{"http:\/\/dx.doi.org\/10.14288\/1.0102364":{"http:\/\/vivoweb.org\/ontology\/core#departmentOrSchool":[{"value":"Business, Sauder School of","type":"literal","lang":"en"}],"http:\/\/www.europeana.eu\/schemas\/edm\/dataProvider":[{"value":"DSpace","type":"literal","lang":"en"}],"https:\/\/open.library.ubc.ca\/terms#degreeCampus":[{"value":"UBCV","type":"literal","lang":"en"}],"http:\/\/purl.org\/dc\/terms\/creator":[{"value":"Thong, Gregory Tin Sin","type":"literal","lang":"en"}],"http:\/\/purl.org\/dc\/terms\/issued":[{"value":"2011-07-22T23:11:39Z","type":"literal","lang":"en"},{"value":"1968","type":"literal","lang":"en"}],"http:\/\/vivoweb.org\/ontology\/core#relatedDegree":[{"value":"Master of Science in Business - MScB","type":"literal","lang":"en"}],"https:\/\/open.library.ubc.ca\/terms#degreeGrantor":[{"value":"University of British Columbia","type":"literal","lang":"en"}],"http:\/\/purl.org\/dc\/terms\/description":[{"value":"One of the consequences arising out of the increasing use of automation in industry has been considered to be the effect of this on the trade union's ability to stage a successful strike. In this study, the null hypothesis is tested to determine whether there is a relationship between the level of automation in industry and the propensity to strike in certain industry groups in the United States.\r\nData from two periods is analyzed; Period 1 between 1951 and 1959, and Period 2 between 1960 and 1965. The measurement of the level of automation in industry is made on the assumption that the level of automation is equivalent\r\nto the level of application of process control employing\r\nelectronic computers in these industries. The measurement of propensity to strike is determined by comparing the ranking of the man-days idle due to work stoppages with the ranking of the annual average production worker employment levels among the industries. Secondary data has been adapted for use in the test of the null hypothesis. The data has been extracted mainly from the trade journal, Control Engineering, published by the McGraw-Hill Book Company, and from Analysis of Work Stoppages and the Employment and Earnings Statistics for the United States, published by the United States, Department of Labor, Bureau of Labor Statistics. The results indicated that at the level of significance,\r\na = .05, the test on the null hypothesis indicated that there is no relationship between the level of automation in industry and the propensity to strike for Period 1. For Period 2, the test indicated that there is a relationship between the two variables, under the same level of significance. Further analysis of the results for Period 2 indicated that industries that have achieved or maintained a high or low level of automation are associated with high propensity to strike. The high propensity to strike in high level of automation\r\nindustries tend to be caused by a small number of strikes of long duration on the average. On the other hand, industries that have maintained a low level of automation have been associated with high propensity to strike in general as a result of a large number of strikes of short duration on the average. A model has been developed to explain the relationship between the two variables. It is concluded that the results of the study, due to the short time spans of the periods studied, may only indicate the short-run or transitory trend. It is possible that these results will be dissimilar to those derived from a long-run study, when equilibrium has set in.","type":"literal","lang":"en"}],"http:\/\/www.europeana.eu\/schemas\/edm\/aggregatedCHO":[{"value":"https:\/\/circle.library.ubc.ca\/rest\/handle\/2429\/36275?expand=metadata","type":"literal","lang":"en"}],"http:\/\/www.w3.org\/2009\/08\/skos-reference\/skos.html#note":[{"value":"\"\"LEVEL 0? AUTOMATION IN INDUSTRY AND THE PROPENSITY TO STRIKE IN CERTAIN INDUSTRIES IN THE UNITED STATES \u2022by GREGORY TIN SIN THONG B.E., U n i v e r s i t y of Malaya, 1961. A.M.I.E. ( M a l a y s i a ) , A.M.I.C.E. A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF'BUSINESS ADMINISTRATION i n the Department of Commerce and Business A d m i n i s t r a t i o n We accept t h i s t h e s i s as conforming to the r e q u i r e d standard THE UNIVERSITY OF BRITISH COLUMBIA June, 1968 In p re sen t i ng t h i s t he s i s in p a r t i a l f u l f i l m e n t of the requirements f o r an advanced degree at the U n i v e r s i t y of B r i t i s h Columbia, I agree that the L i b r a r y s h a l l make i t f r e e l y a v a i l a b l e f o r re fe rence and Study. I f u r t h e r agree that permiss ion f o r ex ten s i ve copying of t h i s t h e s i s f o r s c h o l a r l y purposes may be granted by the Head of my Department or by hlis r e p r e s e n t a t i v e s . It i s understood