stratified by sector of the matched fixed effects models. The matched model did not converge for several sectors as noted below likely due to a small sample size. Generally, there is no observed effect that inspections work to reduce injuries in most sectors during the 12 or 13 to 24 months post inspection. The exception is the service industry, where there is a 23% reduction in injuries in the 12 months following an inspection (Figures 13 and 14). Inspections with orders are not effective at reducing Short term, long term, and fatal injuries during the 12 or 13 to 24 months post inspection (results not shown). Inspections with orders at service sector firms is associated with a significant reduction in acute injuries during the 12 months post inspection (Figure 15). While reductions were also observed for manufacturing and trade firms, and increases for construction firms, the confidence intervals for these effects were wide and likely due to small sample sizes for sector specific models. 138 Figure 13 Inspection effect on acute injuries, 12 months following inspection, by sector Figure 14 Inspection effect on acute injuries, 13-24 months following inspection, by sector 139 Figure 15 Inspection with order effect on acute injuries, 12 months following inspection, by sector Figure 16 Inspection with order effect on acute injuries, 13-24 months following inspection, by sector 0.720.921.05 1.061.330.880.000.200.400.600.801.001.201.401.601.802.002.202.40PR IM AR Y R ESOU R CE SMAN UFACT UR I NG CO NST R UCT IO N T RAN SPO R TAT IO N AND WAR EHO USI NGTR AD E SER VICE S140 5.5.3.3 By firm size The results of the fixed effects models stratified by firm size are shown in Figures 17 and 18 below. Medium and small firms both show no effect on injuries from an inspection. In the first 12 months after an inspection, however, large firms have 20% fewer injuries. The effect disappears during the 13 to 24 months post inspection. When looking at inspections with orders, the results were very similar. They did not seem to be more effective than inspections as a whole at large firms. The result at small firms is suggestive that orders may be effective at reducing injuries there, though the result was not significant. Figure 17 Inspection effect on acute injuries, by injury type and duration of follow up, by firm size: small 1-5 FTE, medium 5-20 FTE, large 20+ FTE 141 Figure 18 Inspection with order effect on acute injuries, by injury type and duration of follow up, by firm size: small 1-5 FTE, medium 5-20 FTE, large 20+ FTE 5.5.3.4 Sensitivity analysis To further examine the relationship between sector and size, the two types of inspection that showed significant effects on injuries, service firms and large firms, were stratified further to service firms stratified by size (Table 30). It appears that the effect is occurring among large service sector firms only. There is no effect in large non-service firms or in small/medium service firms. This result suggests that the observed effect of inspections driven by a few, specific, large service firms. When comparing site visit only inspections to all inspections, which as the variable used in the analyses above, there was little difference between the two sets of results (Table 31). The unmatched result was nearly the same at approximately a null result. The matched results were likewise similar between the site visit only and all inspections results. Ideally, this stratification would be completed for each sector-size combination, but there were only enough firms to have a sufficiently sized sample in the service sector. 142 Table 30 Inspections in large service sector and non-service sector firms, 12 month follow up Table 31 Inspections with site visit compared to all inspections, 12 and 13-24 month follow up Another sensitivity test was conducted removing firms with outlying size and injury rates from the cohort. Tables 32 through 34 show the results of this analysis. Removing firms by size resulted in very similar results to the full cohort. Removing firms with higher injury rates, greater than 0.1 acute injuries/FTE, removed quite a few observations and had quite a large impact. Among the remaining firms, those with inspections experienced a 16% reduction in injuries in the following 12 months, and those with orders experienced a 19% reduction in injuries in the following 12 months. Both were significant at the 95% confidence levels. Results 95% LCL 95% UCL n (obs) Results 95% LCL 95% UCL n (obs)Match 320 0.64** 0.46 0.88 3,914 0.89 0.69 1.16 5,234 Match 230 0.62** 0.44 0.88 3,764 0.86 0.66 1.12 5,155 Match 032 0.58** 0.41 0.81 3,737 0.91 0.70 1.18 5,208 Unmatched 0.85 0.68 1.06 55,418 + p < 0.10, * p < 0.05, ** p < 0.01model did not convergeInspections in Large Firms, 12 month follow upAcute Service Firms Acute Non-Service Firms143 Table 32 With very small firms removed (<1st percentile FTE) Table 33 With very large firms removed (>99th percentile FTE) Table 34 With firms with higher injury rates removed (>0.10 Injuries per FTE) Results 95% LCL 95% UCL n (obs) Results 95% LCL 95% UCL n (obs)Match 320 0.95 0.86 1.05 52,109 0.90 0.78 1.04 30,536 Match 230 1.00 0.90 1.10 52,259 0.90 0.78 1.04 31,721 Match 032 0.96 0.86 1.06 50,990 0.89 0.77 1.03 30,544 Unmatched 0.96 0.86 1.06 607,749 0.91 0.81 1.02 549,198 Inspections Inspections with OrdersResults 95% LCL 95% UCL n (obs) Results 95% LCL 95% UCL n (obs)Match 320 0.98 0.88 1.09 51,153 0.91 0.79 1.05 30,032 Match 230 1.02 0.92 1.13 51,200 0.90 0.78 1.04 31,121 Match 032 0.98 0.88 1.09 50,195 0.90 0.78 1.05 30,169 Unmatched 1.00 0.92 1.08 590,643 0.94 0.84 1.06 534,261 Inspections Inspections with OrdersResults 95% LCL 95% UCL n (obs) Results 95% LCL 95% UCL n (obs)Match 320 0.84* 0.74 0.97 31,790 0.81* 0.67 0.98 19,628 Match 230 0.82** 0.71 0.94 32,161 0.79* 0.65 0.96 19,287 Match 032 0.81** 0.71 0.93 31,536 0.77** 0.64 0.93 19,984 Unmatched 0.79** 0.70 0.89 516,660 0.76** 0.66 0.87 562,313 + p < 0.10, * p < 0.05, ** p < 0.01Inspections Inspections with Orders144 Figure 19 Results of sensitivity analysis removing firms by size and high injury rates, Inspections Figure 20 Results of sensitivity analysis removing firms by size and high injury rates, inspections with orders 0.95 0.980.8400.20.40.60.811.21.41.61.82VERY SM AL L F IR M S RE MO VED ( LES S TH AN 1ST P ERC EN TI LE)V ER Y LA R GE F IR MS R EM OV ED (GR EAT ER THA N 99 TH P E RC EN TI LE)F IR M S W ITH HIG H I N JU RY R AT ES R EMOV ED ( GR EATER T H AN 0 .1 I NJU R Y P ER FTE)1- 1 2 M ON T H S AFTER I NSP E C T IO N0.90 0.910.8100.20.40.60.811.21.41.61.82VERY SM ALL F IR M S R E M OVED ( LESS TH A N 1 S T P E RC EN TILE)V ERY LAR GE F IR M S R EM O V ED (GR EA TER T H AN 99 TH P ER C ENT I LE)F IR MS WITH H I GH IN JUR Y RAT ES RE M OVED (G RE ATER TH AN 0 .1 IN JUR Y PE R FT E)1 -1 2 M O N TH S A FT ER I NSP ECT ION W I TH OR DE R145 5.6 Discussion In the current study that utilized rigorous methods and analytic approaches to address biases, there was little evidence that inspections alone or inspections with orders were associated with a reduction in work-related injuries among British Columbia firms in general between 2005 and 2012. In fact, in some cases, inspections appeared to increase injuries, which could be due to either an increased reporting rate due to the increased visibility of WorkSafeBC after an inspection, or what Mendeloff (2006) calls a “perverse” effect of inspections: “ signaling to management that there were no problems that needed its attention”. However, there was some evidence that inspections alone were associated with a reduction in acute injuries in large, service sector firms specifically (20+FTE), though this may be due to a statistical artefact. Taken together, the evidence suggests that there may be opportunities to bolster the effectiveness of inspections through tailored implementation guidelines or policy changes, but also that further study is warranted. Inspections are an opportunity to help firms understand the requirements of regulations, but small firms may be disadvantaged in this regard relative to large firms (Hampton 2005). The larger service firms may have an advantage, as observed in the current study, in that they are more likely to have safety committees and safety professionals that can use the information from an inspection more strategically that results in the prevention of work-related injuries. Smaller firms may not have these resources or information. For smaller firms, advice imparted via an inspection accompanied by an order may provide more opportunity for limited resources to be deployed to take action that ultimately results in improvement in work-related injuries. Consultation may be a useful tool in gaining compliance among smaller firms, as observed in the current study, though an Ontario study did not find consultations to be effective68 (Hogg-Johnson et al. 2012). Other studies conducted in North America, particularly those discussed in Chapter 3, found that inspections with penalties, and consultations, were more effective than all 68 That study also found inspections with orders to be ineffective, so it is perhaps not comparable to this situation. 