that copying or p u b l i c a t i o n of t h i s t he s i s f o r f i n a n c i a l gain s h a l l not be a l lowed wi thout my w r i t t e n pe rmi s s i on . Department of Commerce and Business A d m i n i s t r a t i o n The U n i v e r s i t y of B r i t i s h Columbia Vancouver 8, Canada i i . ABSTRACT One of the consequences a r i s i n g out of the i n c r e a s i n g use of automation i n i n d u s t r y has been considered to be the e f f e c t of t h i s on the trade union's a b i l i t y to stage a s u c c e s s f u l s t r i k e . I n t h i s study, the n u l l hypothesis i s t e s t e d to determine whether there i s a r e l a t i o n s h i p between the l e v e l of automation i n i n d u s t r y and the p r o p e n s i t y to s t r i k e i n c e r t a i n i n d u s t r y groups i n the U n i t e d States. Data from two periods i s analysed; P e r i o d 1 between 1951 and 1959, and P e r i o d 2 between i 9 6 0 and 1965. The measurement of the l e v e l of automation i n i n d u s t r y i s made on' the assumption that the l e v e l of automation i s equiv-a l e n t to the l e v e l of a p p l i c a t i o n of process c o n t r o l employ-i n g e l e c t r o n i c computers i n these i n d u s t r i e s . The measurement of p r o p e n s i t y to s t r i k e i s determined by comparing the ranking of the man-days i d l e due to work stoppages w i t h the ranking-of the annual average p r o d u c t i o n worker employment l e v e l s among the i n d u s t r i e s . Secondary data has been adapted f o r use i n the t e s t of the n u l l hypothesis. The data has been e x t r a c t e d mainly from the trade j o u r n a l , C o n t r o l Engineering, p u b l i s h e d by the McGraw-Hill Book Company, and from A n a l y s i s of Work  Stoppages and the Employment and Earnings S t a t i s t i c s f o r the  U n i t e d S t a t e s , p u b l i s h e d by the U n i t e d S t a t e s , Department of Labor, Bureau of Labor S t a t i s t i c s . i l l . The r e s u l t s i n d i c a t e d that at the l e v e l of s i g n i f -i c a n c e , a = .05 > the t e s t on the n u l l hypothesis i n d i c a t e d that there i s no r e l a t i o n s h i p between the l e v e l of automation i n i n d u s t r y and the p r o p e n s i t y to s t r i k e f o r P e r i o d 1. For Pe r i o d 2, the t e s t i n d i c a t e d that there i s a r e l a t i o n s h i p between the two v a r i a b l e s , under the same l e v e l of s i g n i f i c a n c e . F u r t h e r a n a l y s i s of the r e s u l t s f o r P e r i o d 2 i n d i c a t e d that i n d u s t r i e s that have achieved or maintained a high or low l e v e l of automation are a s s o c i a t e d w i t h h i g h p r o p e n s i t y to s t r i k e . The h i g h p r o p e n s i t y to s t r i k e i n h i g h l e v e l of auto-mation i n d u s t r i e s tend to be caused by a small number of s t r i k e s of l o n g d u r a t i o n on the average. On the other hand, i n d u s t r i e s that have maintained a low l e v e l of automation have been a s s o c i a t e d w i t h h i g h p r o p e n s i t y to s t r i k e i n general as a r e s u l t of a l a r g e number of s t r i k e s of short d u r a t i o n on the average. A model has been developed to e x p l a i n the r e l a t i o n s h i p between the two v a r i a b l e s . I t i s concluded that the r e s u l t s of the study, due to the short time spans of the perio d s s t u d i e d , may only i n d i c a t e the. short-run or t r a n s i t o r y trend. I t i s p o s s i b l e that these r e s u l t s w i l l be d i s s i m i l a r \u2022 to those derived from a long-run study, when e q u i l i b r i u m has set i n . i v . TABLE OF CONTENTS CHAPTER Page I . INTRODUCTION 1 Scope of the Study 1 Statement of the Hypothesis 3 D e r i v a t i o n of the Word \"Automation\" 3 D e f i n i t i o n of Automation 4 D e f i n i t i o n of Other Terms Used i n The Study 11 I I . LITERATURE AND PREVIOUS RESEARCH 15 The Part Played by S t r i k e s i n C o l l e c t i v e B a r g a i n i n g 15 I n d i c a t i o n of the Waning Povrer Of the Union to S t r i k e i n C e r t a i n I n d u s t r i e s due to Automation 2 0 Some D e t a i l s of S t r i k e s A f f e c t e d by Automation 2 3 Research i n the Pr o p e n s i t y to S t r i k e 3 0 I I I . COLLECTION OP DATA 39 L e v e l of Automation i n Industry 39 The Pr o p e n s i t y to S t r i k e 42 Data, Used and the Method of C o l l e c t i o n 4 3 I n d u s t r i e s Chosen f o r the Study 55 V . CHAPTER Page IV. TESTING OF HYPOTHESIS 60 Theory of the A n a l y s i s of r by k Contingency Table 60 Chi-square 63 Degrees of Freedom 65 The C r i t e r i o n f o r x 68 The Contingency C o e f f i c i e n t , C 70 A n a l y s i s of the.Data 72 Computation 98 V. INTERPRETATION OF THE RESULTS 105 The Results 103 Factors Related to the L e v e l of Automation i n Industry That Tended to Increase the Duration of S t r i k e s 108 Comparing Some of the Results With the General P a t t e r n of S t r i k e P r o p e n s i t i e s 113 Development of a Model 115 VI. CONCLUSION 118 BIBLIOGRAPHY 121 APPENDIX 131 v i . LIST OF TABLES TABLE Page I Names of some major group and sub-group i n d u s t r i e s from two sources I I r by k Contingency Table I l i a Computation of L e v e l of Automation i n Industry - P e r i o d 1 I I l b Computation of L e v e l of Automation i n Industry Using A l t e r n a t i v e Cutoff P o i n t - P e r i o d 1 I I I c Computation of L e v e l of Automation i n Industry - P e r i o d 2 TV I r o n and S t e e l V Nonferrous Metals VI Autos, Trucks and P a r t s ; Aerospace, and Other T r a n s p o r t a t i o n Equipment VI I F a b r i c a t e d Metals and Instruments V i l l a Production Workers Employed i n Industry During Year - P e r i o d 1 V I I l b Production Workers Employed i n Industry During Year - P e r i o d 2 .IXa Work Stoppages Occurring i n Industry During Year - P e r i o d 1 IXb Work Stoppages Occurring i n Industry Daring Year - P e r i o d 2 Xa' Ranking of Production Workers and Work Stoppages Among I n d u s t r i e s - P e r i o d 1 Xb Ranking of Production Workers and- Work Stoppages Among I n d u s t r i e s - P e r i o d 2 58 62 74 76 77 79 80 81 82 84 85 86 87 89 90 v i i . TABLE XIa Frequency of |P-S| - P e r i o d 1 Xlb Frequency of | P - S | - P e r i o d 2 X l l a L e v e l of Automation i n Industry Against Propens i t y to S t r i k e - P e r i o d 1 XIITD L e v e l of Automation i n Industry ( a l t . c u t o f f p o i n t ) Aga.inst P r o p e n s i t y to S t r i k e - P e r i o d 1 XlTc L e v e l of Automation i n Industry Against Pr o p e n s i t y to S t r i k e - P e r i o d 2 X H I a L e v e l of Automation i n Industry Against Propensity to S t r i k e Contingency Table -P e r i o d 1 X H I b . L e v e l of Automation i n Industry Using A l t e r n a t i v e C u t o f f P o i n t s Against Pr o p e n s i t y to S t r i k e Contingency Table -P e r i o d 1 X I I I c L e v e l of Automation i n Industry Against Pr o p e n s i t y ot S t r i k e Contingency Table -P e r i o d 2 XIV E f f e c t of E q u a l i z i n g the Column Total s XV C e l l Values of Average number of Work Stoppages (Upper L e f t H a l f ) and Average Duration of S t r i k e s (Lower Right H a l f ) - P e r i o d 2 XVI I n d i c a t i n g E f f e c t i v e n e s s of Nonproduction Workers During S t r i k e s i n the Petroleum Industry - P e r i o d 2 XVII Comparison w i t h Some Common Res u l t s w i t h the General P a t t e r n of S t r i k e P r o p e n s i t i e s X V I I I Industry and Standard I n d u s t r i a l C l a s s i f i c a t i o n Code XIX Number of Work Stoppages by Major Group and Sub-Group I n d u s t r i e s - P e r i o d 2 XX Average Duration of S t r i k e s i n Industry -P e r i o d 2 Page 91 92 95 96 97 9 9 1 0 0 1 0 1 io4 1 0 5 1 1 1 1 1 4 132 1 3 4 135 v i i i . TABLE Page XXI Computation of Average Number of Work Stoppages f o r Each C e l l - P e r i o d 2 \u00b1J>6 XXII Computation of Average Duration of S t r i k e s f o r Each C e l l - P e r i o d 2 137 X X I I I R a t i o of Nonproduction Workers to T o t a l Employment 138 XXIV Table of C r i t i c a l Values of Chi-square 139 i x . LIST OF ILLUSTRATIONS FIGURE Page 1 . A Chi-square D i s t r i b u t i o n 6 6 2 . L e v e l of Automation i n Industry -Propensi t y to S t r i k e Model 1 1 6 X. ACKNOWLEDGMENT to P r o f e s s o r Noel A. H a l l f o r h i s k i n d d i r e c t i o n and advice i n the w r i t i n g of t h i s t h e s i s . CHAPTER I INTRODUCTION 1. Scope of the Study: During recent years., some l i t e r a t u r e has been w r i t t e n , on automation which made comments that w i t h i n c r e a s i n g automation., the s t r i k e weapon of organized l a b o r might be d e c l i n i n g i n e f f e c t i v e n e s s and might be made obsolete. Reference\"1\" has been made i n the l i t e r a t u r e to c e r t a i n h i g h l y automated i n d u s t r i e s where s t r i k e s had taken p l a c e w i t h the unions which i n i t i a t e d the s t r i k e s being unable to achieve t h e i r o b j e c t i v e s . - I The l i t e r a t u r e has not i n d i c a t e d the f a c t that any o b j e c t i v e general study has been made to enable the authors to s u b s t a n t i a t e these comments3 except through observations. The f o l l o w i n g questions seemed to be l e f t unanswered: (a) Is there a r e l a t i o n s h i p between the l e v e l of automation i n i n d u s t r y and the pr o p e n s i t y to s t r i k e ? (b) I f there i s a r e l a t i o n s h i p 3 what k i n d of r e l a t i o n s h i p i s i t ? (c) What are the p o s s i b l e v a r i a b l e s that may a f f e c t t h i s r e l a t i o n s h i p ? 