146 inspections. This current study also found that inspections on their own without orders, were not effective, except for a reduction of acute injuries among large firms and service firms. Penalties were too rare to investigate, but orders were effective in limited circumstances. That there seemed to be an impact of inspections, with and without orders, on large service firms was not consistent with our initial hypothesis. As per the matching results in Table 26, most of the service industry group was made up of hospitality and other services. Previous studies have not looked explicitly at any industry except manufacturing, and the cohorts in both the Levine and colleagues and Foley and colleagues studied both had a smaller fraction of service firms (4% and 24% respectively). Additionally, it was possible that this observed effect was due to chance, given the number of analysis conducted. This would warrant further study focused on the services industry, as it makes up a large part of the British Columbia economy. Fall protection inspections seem to be very good at targeting firms that might have safety issues but are not necessarily effective at improving them. When a sensitivity analysis was conducted by removing firms that had high injury rates were completed, inspections appeared to be more effective among the new group. However, many observations were removed in this process. In addition, interventions that worked at firms with higher injury rates would be the most impactful. Looking back at the theoretical model from Chapter 2, WorkSafeBC inspections could incorporate additional aspects of the ‘responsive regulation model’ in order to increase their effectiveness. Responsive regulation is more than just the pyramid seen in Figure 3. It calls for both harsh penalties to be in the background, but also a range of creative strategies to induce compliance given the firm’s circumstance, ability and willingness to change. In addition, more support could be provided to firms that want to comply but that lack the resources. Indeed, consultations are relatively rare in British Columbia and there is evidence that for compliant firms these can be effective (Foley et al. 2012). Finally, regulations that go beyond sociotechnical compliance may be needed that focus on safety management and organisational culture. Moreover, inspections may not be appropriate for injury risk reduction at firms with very complex or haphazard internal workings, in which case self-regulation activities such as 147 safety management programs may be more effective. However, it would be essential to combine the self-regulation with legal support and the advice of external stakeholders to ensure it is effectively implemented (Parker 2014). A shift to this mix of responsive regulation may be occurring in British Columbia. In 2014, in response to a 2012 workplace tragedy at a sawmill in Burns Lake, the British Columbia government released an action plan to improve the inspection and investigation process in general, in addition to recommendations for wood manufacturing industries specifically. WorkSafeBC agreed to implement the recommendations in the province, which included: prioritizing education, increased training of WorkSafeBC officers, developing a hierarchy of enforcement tools, increased use of stop work orders, and the introduction of citations (British Columbia Provincial Government 2014). Strengths and limitations There are some study limitations that must be acknowledged. The main limitation is the retrospective and observational study design to examine an intervention that is applied in a non-random fashion; analysis methods were chosen to overcome this situation, though it may not be as rigorous as a randomize study. Further, the data was administrative and was not collected for the purpose of this research study, which meant that some variables were less than ideal and could have introduced bias. For example, the full time equivalents variable was an estimate using census and payroll data, rather than being measured directly. This study’s obligatory focus on single location firms may not be generalizable to larger multi-location firms. However, the study sample of firms enabled a detailed look at smaller firms (1+ FTEs) compared to most previous studies (10+ FTEs), and included all industries compared to previous studies focused on single industries (see Haviland et al. 2012; Agnesi et al. 2016). Another limitation is the potential for reporting bias. The presence of an inspector at a worksite may prompt an increase in the number of workplace injuries reported to WorkSafeBC, leading to a difference in the injury reporting behaviours between treatment and control firms. This may mask an injury reduction effect as the increase in reporting artificially raises injury 148 rates. In addition, co-interventions such as consultations and education visits around the time of an inspection, could not be controlled for in the current analyses. However, consultations and education visits are uncommon at WorkSafeBC and any cross-contamination of the observed effect of inspections with these interventions should be minimal. Finally, the fact that some firms that are considered single location may have several worksites means that the measured effect of an inspection may be diluted if there is little safety coordination between sites; that is, if the results of an inspection at one site are not able to be learned or applied at another site the injury rate may not decrease at the other sites. In that way, the injury rate over the whole firm may not change much in response to an inspection. Despite these limitations, this study was an improvement on previous studies in several key ways. The use of matched fixed effects for a population level cohort is a rigorous analysis and may provide causal evidence when applied to observational data. In addition, the rich linked, WorkSafeBC data provided important matching and potential confounder variables of high quality for inclusion in the analyses. This meant data loss was minimized and the data available strengthened the matching methods and the multivariable models to investigate the effect of inspections on work injuries. 149 Overall Conclusions of the Dissertation 6.1 Introduction I conclude this dissertation with a synthesis and a critical assessment of the program of research that investigated the effectiveness of inspections on firm injury rates in the Canadian province of British Columbia. A rigorous examination of the effect of inspections was warranted given the significant resources devoted to this enforcement activity and the lack of Canadian evidence to support policy decisions in the Canadian context. Even in other jurisdictions outside of Canada, where the use of inspections is studied comprehensively, there are few conclusions to drawn from to guide policy decisions given the methodological limitations of prior studies and the equivocal findings across studies. By creating a theoretical model of the inspection process, including aspects that may impact inspection effectiveness, and the use of statistical analysis, this paper provides insight into inspections and provides guidance on how to effectively research inspections. Below I revisit the research questions and integrate the results with the results of previous studies. Finally, looking to the future, I suggest ways the results can be incorporated into policy, and suggest prospective research to further investigate the effectiveness of inspections and other regulatory activity. 