1. The d e t a i l s of t h i s l i t e r a t u r e w i l l be unfolded i n Chapter I I . 2. I t i s proposed i n t h i s study to make an attempt to provide answers to these questions. The study w i l l be con-f i n e d to 15 major i n d u s t r y groups i n the Un i t e d States - 8 on manufacturing of durable goods, 6 on manufacturing of non-durable goods and one on mining. Other major i n d u s t r y groups have been excluded due to r e s t r i c t i o n s imposed by the secondary data used i n the study and by the sources from which the data has been e x t r a c t e d , mainly from a trade j o u r n a l , C o n t r o l Engineering, and from p u b l i c a t i o n s of the United States Department of Labor, Bureau of Labor S t a t i s t i c s , B u l l e t i n s on: (a) A n a l y s i s of Work Stoppages (b) Employment and Earning S t a t i s t i c s f o r the United States. The study i s c a r r i e d out f o r two time p e r i o d s , P e r i o d 1, between 1.951 arid 1959 and, P e r i o d 2, between i 9 6 0 and 1965. The year, 1951., has been chosen as the s t a r t i n g p o i n t f o r P e r i o d 1 because the e l e c t r o n i c computer was f i r s t p used commercially i n i n d u s t r y f o r data p r o c e s s i n g i n 1951 . In 1959 s t r i k e s that had been f i r s t reported i n the Business  Week and the U.S. News and World Report to have proved i n e f f e c t i v e i n the o i l r e f i n i n g i n d u s t r y , were i n i t i a t e d . P e r i o d 2 has been chosen as the p e r i o d when the l e v e l of auto-mation might have a profound e f f e c t on the outcome of the s t r i k e . 2. United S t a t e s , Department of Labor, Bureau of Labor S t a t i s t i c s , T echnological Trends i n Major American I n d u s t r i e s , B u l l e t i n No. 147-4, Feb. 19bo, p. 3 . 3. 2. Statement of the Hypothesis: The hypothesis can he s t a t e d as the n u l l hypothesis, H Q , and the a l t e r n a t i v e hypothesis, H^ . N u l l Hypothesis, H Q : There i s no r e l a t i o n s h i p between the l e v e l of automation i n i n d u s t r y and the p r o p e n s i t y to s t r i k e i n P e r i o d 1 and P e r i o d 2. A l t e r n a t i v e Hypothesis, H^ : There i s a r e l a t i o n s h i p between the l e v e l of automation i n i n d u s t r y and the p r o p e n s i t y to s t r i k e i n P e r i o d 1 and P e r i o d 2. I t i s proposed to t e s t the n u l l hypothesis, H Q , by u s i n g the nonparametric s t a t i s t i c a l t e s t method f o r the t e s t i n g of s i g n i f i c a n c e and the c o r r e l a t i o n of q u a l i t a t i v e data. \u2022 The chi-square t e s t and the contingency c o e f f i c i e n t t e s t w i l l be used. The l e v e l of s i g n i f i c a n c e assumed to be s u f f i c i e n t i n the presence of secondary data used i s accepted as a.= .05 . J. D e r i v a t i o n of the word \"automation\": In l a t e 19^6, the word \"automation\" was created at a s t a f f meeting by Delmar S. Harder, a mechanical engineer. He was h o l d i n g the p o s i t i o n then of V i c e P r e s i d e n t of Manufacturing i n the Ford Motor Company . The word f i r s t appeared i n p r i n t i n the McGraw-Hill metalworking j o u r n a l , the American M a c h i n i s t , i n 3. James B r i g h t , Automation and Management, (Boston: D i v i s i o n ..of Research, Graduate School of Business A d m i n i s t r a t i o n , Harvard U n i v e r s i t y , 1958) . 4. the October 21 , 1948 i s s u e . Another claimant to the authorship of the word \"automation\" was John Diebold. He mentioned that h i s d e r i v -a t i o n of the word was made independently of Delmar S. Harder. During the w r i t i n g of the Harvard r e p o r t , Making the Automatic  Factory a R e a l i t y , i n the f a l l of 1950 , he had used the word automization. F i n d i n g the word automization awkward and a b i t d i f f i c u l t to s p e l l , he had i t shortened to automation 0. John Diebold has been c r e d i t e d w i t h having p u b l i s h e d the f i r s t book on automation. 4. D e f i n i t i o n of Automation: R e f e r r i n g to the m a j o r i t y of l i t e r a t u r e on the t o p i c of automation, one would o f t e n f i n d the f o l l o w i n g question being asked, \"What i s Automation?\" Why i s i t necessary to de f i n e automation i n any book on t h i s subject? Since the word was created i n 1946, there appeared a whole s e r i e s of numerous and v a r i e d meanings f o r automation. In e f f e c t , these d i v e r s e d e f i n i t i o n s of automation have generated a v i r t u a l \" j u n g l e \" of d e f i n i t i o n s f o r the word. The maze has been such that i t i s necessary f o r an author to define the l i m i t s w i t h i n which he i s d i s c u s s i n g the t o p i c . One of the reasons a t t r i b u t e d to t h i s confusion was that the 4. American M a c h i n i s t , \"What i s Automation?\" V o l . 101, No. 22, Oct. 21 , 1957, p. 169-5- Wilbur Cross, John Diebold, Breaking the Confines of the P o s s i b l e , (New York: Jajnes H. Heineman, Inc., 1965) , p. 65. 6. John Diebold, Automation, The Advent of the Automatic Factory, (New York: D. Van Nostrand Company, Inc., 1952), p. i x . 5. technology and processes of automation had e x i s t e d even before the word was created. Feople from various d i s c i p l i n e s , such as s c i e n t i s t s , engineers, union spokesmen, t e c h n i c i a n s , p r o f e s s o r s and i n d u s t r i a l experts, have found i t w i t h i n t h e i r domain to use automation. These people have not been able to agree on the one d e f i n i t i o n of automation, so they produced t h e i r own, and thus c o n t r i b u t i n g to the chaos. When Delmar S. Harder f i r s t coined the word \"automation\" he denoted t h i s term to mean automatic t r a n s f e r -of work pieces from one machine to another i n the prod u c t i o n process without human a i d . John Diebold defined i t as \"both automatic o p e r a t i o n and process of making things automatic\".^ Looking at these d e f i n i t i o n s from the present day p o i n t of view, they seem l i m i t e d and f a r too inadequate to describe automation. o B r i g h t has compiled a l i s t of 24 d e f i n i t i o n s of automation which had been presented by persons from various vocations and d i s c i p l i n e s i n t h e i r i n d i v i d u a l r eports before the Congress of the United States i n October 1955^. On t r a c i n g through t h i s l i s t of d e f i n i t i o n s which were expressed 7- Paul T. V i e l l e t t e , \"The Rise of the Concept of Automation\", i n Automation and S o c i e t y , ed. by Howard Boone Jacobson and Joseph S. Roucek, (New York:' P h i l o s o p h i c a l L i b r a r y , Inc., 1959) , p. -5. . \u2022 8 . B r i g h t , op. c i t . , pp. 239-241. 9- U.S. Congress, J o i n t Committee on the Economic Report, Hearings, Subcommittee on Economic S t a b i l i z a t i o n Automation and Tech n o l o g i c a l Change, 84th. Congress, 1 s t Session, Oct. 1955, T U n-\" t e d States Govt. P r i n t i n g O f f i c e , Washington). 6. nine years a f t e r the word was o r i g i n a t e d , one cannot help but f e e l . t h e impact of the d i v e r s e meanings t h i s word has generated even through t h i s short p e r i o d of time. The m a j o r i t y of the d e f i n i t i o n s came i n s i n g l e sentence form, encompassing very broad and loose connotations. Some of these explained that only the word \"automation\" was new, being used to describe the production process vrtiich was merely an extension of mech-a n i z a t i o n and of the i n d u s t r i a l r e v o l u t i o n . A few even defined automation as being synonymous w i t h mechanization. Only one d e f i n i t i o n has been given that i s \"pr e c i s e enough to be u s e f u l i n l o g i c a l a n a l y s i s \" . H e n r y 1 0 has supported M a s s i e 1 1 i n h i s c r i t i c i s m that s i n g l e sentence d e f i n i t i o n s of automation have provided i n s u f f i c i e n t and inadequate coverage of the extensive area i n which automation holds meaning, and thus one of the causes of the problem. A need f o r a more comprehensive d e f i n i t i o n that i s p r e c i s e enough and, y e t , encompassing a wide range, has been 12 recognized by Baldwin and Shultz . Their d e f i n i t i o n was based on three b a s i c concepts of the p r o d u c t i v e process of automation, and became the g e n e r a l l y accepted and recognized 10. E. Floyd Henry, \"Technological Change - A Challenge to C o l l e c t i v e B a r g a i n i n g \" , i n Changing Patterns i n I n d u s t r i a l  R e l a t i o n s , ed. by Frances Bairstow ( M c G i l l U n i v e r s i t y , 13th Annual I n d u s t r i a l R e l a t i o n s Conference, Jun. 6 and 7, 1961), p. 73. 11. Joseph L. Massie, \"Looking Around, Automation f o r Manage-ment\", Harvard Business Review, V o l . 34, Ko. 2, March-A p r i l 195o, p. 143. 12. George B. Baldwin and George P. S h u l t z , \"Automation: A New Dimension to Old Problems\", I n d u s t r i a l R e l a t i o n s Research  A s s o c i a t i o n , Proceedings of the Seventh Annual Meeting, D e t r o i t , Dec. 1954, pp. 1 1 5 - l l b . 