6.2 Summary of findings in context of research questions and previous research Can a practical model of workplace safety regulation and enforcement be generated using theories from various disciplines? The focus on economic rationality in the study of enforcement exposes an overly strong reliance on financial motivations, neglecting the contributions that other academic disciplines can make. To address this neglect of multidisciplinary information, a summary of the theories that describe many of the characteristics of organizations and workers was presented in Chapter 2. Since responsive regulation is the structure within which many organizations appear to be operating, these multidisciplinary theories were examined in the specific context of 150 responsive regulation. The summary was then synthesized into a working model of workplace safety inspections (see Figure 3). Additionally, researchers have relied on models that focus on the organization as a whole and do not reference the nuances of how organizations work. However, the number of individuals involved in the regulation and safety of a workplace, along with workplace organizational and individual worker’s behaviours, indicate a more complicated set of motivations, which means that the organization can be working on a different set of goals from the decision makers. This model starts with a legitimate regulation regime that develops regulations that result in a safer work environment. High quality inspections targeted at firms that need improvement are a required condition for success. Using responsive regulation, both enforcement and compliance techniques can work to achieve compliance, but both require discretionary use by inspectors and a relationship between inspectors and firms, to achieve compliance. The inspector may be required to intuit the motivations of firms to identify those that are motivated by purely rational calculi and apply deterrence methods, while avoiding using punitive techniques with generally compliant firms that may see these methods as antagonistic and become less cooperative. As the combination of compliance motivations will vary from firm to firm, this method requires well-trained and perceptive inspectors that can move beyond motivating firms and investigate facilitating safety. In concert with this, for an inspection regime to be truly responsive, inspectors must have a range of options at their disposal, from the ability to provide information to firms that need extra help, to of levying harsh penalties for recalcitrant firms. Depending on the which of Rubin’s theories (2005) of the firm that the organizational structure resembles, inspectors may need to speak the language of the firm or develop a working relationship with more than just the decision makers in the firms. 151 Putting inspections in the context of today’s enforcement theories The results of studies of inspections from the United States that have applicability to the British Columbia context have been equivocal. Results differ by jurisdiction, and even among studies within the same state, the effectiveness appears to change over time. However, by examining publicly available data, and studies and reports of each regulator, conclusions were drawn on what aspects of the regulatory system may impact the effectiveness of inspections. For example, inspections are much more frequent in Washington, leading to increased general deterrence due to probability of inspection and possibly decreased specific deterrence as firms were more prepared, that is, firm decision makers had a higher expectation they would be inspection and reacted accordingly. Penalties are much higher in Pennsylvania and California than Washington, which can increase both specific and general deterrence. In California, these higher penalties are appealed frequently, and these appeals take much longer in California than in any other state. This may delay the effectiveness of appealed inspections as compliance is not required until the appeal is decided. The results of the different studies also indicated that inspections with penalties were more effective than inspections without penalties. This may be because penalties draw attention to matters that need attending to. In addition, consultations may be effective at reducing injuries. In the context of British Columbia, it is likely that inspections that do not generally have associated penalties (which are most inspections in BC), will not be effective at reducing injuries. Orders may be effective for those firms where regulatory mechanism is to draw attention to an infraction for inattentive or un-informed firms. This is in line with the theory that penalties are effective because they draw a firm’s attention to an unsafe condition. Since orders are not appealed in BC to the same degree that they are in the United States, the effects could be more immediate in BC. Finally, enforcement theories indicate that it is vital that intervention studies have clear and detailed information about the context and the intervention so that the end user may better understand the implications of the findings to inform policy. 152 What is the most appropriate statistical approach to answer the question: “Do workplace safety regulatory inspections lead to lower injury rates?”? Various methods that could be used to analyze the effectiveness of inspections were investigated. The differences in assumptions, strengths, limitations, interpretation were discussed for each method. In particular, it was necessary to consider whether the method could address the facts that the available WorkSafeBC data is count data for injuries, is longitudinal, and that the treatment of inspections is highly targeted. After examining the suitability of each analytical method and the trade-offs inherent in each approach, it was decided that fixed effects or difference-in-differences with coarsened exact matching would each be appropriate to the data and the research question. Fixed effects models could be based on matched or unmatched firms, although unmatched analyses may be required if the outcome is rare in a stratified analysis. Upon analysing the WorkSafeBC data using previously applied analytical methods, it was identified that not all the methods were appropriate. Methods cannot be replicated without justification and must be examined critically relative to the data, context and study design. In addition, it is prudent to take care in interpretation of findings of observational studies; if the assumptions of a causal model are not met, conclusions regarding causality are limited. Do workplace safety regulatory inspections lead to lower injury rates? Using a fixed effects Negative Binomial regression model combined with coarsened exact matching, it was found that inspections generally do not impact acute or short term, long-term, and fatal injuries. Inspections to appear be followed by reductions in the acute injury rate at large service firms. Inspections are the most frequently used activity and can be viewed as an expression of persuasive regulation. Penalties were too rare to investigate, but the results suggested that inspections with orders, particularly when combined with a site visit, can be effective at reducing acute injuries. However, these results were not statistically significant at a 95% confidence level. 153 In sum, the findings from the investigation of the effect of inspections on acute injuries in BC indicate that a more responsive enforcement regime, that can incorporate more penalties and consultations, might be useful. 