7. view of automation. The three b a s i c concepts of automation quoted are as f o l l o w s : -( i ) I n t e g r a t i o n : Connecting together of c o n v e n t i o n a l l y separate i n d i v i d u a l work s t a t i o n s , separate manufacturing operations or t r a n s f e r machines l i n k e d together i n sequence w i t h the automatic handling to form l i n e s of continuous p r o d u c t i o n , w i t h the product f l o w i n g through \"without the need f o r i n t e r v e n t i o n of human hands\". Many of the f u n c t i o n s of machine l o a d i n g and unloading which had been found necessary are e l i m i n a t e d by t h i s process. This development i s a l s o known as \" D e t r o i t 13 Automation\" , because of the c o n t r i b u t i o n made by the automobile i n d u s t r y i n which t h i s had i t s o r i g i n . \" D e t r o i t Automation\" has been known synonymously as mech-3-nization. Another term used i n d e s c r i b i n g t h i s process i s \"continuous automatic;production\". The development of t h i s process depends mainly upon the advancement of s o p h i s t i c a t i o n i n the f i e l d of mechanical engineering. This development of automation has been considered by some as an e v o l u t i o n of the process of mechanization. ( i i ) Feedback Technology: The employment of the c l o s e d loop c o n t r o l devices or servomechanisms which e l i m i n a t e s the need f o r human c o n t r o l i n the perforaiance of i n d i v i d u a l operations. Some b u i l t - i n automatic device, sometimes 1 3 . Anderson Ashburn, .\"Detroit Automation\", i n The Annals of the American Academy of P o l i t i c a l and.Social Science, V o l 3^0, Mar. 1 9 o 2 , Automation, S p e c i a l e d i t o r Charles K i l l i n g s w o r t h , pp. 2 1 - 2 8 . 8. known as \" l i t t l e \"black boxes\" i n c o r p o r a t i n g the processes of mechanizing i n t e l l e c t u a l and sensory f u n c t i o n s , are employed. This development i s based on the establishment of p r e s c r i b e d and predetermined standards and s p e c i f i c -a t i o n s . Any e r r o r or d e v i a t i o n i n performance i s auto-m a t i c a l l y c o r r e c t e d to enable the system to maintain i t s previous predetermined l e v e l of performance. The system has a b u i l t - i n c a p a c i t y to r e g u l a t e and c o n t r o l e r r o r , enabling c o n t r o l f u n c t i o n s to be c e n t r a l i z e d , thus achiev-i n g remote and s e l f - r e g u l a t i n g c o n t r o l . This development i s sometimes known as \"automatic c o n t r o l \" and i s dependent upon the advancement of knowledge and techniques i n the f i e l d of e l e c t r i c a l engineering, and e l e c t r o n i c s . ( i i i ) E l e c t r o n i c Computer Technology: Sometimes known as \"business automation\"\"'' \\ i t i n c o r p o r a t e s the development of general and s p e c i a l computing machines possessing f a c i l i t i e s f o r r e c o r d i n g , s t o r i n g and p r o c e s s i n g of a l p h a b e t i c a l or numerical data. E l e c t r i c a l data p r o c e s s i n g systems w i t h b u i l t - i n \" s y n t h e t i c i n t e l l i g e n c e \" have been able to perform c e r t a i n f u n c t i o n s at speeds beyond that a t t a i n e d by u s i n g the human b r a i n power alone. These \" e l e c t r o n i c b r a i n s \" w i t h t h e i r s t o r e d \"memories\" are capable of supplying d i r e c t i o n to operate machines. Advancement i n e l e c t r i c a l enginnering and e l e c t r o n i c s 14. Bernard Ka,rsh, \"Work and Automation\", i n Automation and  S o c i e t y , ed. by Howard Boone Jacobson and Joseph S. Roucek, (New York: P h i l o s o p h i c a l L i b r a r y , Inc., 1 9 5 9 ) , p. 3 8 7 . has made s i g n i f i c a n t c o n t r i b u t i o n towards progress i n t h i s f i e l d . This i s an area where there i s tremendous p o t e n t i a l f o r expansion. Authors who have used t h i s comprehensive d e f i n i t i o n of automation and have quoted Baldwin and Sh u l t z as t h e i r source, i n c l u d e Henry 1^, L e f t k o w i t z 1 0 , Massie\"^, N o r t h r u p 1 ^ 19 and S i l v e y . There are a l s o other l i t e r a t u r e i n which the three b a s i c concepts have been used to pr o v i d e a comprehensive d e f i n i t i o n of automation without quoting any source from which they have been derived. Some of these have been w r i t t e n by 15- Henry, op. c i t . , p. 74 . 16. I r v i n g L e f t k o w i t z , \"Statement of ...\", i n New Views on  Automation, U.S. Congress, J o i n t Economic Committee, doth Congress, 2nd Session, i 9 6 0 , pp. 147-148. 17. Massie, op. c i t . , p. l43>. 18. Herbert R. Northrup, \"Automation: E f f e c t s on Labor Force, S k i l l s and Employment,\" I n d u s t r i a l R e l a t i o n s Research  A s s o c i a t i o n , Proceedings of the Eleventh Annual Meeting, Chicago, Dec. 1958,' p. 33\"\" 19. Ted.F. S i l v e y , \"Automation Research and Organized Labor\", i n Man and Automation, Report of the Proceedings of a Conference sponsored by the So c i e t y f o r A p p l i e d Anthro-pology at Yale U n i v e r s i t y , (New Haven, Connecticut: Yale U n i v e r s i t y ; The Technology P r o j e c t ; 1956) , p. 88. This comprehensive d e f i n i t i o n has been viewed as being analogous to a three-legged s t o o l . A l l the three l e g s are important. I f one l e g were to be omitted, the other two are i n s u f f i c i e n t to maintain s t a b i l i t y . 1 0 . B a r k i n ,.Chamberlain , Limberg , Shallenberger , and the Department of S c i e n t i f i c and I n d u s t r i a l Research, England (D.S.I.R) . Woodward has a l s o made use of t h i s d e f i n i t -i o n . She quoted her source as the D.S.I.R. The l i t e r a t u r e on automation so f a r uncovered has produced 11 authors and one research o r g a n i z a t i o n , who have agreed upon t h i s p a r t i c u l a r comprehensive d e f i n i t i o n of auto-mation. S i x of these have not quoted any source from which they der i v e d t h e i r d e f i n i t i o n even though the remainder d i d . At l e a s t there seems to be a concensus of o p i n i o n among t h i s group about the extent of the area to be covered by t h i s d e f i n i t i o n . I t i s a l s o p o s s i b l e that there are others 2 0 . Solomon B a r k i n , \" I m p l i c a t i o n s f o r Developments' i n Auto-mation f o r our Economy\", In Impact of Automation on  Employment, Committee on Education and Labor, U.S. Congress, House of Rep r e s e n t a t i v e s j 8 7 t h Congress, 1 s t Session, Mar. 1961), pp. 1 8 7 - 1 8 8 . 21 N e i l W. Chamberlain. Labor, (New York: McGraw-Hill Book Company, Inc., 1 9 5 8 ) , p. 2 9 5 . Here i t was s t a t e d that the concept of i n t e g r a t i o n was nothing new but an e v o l u t i o n of processes which had commenced sin c e the i n d u s t r i a l r e v o l u t i o n . D i f f e r e n t i a t i o n from these i n i t i a l processes of mechanization was c o n t r i b u t e d mainly from the other two b a s i c concepts; feedback technology and computer technology. 2 2 . Herman Limberg, \"Automation and P u b l i c A d m i n i s t r a t i o n \" , I n Airtomation and S o c i e t y , ed. by Howard Boone Jacob son and Joseph S. Roucek, (New York: P h i l o s o p h i c a l L i b r a r y Inc., 1 9 5 9 ) , pp. 360-3O1. 2 3 . Frank K. Shallenberger, \"Economics of P l a n t Automation\", i n Automation i n Business and Industry, ed. by Eugene M. Grabbe, (New York: John Wiley and Sons, Inc., 1957)> p. 5 5 2 . 24. Department of S c i e n t i f i c and I n d u s t r i a l Research, Automation, A Report on the T e c h n i c a l Trends and t h e i r Imuact on Management and Labor, (London: H.M.S.O., 1956\"), p. 1. 2 5 . Joan Woodward, I n d u s t r i a l Organization: Theory and  Practice.., (London: Oxford U n i v e r s i t y P r e s s , 1 9 ^ 5 ) , p. 1 2 . 11. of t h i s o p i n i o n , but have not been uncovered by the l i t e r a t u r e examined so f a r . I t would seem that a long drawn out process has been made to i n d i c a t e the number of instances i n which t h i s defin-, i t i o n was used. This step has been taken to gain support f o r the d e f i n i t i o n . I t i s proposed i n t h i s t h e s i s to define automation by making use of t h i s comprehensive d e f i n i t i o n f i r s t put forward by Baldwin and S h u l t z . Among other comprehensive d e f i n i t i o n s of automation i s a m o d i f i c a t i o n of t h i s d e f i n i t i o n ^ 0 j u s t discussed. This m o d i f i c a t i o n has not gained as much support as the o r i g i n a l d e f i n i t i o n . 5- D e f i n i t i o n of Other Terns Used i n the Study: (a) L e v e l of Automation i n Industry: C l a s s i f i c a t i o n of each major i n d u s t r y group, a, p a i r of major i n d u s t r y groups or ea.ch i n d u s t r y sub-group, by the extent of automation (according to the accepted d e f i n i t i o n ) , being employed 26. See Walter Buckingham, Automation, I t s Impact on Business and People, (Mew York: Harper and Row, P u b l i s h e r s , Inc., 196l), pp. 6-I3. Pour fundamental, p r i n c i p l e s have been used i n the m o d i f i c a t i o n of the d e f i n i t i o n . They are mechanization, continuous-process, automatic c o n t r o l and r a t i o n a l i z a t i o n . Mechanization i n c l u d e s e l e c t r o n i c computers and i s thus e q u i v a l e n t to e l e c t r o n i c computer technology, continuous process i s equivalent to i n t e -g r a t i o n and automatic c o n t r o l I s e q u i v a l e n t to feedback technology. The f o u r t h p r i n c i p l e , r a t i o n a l i z a t i o n , t i e s the engineering aspects of automation to the economic, s o c i a l and managerial aspects, and appears to be I n t a n g i b l e . This study