6.3 Policy Applications of Research Findings Policy recommendations to WorkSafeBC Several policy recommendations arise from this dissertation that are relevant to WorkSafeBC. The first recommendation is that, drawing of the responsive regulation model developed and described in Chapter 2, that suggests that WorkSafeBC could broaden their enforcement toolbox. These tools could include smaller but more frequently applied fines, expanded consultation programs, or mandatory training. The finding that inspections with orders do not appear to reduce injuries significantly appears to indicate that the compliance message is not reaching the decision makers at firms in British Columbia. One lever that may deliver the message, and which is already available to the inspectorate, is a financial penalty. Previous research suggests, that higher penalties, with publicity to provide information to other firms and thus greater general deterrence, may be necessary to induce compliance. In addition, inspected firms need to be aware that there are penalties being applied for the threat of penalty to work. Over and above the threat of penalty are the ability to shut down a firm temporarily and ultimately the criminal prosecution of the company (or through the corporate veil to the executive or others, if that is deemed necessary). The key to effective responsive regulation, however, is the matching of the regulatory response to the circumstance of the firm. One enforcement tool that WorkSafeBC has is the use of consultations. These have been shown to be useful in other studies (Foley et al. 2012). Consultations or similar programs can provide increased facilitation to companies that have the motivation to improve safety but not the know-how. These may be implemented by the inspectorate, other staff from the regulatory agency, or in partnership with industry associations. Industry-wide effort may have resulting 154 systemic effects, as suggested by Weil (2008) and may be conducted along with the industry safety associations already established in British Columbia. In light of changes to the interpretation of the penalty pyramid, and in order to be able to successfully apply different policy levers to different firms according to their motivations and abilities, it may be necessary to provide additional training to the WorkSafeBC inspectorate. This training could move beyond technical safety know-how and into soft skills such as negotiation, communication, and conflict resolution. Recommendations to WorkSafeBC with reference to the 2014 Macatee Report In 2014, in response to a 2012 workplace tragedy at a sawmill at Burns Lake, the British Columbia government released an action plan to improve the inspection and investigation process in general, in addition to recommendations specific to the wood manufacturing sector. WorkSafeBC agreed to implement the recommendations that applied to that organization across the province (British Columbia Provincial Government 2014) (noted in the Final Report on the WorkSafeBC Review and Action Plan, 2016 (Macatee 2016) was that all of these changes were at least substantively implemented). Key recommendations from the Report included improvements to the methods of conducting investigations, focusing on improving dust safety sawmills in BC in general, and some changes to the structure and executive of WorkSafeBC. However, a significant part of the Report involved progressing WorkSafeBC prevention to a “world-class inspection and investigation regime”, defined in the Report, as a sustainable system, with well-understood rules for employers, and proactive compliance. Enforcement tools should be visible to effectively drive compliance and deterrence. The recommendations of the Report in concert with the conclusions in this dissertation are discussed in this section. The recommendations of the Report will be reviewed with a view to the inspection model and analysis of inspections provided earlier with attention to the potential of the recommendations to increase the responsiveness of the regulatory regime. 155 It should be noted that the very existence of the Macatee report lends legitimacy to the regulatory regime because the Report provides a well-researched evidence base for regulation. Another way legitimacy is added by this report is a recommendation that WorkSafeBC involve labour and industry in the development of regulations, by having input into WorkSafeBC regulatory priorities with significant consultation periods, as well as the means to submit ideas for amendments to the regulation. Importantly, non-unionized workers should be consulted as these workers lack the power of both industry and unions. The Report notes that world class safety regulators are respected by industry and labour and trusted by the general public. This trust is partly achieved by proportionality, clarity, consistency and transparency with a regulatory body with competent professionals. Proportionality involves providing support to companies that attempt to comply and being able to escalate to strong enforcement tools for those with poor safety records or who are reckless with safety matters. This requires a set of effective tools to allow the application of the lowest level of enforcement with the possibility of strong punishment if necessary. All the above recommendations add to legitimacy of a regulatory regime. The inspection model in Chapter 2 also notes that it is important for regulations to be technically sound. The Report included several strategies to improve regulations. As part of the recommendation to focus on anticipation and prediction of emerging trends, WorkSafeBC created a Risk Analysis Unit to focus on risks that do not align well with a claims-oriented model, that is, risks that do not show up until claims have been made. The Report also speaks to a need for inspections to be targeted efficiently and effective to capture safety infractions. One recommendation is a refocus on proactive rather than reactive inspections. In addition, the necessity of using measures of risk to prioritize inspection activities based on industry, activities, and historical safety performance is highlighted. It is also recommended that prevention officers (particularly more senior officers) inspect locations whenever there are unsafe conditions, be that during normal business hours, late night, or weekends. The Report also contains recommendations for additional resources to preventative inspections to improve effectiveness and highlights the need for training of prevention 156 personnel who are envisioned as having “full responsibility for orders, citations, and administrative penalties”. Notwithstanding this, the training proscribed is almost entirely administrative, from report writing to case management, evidence collection and data entry. This is not necessarily the type of training that would help create higher quality inspections necessary for success. Training instead could focus on improving the inspectors’ skills at choosing the right enforcement tool, given the firm and the circumstance, as discussed in Chapter 2. There are many recommendations in the Macatee Report regarding motivation of firms to become compliant, and it mostly centres on the enforcement pyramid. There is a recommendation to expand the lower levels of the consultation program and to allocate more resources to education and compliance. Publishing, or “naming and shaming” firms that are non-compliant is another low-pyramid level recommendation. To motivate firms, two additional mid-pyramid level tools are suggested in the Macatee Report. The first is an Assurance of Compliance (AOC) tool, to commit the most senior management to a written agreement to correct a violation, subject to additional measures if the agreement is not adhered to. The second new tool is the citation – a type of penalty that is applied immediately or on-the-spot, during an inspection, for certain minor OHS violations that have been clearly committed previously. These ticket-like penalties are low cost, quick, and easy to apply in comparison with other ways of achieving prevention. It is unknown how effective the AOC will be, as this type of tool has not been studied. However, the citations, being basically penalties, should be effective based on previous studies as they are of similar monetary amounts. Suggestions from the Report also deal with sanctions at the top of the regulatory pyramid, emphasizing the utility of using powers generally reserved for penalties after accident investigations as a preventative tool. The penalty is suggested to be proportional to both the severity of the offense and the employer’s size and safety history. In case of lagging progress in compliance, the officer should have an escalating range of enforcement tools available. This would include such tools as the continued use of prosecutions, and the improvement of powers 157 of injunction to address ongoing safety issues. WorkSafeBC should continue the use of administrative penalties and be able to issue them in amounts that have a deterrent effect and be able to pierce the ‘corporate veil’ and apply them to individuals within a firm. Another suggestion that should improve the effectiveness of penalties is to reduce the period during which an appeal may be made. Missing from the Report, however, are mentions of the skills required to effectively implement responsive regulation at the inspector level, such as negotiation, conflict resolution, collaboration and intuition. These are difficult skills to train, but necessary when it comes to understanding and dealing with firms with a myriad of motives. The Report provided many suggestions that offer the potential to improve the effectiveness of the prevention program at WorkSafeBC in general, and inspections specifically, that warrant future evaluation. In addition, the Report mentions the development of performance measures and assessments of the extent of worker safety awareness and safety culture at firms, the effectiveness of prevention officers and enforcement tools including the penalty pyramid. Many of the recommendations in the Report are consistent with responsive regulation mode and the implementation of these by WorkSafeBC warrant future research to evaluate their effectiveness on workplace health and safety outcomes. Broader policy recommendations Several findings from this dissertation can be used to inform policy and research in Canada and internationally. Significantly, this work adds to the evidence that on average inspections must be accompanied by a penalty to lead to a reduction in workplace injuries. Additionally, it is important for any regulatory intervention research to provide relevant context so that the results can be interpreted and applied to other jurisdictions. Such information would include the likelihood of inspection and the likelihood and amount of penalties. This would allow other regulators to gauge the general deterrence in their state, which might impact the specific deterrence that a firm experiences – those firms expecting an inspection would be better prepared, in theory, and the effect of an inspection at that firm might be 158 modified downward. The context given would ideally even range to information on the trust levels between government and the private sector generally. It is important that different types of firms be studied when examining the effect of inspections. The fact that, when stratified, the results from the services industry and large firm categories differed from the results from other categories when stratified indicated that the type of firm may relevant in identifying the most effective regulatory response. Moreover, different techniques may be required than those that were used in this study as this study had insufficient sample size to investigate more fine grained firm categories. Finally, the broader points from the model that was discussed in Chapter 2 are relevant to many workplace safety regulators. It is important to consider targeting strategies when choosing a firm to inspect and inspections should be thorough. Most importantly, the main point of responsive regulation, that it actually be responsive and not merely a progression up the penalty pyramid is applicable to a broad range of regulatory contexts. This requires a thorough knowledge of how to motivate firms and how to identify which strategy should be used for what type of firm and speaks to a need for a well-trained and professional inspectorate. Finally, the complex nature of organizations and the changing nature of work point to a need to investigate new regulatory strategies and expand on current types of self-regulation such as safety management systems. 6.4 Suggestions for Future Research In examining the data on inspections and injuries, it appears to be important to investigate whether there is a link between compliance and safety. One approach to this investigation might be a textual analysis of accident investigation reports to examine how regulations relate to injuries and which regulations are most commonly cited in investigation reports. Summaries by the inspectors of compliance, perhaps even summarizing the results of the inspection into a score, may also be useful in determining compliance levels. Another missing link is evidence that the results of the inspection make it to the ‘shop floor’. In this case, a qualitative study of the experiences of managers, supervisors, and 159 employees after an inspection, to gauge reactions and response to an inspection, would be useful. Penalties were vital to the effectiveness of inspections in Pennsylvania (Haviland, Burns, et al. 2012). However, penalties following inspections are relatively infrequent in British Columbia, and as a result, it was not possible to study their effect on inspections in the current analyses. Thus, the study of other jurisdictions in Canada where penalties are more common would be useful. In addition, as it is anticipated that WorkSafeBC will increase the number of and types penalties, the study of more recent data might permit the examination of penalties in British Columbia. Foley and colleagues (2012) found that consultations were effective in reducing injury rates in Washington State, but Hogg-Johnson and colleagues (2012) found consultations be ineffective in Ontario. However, the researchers in Ontario estimated that this could be due to firm selection issues or limited intensity or participation. A study in British Columbia of consultations that have more intensity and better targeting may be appropriate, especially using the randomized control study approach as in the Hogg-Johnson study, to allow for a smaller sample of firms to be studied more carefully. The data used in this study was of high quality. However, it would be ideal to be able to work with regulators to address methods of collecting data from inspections for more in-depth studies. For example, more precise information on forms regarding the regulations that were being violated or coding on forms for certain types of non-compliance may allow more precise research to be completed. A few simple questions might be carried over from the Safety Management Systems Audits and the answers recorded for future analysis, such as the scoring system used in Lindell’s study of United States Naval Facilities (Lindell 1997). It would be valuable to study the implemented citations and other regulatory tools recommended in the Macatee Report (Macatee 2014; 2016). This could be achieved in a straightforward manner using the study designs and estimation approaches highlighted in Chapters 4 and 5. An interrupted time series may also be an effective way to examine the effect in aggregate of the implementation of the Macatee recommendation including a potential 160 increase in the general deterrence effect on firms that are not directly receiving enforcement activity. Structured interviews with inspectors and managers at firms in British Columbia may also help to examine the environmental and structural factors that support safe practices at work. Finally, there are improvements to data that could improve future intervention studies. A key limitation of this study was the use of the derived Full Time Equivalents Variable (FTE). Research into an appropriate alternative to this variable would be useful to similar studies of inspections and could also improve most research into regulatory workplace interventions. In addition, improved geographic information that could more accurately determine the firm location that an injury could be attributed to, and the number of FTEs that could be assigned to, each location in multi-site firms. 6.5 Conclusion Inspections are an important part of the WorkSafeBC regulatory enforcement program. In this dissertation, the effect of inspections on workplace injuries in British Columbia was examined. 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(Baggs, Silverstein, and Foley 2003) WA, USA 1997-2000 8929 Fixed and non-fixed, single location business 617 visits to these firms 1-2 years 10 employees plus GEE approach to Poisson, controlled for previous claims Fixed site: claims rates declined 22.5% with enforcement vs. 7% among employers with no activity. Non-fixed: claims rates declined 12.8% for employers with enforcement activity compared to a 7.4% decline for those with no activity. 188 Reference Location Years Number of Firms in Sample Industry Represented Number of Firms with Inspections Follow up Employer size range Model Type Results (Mendeloff and Gray 2005) USA OSHA states, + national 1992-1998 16,036 Manufacturing 50,276 inspections 1-4 years Larger firms over represented Replication of Gray and Scholz, 1993 Log trans; Dependent variable is change in log of number of injuries Inspections reduce a broad range of injuries, not just those related to the cited standards. 189 Reference Location Years Number of Firms in Sample Industry Represented Number of Firms with Inspections Follow up Employer size range Model Type Results (W. Gray and Mendeloff 2002) USA 1979-1998 Federal OSHA: 1979-85: 6842 1987-91: 3118 1992-98: 80 Federal + State OSHA: 1992-1998: 1575 Manufacturing ? 4 years Larger firms over represented Replication of Gray and Scholz, 1993 Log trans; Dependent variable is change in log of number of injuries Effect of penalty inspection fell from 19% in 1979-85 to 11% in 1987-91 to 1% (not significant) in 1992-98 190 Reference Location Years Number of Firms in Sample Industry Represented Number of Firms with Inspections Follow up Employer size range Model Type Results (Haviland 1979) PA, USA 1998-2005 9150 Single facility manufacturing About 1/3? 1 year 10 employees plus Replication of Gray and Scholz, 1993 Log trans; Dependent variable is change in log of number of injuries For 20-250 employee firms, penalty inspections led to a small decline in injury rates, perhaps reversing what was found by (Gray, 2005) (Haviland et al. 2010) PA, USA 1998-2005 5,720 Single facility manufacturing firms Number of regulation specific citations ranged from 88 to 625 (note: not number of firms) 1 -2 years 20-250 employees Dependent variable is the change in Log Number of Injuries We find that inspections that imposed penalties during this year or last year were associated with significant annual reductions in injuries due to being struck by various types of objects (-0.014), being caught in objects or machinery (-0.013), and bodily exertion (-0.040). 191 Reference Location Years Number of Firms in Sample Industry Represented Number of Firms with Inspections Follow up Employer size range Model Type Results (Levine, Toffel, and Johnson 2012b) CA, USA 1996-2006 409 treatment group, 409 control Single establishment firms in high injury rate industries 409 1, 2, 3, and 4 years. Did not use firms that had been inspected within previous 2 years. 10 employees plus Randomized; Randomized inspections reduce injury rates by 9.4% up to 4 years after inspection. 192 Reference Location Years Number of Firms in Sample Industry Represented Number of Firms with Inspections Follow up Employer size range Model Type Results (Foley et al. 2012) WA, USA 1999-2008 Around 8500 per year, pooled it was 86, 314 Single location 1139 consultation only 3985 enforcement only 3127 enforcement with citation 1 year. Did not use firms that had been inspected within previous 2 years. 10 employees plus Pooled 10 separate 4-year studies; GEE approach to Poisson, controlled for size, previous claims incidence rates Claimed injury rates declined 4% in workplaces with inspections, effect was stronger when MSD claims were excluded; inspections with citations were associated with a 20% decline in non-MSD injury claims. (Hogg-Johnson et al. 2012) ON 2002-2008 3131 Manufacturing 896 inspected, 896 received consultation 1-2 years 6 employees plus Randomized, matched No significant difference found in injury rates. (Farina et al. 2016) Italy 2001-2007, inspection 2003-2005 574 Manufacturing 331 Partial Inspection, 243 Comprehensive Inspection Varies. Maximum 6 years. 10 employees plus Survival analysis: Kaplan–Meier method and Cox models Via Kaplan-Meier curves, firms with comprehensive inspection had a higher survival compared to companies with a partial inspection. The Cox model, adjusted for confounders, yields a preventive effect of comprehensive inspection vs. partial inspection for companies with 10–30 employees (hazard ratio of 0.74, p-value 0.018), but not for those with more than 30 employees. 193 Reference Location Years Number of Firms in Sample Industry Represented Number of Firms with Inspections Follow up Employer size range Model Type Results (Agnesi et al. 2016) Italy 2001-2007 4760 Manufacturing Analyses included 342 firms with Inspection after Injury and 232 firms with Programmed Inspection. 4186 reference firms. >10 employees Interrupted time series analyses Inspection after injury reduced all injuries by 24% (p=0.001) all injuries, and severe injuries by 36% (p=0.001). These reductions persisted from immediately after the inspection to 2 years after. The effects of programmed inspections were not significant. The researchers attempted to deal with regression to mean by following the firms for eight quarters before and after inspection. 194 Appendix B: Tables of Data, with specific reference to the database Table B1 Dependent and Independent Variables Analysis Variable Name Data Label Table Examples Independent Variables All, also split up by activity e.g. education vs. inspection Prevention Activity Pvact_activity_cd PVACT_ACTIVITY_DIM ER education, IR inspection, RFS Recommendation for Sanction All Date Caldr_date_surr caldr_yr_surr INSPT_ORDER_FACT, many others EMCUY_SNAPSHOT_FACT Inspections Inspection Order Inspt_activity_id matched to an inspection with inspt_seq_num INSPT_INSP_ORDR_DIM Regulations cited and injury type Regulation cited Regsu_subsection_num Regse_section_num Regty_regtype_cd Regln_parasub_id Inprg_group_surr REGLN_REGULATION_DIM INSPT_ORDER_FACT REGSU_SUBSECT_LK (just first two variables) Regulation Type WCA - Wcb Act Regulation Section Num - 70, 71, 72, 73.... 78 195 Dependent Variables Regulations cited and injury type CSA accident code acc_lvl1_cd (Made up of three hierarchical levels) ACCDT_ACC_TYP_DIM 11000 - fall to lower level, uns 11540 - fall from roof edge 31500 - struck by lightning For analysis of regulation matching injury type. All Injury rate CLAIM_CNT/ PERSON_YRS_QTY CLAIM_DIM / ECUPY_PERSON_YR_FACT Total of claims for each year/number of employees Table B2 Covariates Description Name in Database Table Name Justification Reference Found that inspector did not matter for injury prevention. Date Caldr_date_surr in OR hsfty_wite_cisit_dt OR hstfy_site_visit_dt Pvact_site_visit_dt_surr Edupr_site_visit_dt CLAIM_DT_ID hsfty_fact hsfty_activity_fact PVACT_ACTIVITY_DIM EDUPR_ACTIVITY_FACT Industry technology changes over time, so does the economy. Attitudes to safety do as well, and effect of inspections has been shown to change over time. (Geldart, Shannon, and Lohfeld 2005; W. Gray and Mendeloff 2002) 196 CLAIM_DIM Firm Size PERSON_YRS_QTY EMPLOYER CU YEAR SNAPSHOT FACT Small firms partially insulated from experience rating, under less CSR scrutiny, less PR pressure, large firms have more resources for safety, more likelihood of prior inspection, (Mendeloff et al. 2012; Foley et al. 2012) Change in employment PERSON_YRS_QTYi2- PERSON_YRS_QTYi1 Injuries may increase to the addition of less-experienced workers and in the event of a shrinking workforce, seniority-based layoffs leaving the more experienced workers behind, decreases in employment are likely to lead to fewer injuries. Thus, the change in employment is expected to be positively related to the number of injuries. Because our dependent variable is the change in the number of injuries, we need to look at the change in the change in the plant’s employment. (Mendeloff et al. 2012) 197 Industry Cu_sector_cu_cd EOC_EMP_OL_CU_DIM Influences injury rates and whether a company gets inspected, cost of compliance differs, workers that are dispersed outdoors may be harder to monitor, regulations and standards may be more relevant to the hazards in some industries than others (W. B. Gray and Shadbegian 2005; Haviland et al. 2008) Location/Region ol_insp_area_num ol_geo_loc_code ol_geo_rgn_cd OL_OP_LOC_LK In Combination with Industry, can tell us about economic conditions that the firm is experiencing Occupation occup_id CLAIM_DIM Injury source code soi_type_cd soi_lvl1_cd soi_lvl2_cd soi_lvl3_cd mppd_soi_cd srijy_id SRIJY_TYP_DIM The code that identifies a source of injury Mapped source of injury code (treats CWIS and CSA codes the same conceptually) A surrogate key that identifies a unique combination of source of injury code, 198 standard and mapped source of injury code Pvact_resps_typ_cd Has information on whether inspection was actually part of accident investigation; this ins only available for years mid-2006 on 199 Appendix C: Result Tables and Supplemental Figures, Chapter 4 Table C1 Sample Stata output from Analysis based on Haviland et al., Acute Injuries Regression results from method used in Haviland, acute injuries in year after inspection, with and without CEM Unmatched Match 230 Match 320 Match 032 (sum) inspected -0.00826** -0.0105** -0.0102** -0.00970** [-0.00889,-0.00763] [-0.0160,-0.00505] [-0.0156,-0.00472] [-0.0151,-0.00427] FTEyear1 0.00000283+ 0.000101 0.0000994 0.0000807 [-1.15e-08,0.00000568] [-0.000119,0.000321] [-0.000119,0.000318] [-0.000135,0.000296] chgchg -0.000451+ -0.00995** -0.00976** -0.00687** [-0.000921,0.0000194] [-0.0151,-0.00475] [-0.0149,-0.00460] [-0.0120,-0.00171] BASE_RT 0.000413* 0.00108 0.00164 0.00123 [0.0000700,0.000757] [-0.00119,0.00336] [-0.000622,0.00391] [-0.00103,0.00349] sector4==Agriculture -0.00251 0.0302 0.0340 0.00568 [-0.0177,0.0127] [-0.0712,0.132] [-0.0667,0.135] [-0.115,0.126] sector4==Fishing -0.00582 0.0232 0.0240 0 [-0.0273,0.0157] [-0.133,0.180] [-0.131,0.179] [0,0] sector4==Forestry -0.00576 0.0339 0.0319 0.0105 [-0.0210,0.00953] [-0.0686,0.136] [-0.0698,0.134] [-0.111,0.132] sector4==Oil & Gas -0.00687 -0.00509 0.000982 -0.0162 [-0.0226,0.00890] [-0.113,0.102] [-0.106,0.108] [-0.142,0.109] sector4==Food & Bev -0.0142+ 0.0328 0.0296 -0.000209 [-0.0301,0.00170] [-0.0734,0.139] [-0.0757,0.135] [-0.124,0.124] sector4==Metal & Non-Metal -0.0141+ 0.0366 0.0362 0.0164 [-0.0294,0.00127] [-0.0651,0.138] [-0.0648,0.137] [-0.104,0.137] sector4==Plastic Products -0.00896 0.0193 0.00603 -0.0171 [-0.0249,0.00699] [-0.0867,0.125] [-0.0992,0.111] [-0.141,0.107] sector4==Wood & paper products -0.0249** 0.0184 0.0224 -0.000306 [-0.0402,-0.00954] [-0.0833,0.120] [-0.0786,0.123] [-0.121,0.120] sector4==NEC Manufacturing -0.00934 0.0315 0.0360 0.0150 [-0.0248,0.00610] [-0.0714,0.134] [-0.0662,0.138] [-0.106,0.136] 200 sector4==General Construction -0.00222 0.0328 0.0315 0.0115 [-0.0172,0.0128] [-0.0671,0.133] [-0.0678,0.131] [-0.108,0.131] sector4==Heavy Construction 0 0 0 -0.0413 [0,0] [0,0] [0,0] [-0.193,0.111] sector4==Road Construction/Maint. 0.00363 0.0567 0.0583 0.0364 [-0.0124,0.0196] [-0.0492,0.163] [-0.0467,0.163] [-0.0876,0.160] sector4==Warehousing -0.0136 0.0368 0.0286 0.0144 [-0.0331,0.00599] [-0.0807,0.154] [-0.0880,0.145] [-0.119,0.148] sector4==Transportation -0.00234 0.0337 0.0298 0.0111 [-0.0174,0.0127] [-0.0670,0.135] [-0.0703,0.130] [-0.109,0.131] sector4==Retail -0.00160 0.0257 0.0300 0.00475 [-0.0167,0.0135] [-0.0752,0.127] [-0.0703,0.130] [-0.115,0.124] sector4==Wholesale -0.00199 0.0254 0.0237 0.00175 [-0.0173,0.0133] [-0.0765,0.127] [-0.0775,0.125] [-0.119,0.122] sector4==Public Administration 0.00276 0.0268 0.0170 0.00519 [-0.0134,0.0189] [-0.0922,0.146] [-0.101,0.135] [-0.130,0.140] sector4==Accom, food,leisure -0.00284 0.0282 0.0269 0.00509 [-0.0179,0.0123] [-0.0727,0.129] [-0.0733,0.127] [-0.115,0.125] sector4==Business Services -0.000495 0.0241 0.0270 0.00201 [-0.0157,0.0147] [-0.0781,0.126] [-0.0745,0.129] [-0.119,0.123] sector4==Professional serv -0.00119 0.0295 0.0335 0.00856 [-0.0164,0.0140] [-0.0720,0.131] [-0.0673,0.134] [-0.112,0.129] sector4==Other serv -0.00163 0.0320 0.0314 0.00521 [-0.0167,0.0134] [-0.0685,0.133] [-0.0684,0.131] [-0.114,0.125] sector4==Education 0.00303 0.0297 0.0315 0.0128 [-0.0125,0.0186] [-0.0756,0.135] [-0.0732,0.136] [-0.111,0.136] sector4==Health Care 0.00116 0.0535 0.0495 0.0152 [-0.0140,0.0163] [-0.0490,0.156] [-0.0523,0.151] [-0.106,0.136] sector4==Utilities -0.00202 0.0134 0.0357 0.00185 [-0.0192,0.0152] [-0.107,0.134] [-0.0841,0.155] [-0.135,0.138] year_date==2005 0 0 0.0369** 0 201 [0,0] [0,0] [0.0192,0.0545] [0,0] year_date==2006 -0.00290** -0.0117 0.0171* -0.0167+ [-0.00462,-0.00118] [-0.0288,0.00533] [0.00227,0.0320] [-0.0336,0.000213] year_date==2007 -0.00620** -0.0100 0.0292** -0.00370 [-0.00791,-0.00449] [-0.0265,0.00652] [0.0151,0.0433] [-0.0201,0.0127] year_date==2008 -0.0186** -0.0122 0.0224** -0.0123 [-0.0203,-0.0168] [-0.0285,0.00407] [0.00879,0.0361] [-0.0284,0.00391] year_date==2009 -0.0183** -0.0197* 0.00848 -0.0296** [-0.0200,-0.0166] [-0.0358,-0.00352] [-0.00491,0.0219] [-0.0456,-0.0136] year_date==2010 -0.00389** -0.00452 0.0295** -0.00852 [-0.00559,-0.00220] [-0.0206,0.0115] [0.0162,0.0427] [-0.0244,0.00739] year_date==2011 -0.00247** -0.0117 0.0229** -0.00799 [-0.00416,-0.000785] [-0.0276,0.00425] [0.00975,0.0361] [-0.0237,0.00777] year_date==2012 -0.00468** -0.0371** 0 -0.0409** [-0.00636,-0.00299] [-0.0549,-0.0193] [0,0] [-0.0585,-0.0232] Constant 0.00786 -0.0150 -0.0505 0.00902 [-0.00732,0.0230] [-0.117,0.0868] [-0.151,0.0500] [-0.111,0.129] Observations 1208029 29176 29171 29167 95% confidence intervals in brackets + p < 0.10, * p < 0.05, ** p < 0.01 202 Table C2 Sample Stata output from Analysis based on Foley et al., Acute Injuries Regression results from method used in Foley, acute injuries in year after inspection, with and without CEM Unmatched Match 230 Match 320 Match 032 new_insp_1year_prev 1.457 1.243** 1.215** 1.241** [0.837,2.536] [1.110,1.392] [1.085,1.360] [1.110,1.388] year=2005 1 1 1 1 [1,1] [1,1] [1,1] [1,1] year=2006 1.032 1.209 1.076 1.215 [0.924,1.153] [0.857,1.708] [0.782,1.480] [0.884,1.670] year=2007 1.236** 1.254 1.078 1.126 [1.110,1.376] [0.933,1.686] [0.819,1.417] [0.858,1.477] year=2008 1.451** 1.373+ 1.265 1.268 [1.306,1.613] [1.000,1.886] [0.947,1.690] [0.943,1.705] year=2009 1.383** 1.144 1.059 0.991 [1.240,1.542] [0.836,1.567] [0.795,1.410] [0.738,1.330] year=2010 1.329** 1.137 0.974 1.001 [1.192,1.480] [0.825,1.568] [0.725,1.308] [0.741,1.352] year=2011 1.252** 1.099 0.992 0.996 [1.125,1.394] [0.788,1.533] [0.731,1.347] [0.730,1.358] year=2012 1.384** 1.060 1.015 1.044 [1.240,1.545] [0.753,1.493] [0.740,1.391] [0.759,1.436] Primary Resources 1 1 1 1 [1,1] [1,1] [1,1] [1,1] Manufacturing 2.085** 1.679** 1.512** 1.717** [1.690,2.573] [1.223,2.305] [1.111,2.058] [1.259,2.341] 203 Construction 1.401** 1.330* 1.280+ 1.315* [1.169,1.680] [1.006,1.758] [0.975,1.682] [1.001,1.727] Transportation & Warehousing 1.006 1.120 1.102 1.122 [0.830,1.220] [0.795,1.578] [0.789,1.541] [0.800,1.575] Trade 1.188 0.966 0.808 0.800 [0.954,1.480] [0.690,1.352] [0.579,1.126] [0.571,1.121] Public Sector 1.484 1.667 0.825 0.937 [0.881,2.501] [0.709,3.922] [0.249,2.735] [0.287,3.054] Service Sector 1.129 0.996 0.949 0.942 [0.915,1.393] [0.733,1.354] [0.702,1.283] [0.696,1.275] FTEyear1 0.994** 0.994** 0.994** 0.993** [0.992,0.996] [0.992,0.997] [0.991,0.996] [0.991,0.996] BASE_RT 1.490** 1.244** 1.223** 1.213** [1.454,1.527] [1.208,1.280] [1.188,1.259] [1.177,1.250] Observations 365561 20190 20291 20285 Exponentiated coefficients; 95% confidence intervals in brackets + p < 0.10, * p < 0.05, ** p < 0.01 204 Table C3 Sample Stata output from Analysis based on Levine et al. article Regression results from matched fixed effects method used in Levine, acute injuries in year after inspection, with and without CEM, various matches Match 230 Match 320 Match 032 Unmatched (sum) acute new_insp_1year_prev 1.156* 1.031 1.066 1.033 [1.022,1.309] [0.911,1.166] [0.941,1.207] [0.942,1.132] year=2005 1 1 1 1 [1,1] [1,1] [1,1] [1,1] year=2006 1.231 1.362+ 1.172 1.075 [0.888,1.706] [0.971,1.909] [0.850,1.615] [0.977,1.183] year=2007 0.872 1.110 0.898 1.030 [0.675,1.125] [0.853,1.444] [0.702,1.148] [0.939,1.131] year=2008 1.078 1.238 1.050 1.070 [0.779,1.492] [0.884,1.734] [0.765,1.443] [0.972,1.178] year=2009 0.698* 0.985 0.751+ 0.962 [0.513,0.951] [0.715,1.356] [0.555,1.016] [0.872,1.061] year=2010 0.712+ 0.973 0.820 0.931 [0.505,1.004] [0.683,1.386] [0.585,1.149] [0.844,1.028] year=2011 0.688* 1.029 0.734+ 0.917+ [0.493,0.960] [0.731,1.447] [0.530,1.018] [0.830,1.013] year=2012 0.645* 0.981 0.791 0.993 [0.435,0.954] [0.658,1.462] [0.538,1.164] [0.896,1.100] FTEyear1 1.001 1.005 1.001 1.001 [0.992,1.010] [0.996,1.015] [0.992,1.011] [0.999,1.004] BASE_RT 1.011 1.017 1.009 1.056** [0.929,1.101] [0.933,1.108] [0.928,1.097] [1.013,1.101] Observations 4046 4072 4066 40941 Exponentiated coefficients; 95% confidence intervals in brackets + p < 0.10, * p < 0.05, ** p < 0.01 205 Table C4 Sample Stata output from GEE method with Difference-in-differences Regression results from method used in Haviland, acute injuries in year after inspection, with and without CEM, various k2k matches Match 320 Match 230 Match 032 treatment=0 1 1 1 [1,1] [1,1] [1,1] treatment=1 1.522** 1.456** 1.446** [1.335,1.734] [1.278,1.657] [1.270,1.647] post=0 1 1 1 [1,1] [1,1] [1,1] post=1 0.965 0.850* 0.985 [0.827,1.125] [0.727,0.994] [0.849,1.142] treatment=0 # post=0 1 1 1 [1,1] [1,1] [1,1] treatment=0 # post=1 1 1 1 [1,1] [1,1] [1,1] treatment=1 # post=0 1 1 1 [1,1] [1,1] [1,1] treatment=1 # post=1 0.982 1.150 0.965 [0.828,1.165] [0.969,1.365] [0.817,1.141] BASE_RT 1.153** 1.141** 1.141** [1.123,1.184] [1.111,1.171] [1.112,1.171] year=2004 1 1 1 [1,1] [1,1] [1,1] year=2005 1.213 1.209 1.274 [0.878,1.675] [0.883,1.656] [0.939,1.727] year=2006 1.348* 1.332* 1.284+ [1.031,1.762] [1.016,1.745] [0.989,1.667] 206 year=2007 1.469** 1.311+ 1.337* [1.122,1.922] [0.997,1.723] [1.025,1.745] year=2008 1.601** 1.554** 1.438** [1.227,2.087] [1.190,2.030] [1.110,1.864] year=2009 1.320* 1.215 1.204 [1.012,1.722] [0.928,1.591] [0.927,1.564] year=2010 1.378* 1.241 1.264+ [1.053,1.803] [0.944,1.631] [0.969,1.648] year=2011 1.350* 1.205 1.174 [1.036,1.758] [0.921,1.575] [0.904,1.523] year=2012 1.507** 1.370* 1.365* [1.118,2.030] [1.015,1.848] [1.023,1.822] year=2013 1.349* 1.192 1.305+ [1.010,1.803] [0.887,1.600] [0.981,1.736] FTEyear1 0.997* 0.996** 0.997** [0.995,0.999] [0.994,0.998] [0.995,0.999] Agriculture 1 1 1 [1,1] [1,1] [1,1] Fishing 1.028 0.815 1.065 [0.196,5.387] [0.138,4.802] [0.196,5.800] Forestry 0.734 0.855 0.898 [0.477,1.128] [0.565,1.295] [0.582,1.387] Oil & Gas 1.495 1.311 1.349 [0.877,2.549] [0.704,2.438] [0.724,2.516] Food & Bev 1.816* 2.292** 2.083** [1.068,3.089] [1.408,3.731] [1.297,3.344] Metal & Non-Metal 1.778** 2.200** 2.237** [1.274,2.482] [1.592,3.039] [1.601,3.126] 207 Plastic Products 0.766 0.843 0.799 [0.414,1.416] [0.435,1.634] [0.426,1.497] Wood & paper products 2.035** 2.278** 2.652** [1.500,2.761] [1.691,3.069] [1.951,3.604] NEC Manufacturing 0.973 1.062 1.000 [0.647,1.462] [0.711,1.585] [0.655,1.527] General Construction 1.270+ 1.366* 1.496** [0.972,1.658] [1.052,1.775] [1.139,1.966] Heavy Construction 1.832 2.101+ 1.176 [0.638,5.264] [0.883,5.000] [0.357,3.870] Road Construction/Maint. 0.810 0.944 1.058 [0.475,1.381] [0.566,1.575] [0.636,1.759] Warehousing 1.184 1.105 1.302 [0.663,2.116] [0.606,2.013] [0.721,2.349] Transportation 1.185 1.211 1.328+ [0.867,1.621] [0.890,1.648] [0.966,1.826] Retail 0.753+ 0.753+ 0.864 [0.550,1.031] [0.551,1.029] [0.625,1.194] Wholesale 0.572** 0.547** 0.672+ [0.384,0.852] [0.364,0.820] [0.439,1.029] Public Administration 1.063 0.819 0.806 [0.514,2.199] [0.327,2.049] [0.307,2.113] Accom, food,leisure 0.848 0.943 1.046 [0.634,1.134] [0.707,1.258] [0.777,1.410] 208 Business Services 0.189** 0.143** 0.112** [0.0943,0.380] [0.0776,0.265] [0.0559,0.225] Professional serv 0.245** 0.271** 0.275** [0.146,0.413] [0.163,0.451] [0.162,0.468] Other serv 1.212 1.242 1.388* [0.910,1.614] [0.936,1.649] [1.037,1.857] Education 0.464 0.570 0.508 [0.180,1.200] [0.221,1.469] [0.188,1.376] Health Care 0.879 0.926 0.954 [0.598,1.293] [0.624,1.376] [0.640,1.421] Utilities 0.119* 0.139* 0.263* [0.0176,0.802] [0.0215,0.896] [0.0693,0.998] Observations 33170 33160 33234 Exponentiated coefficients; 95% confidence intervals in brackets + p < 0.10, * p < 0.05, ** p < 0.01 209 Appendix D: Example Result Tables and Supplementary Materials, Chapter 5 Table D1 Results of Diagnostic Tests including Akaike’s Information Criterion and Likelihood Ratio Test Model Follow upO utcome Definition AIC BIC Likelihood Ratio ResultNo Covariates 33732.66 33856.34Add FTE 33720.63 33853.83 ✔Add Base Rate and FTE 33722.29 33865.01No Covariates 239675.5 239833.3Add FTE 239663.8 239833.7 ✔Add Base Rate and FTE 239658.5 239840.6No Covariates 17534.83 17652.51Add FTE 17532.76 17659.5 ✔Add Base Rate and FTE 17534.33 17670.12No Covariates 122080.5 122232.2Add FTE 122073.5 122236.9 ✔Add Base Rate and FTE 122072 122247No Covariates 8807.111 8916.179Add FTE 8806.376 8923.235Add Base Rate and FTE 8805.561 8930.211No Covariates 67687.68 67832.44Add FTE 67683.6 67838.69 ✔Add Base Rate and FTE 67685.42 67850.85No Covariates 4426.433 4529.866Add FTE 4427.937 4538.758Add Base Rate and FTE 4428.586 4546.795No Covariates 34814.12 34953.85 ✔Add FTE 34810.46 34960.17Add Base Rate and FTE 34812.17 34971.86Unmatched 2nd Year Acute0.01740.5904Unmatched 2nd Year SLF0.01360.6726Matched 2nd Year Acute0.48130.2451Unmatched 1 Year Acute0.00270.0603Matched (320)2nd Year SLF0.09820.0934Unmatched 1 Year SLF0.00020.007Matched 1 Year Acute0.04370.5127Likelihood Ratio P-valueMatched (320)1 Year SLF0.00020.5631210 Table D 2 Sample Stata Output, Rate Ratios, acute injuries in 12 months after inspection, using fixed effects NB, comparing various k2k matches, CEM Match 320 Match 230 Match 032 Unmatched (sum) acute follow_up_1year 0.951 0.997 0.957 1.000 [0.858,1.054] [0.900,1.106] [0.863,1.061] [0.926,1.080] year=2005 1 1 1 1 [1,1] [1,1] [1,1] [1,1] year=2006 0.925 1.005 0.952 1.048 [0.732,1.168] [0.795,1.272] [0.759,1.195] [0.959,1.146] year=2007 0.991 1.034 1.021 1.003 [0.772,1.271] [0.806,1.327] [0.802,1.300] [0.918,1.096] year=2008 0.982 0.977 0.919 1.044 [0.757,1.273] [0.754,1.265] [0.714,1.183] [0.956,1.140] year=2009 0.811 0.700** 0.741* 0.938 [0.621,1.061] [0.535,0.915] [0.572,0.961] [0.858,1.026] year=2010 0.746* 0.685** 0.698** 0.893* [0.567,0.982] [0.522,0.900] [0.535,0.911] [0.816,0.978] year=2011 0.809 0.695* 0.718* 0.908* [0.611,1.071] [0.525,0.920] [0.546,0.943] [0.830,0.994] year=2012 0.888 0.804 0.809 0.994 [0.656,1.203] [0.595,1.086] [0.601,1.090] [0.905,1.092] year=2013 0.918 0.765 0.825 0.909+ [0.648,1.300] [0.540,1.086] [0.585,1.162] [0.824,1.002] lnFTEyear1 0.796** 0.785** 0.763** 0.910** [0.672,0.942] [0.667,0.923] [0.648,0.899] [0.852,0.972] Observations 52406 52484 51398 611022 Exponentiated coefficients; 95% confidence intervals in brackets + p < 0.10, * p < 0.05, ** p < 0.01
Thesis/Dissertation
eng
Occupational and Environmental Hygiene
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Understanding regulatory workplace safety inspections in British Columbia, Canada : theory and evaluation
Text