covers the s o c i a l asj)ect of automation and the o r i g i n a l d e f i n i t i o n seemed more appropriate i n usage i n t h i s case. 12. i n the p r o d u c t i o n process during the p a r t i c u l a r time p e r i o d . This extent of automation being employed i n the p r o duction process can be considered by the percent-age of companies i n d i c a t i n g the a p p l i c a t i o n of concepts which c o n t r i b u t e to the d e f i n i t i o n of automation. The i n d u s t r i e s that i n d i c a t e d a l a r g e r percentage of companies s t a t i n g that they employed e l e c t r o n i c computers on a p a r t i c u l a r a p p l i c a t i o n w i l l rank higher than an i n d u s t r y that i n d i c a t e d a lower percentage of companies p r o v i d i n g data f o r the same a p p l i c a t i o n . Some companies may employ t h i s a p p l i c a t i o n more than others w i t h i n the same i n d u s t r y group. I t i s assumed that t h i s w i l l be averaged out i n the data. The \" l e v e l of automation\" has already been defined as: \"... the degree to which machines employed are s e l f -27 s e t t i n g , s e l f - c o r r e c t i v e and programmed.\" I t i s thus considered necessary to define \" l e v e l of auto-mation i n i n d u s t r y \" to encompass the major i n d u s t r y groups and i n d u s t r y sub-groups s t u d i e d , to d i f f e r e n t i a t e t h i s from the d e f i n i t i o n of \" l e v e l of automation\". (b)' S t r i k e : A s t r i k e has been defined, by the U.S. Bureau of Labor S t a t i s t i c s , as a temporary stoppage of work by 27. J i r i Nehnevajsa and A l b e r t Prances, \"Automation and S o c i a l S t r a t i f i c a t i o n \" , i n Automation and S o c i e t y , ed. by Howard Boone Jacobson and Joseph S. Roucek, (New York: P h i l o s o p h i c a l L i b r a r y , Inc., 1 9 5 9 ) , p. 3 9 5 . 13. a group of employees (not n e c e s s a r i l y members of a union) to express a grievance or enforce a demand. In the m a j o r i t y of cases, the i s s u e i n dispute i s d i r e c t l y between two p a r t i e s , the employers and the s t r i k i n g employees. There are s i g n i f i c a n t examples of exceptions that have occurred. In a j u r i s d i c t i o n a l s t r i k e , as w e l l as In a r i v a l union or r e p r e s e n t a t i o n s t r i k e , f o r c e s c o n t r i b u t i n g to the s t r i k e may i n v o l v e more than one union r a t h e r than the employer d i r e c t l y . Employees may take up s t r i k e a c t i o n against t h e i r immediate employer i n the case of a sympathy s t r i k e where u s u a l l y there e x i s t s no present dispute between them. Workers may sometimes engage i n a general or p r o t e s t s t r i k e to b r i n g to.the a t t e n t i o n of the government machinery t h e i r f e e l -i ngs about matters that a f f e c t t h e i r w e l l - b e i n g . P r o p e n s i t y to S t r i k e : Possessing a strong i n c l i n a t i o n , d i s p o s i t i o n or proneness of organized l a b o r to adopt s t r i k e a c t i o n to achieve t h e i r goals. The measure of the prop-e n s i t y to s t r i k e i s determined by the man-days l o s t due to work stoppages from s t r i k e s and l o c k - o u t s . I t i s assumed that the p r o p o r t i o n and d u r a t i o n of l o c k - o u t s are n e g l i g i b l e as compared w i t h that of s t r i k e s of organized l a b o r , and that the work stoppages are caused by the assumption of s t r i k e a c t i o n by trade unions. In t h i s stud;\/ work stoppages are used synonymously as s t r i k e s . The i n t e n s i t y or d u r a t i o n of the s t r i k e s have been con-s i d e r e d more important than the number of i n d i v i d u a l s t r i k e s . 14. An i n d u s t r y a f f e c t e d by a s e r i e s of small s t r i k e s (fewer union members on s t r i k e ) of short d u r a t i o n w i l l rank lower than an i n d u s t r y a f f e c t e d by a few b i g s t r i k e s ( l a r g e number of union members on s t r i k e ) of longer d u r a t i o n , i f the cumulative man days l o s t i n the l a t t e r 28 i s g r e a t e r than that i n the former (d) Production Workers: The standard d e f i n i t i o n of product-i o n workers as accepted by the U.S. Bureau of Labor S t a t i s t i c s i n c l u d e those i n the all-employee group who are employed i n the f o l l o w i n g a c t i v i t i e s : working f o r e -men and a l l non-supervisory workers ( i n c l u d i n g leadmen and t r a i n e e s ) that have been employed i n f a b r i c a t i n g , p r o c e s s i n g , assembling, i n s p e c t i o n , h a n d l i n g , r e c e i v i n g , packing, storage, warehousing, s h i p p i n g , maintenance, r e p a i r , j a n i t o r i a l , watchmen, s e r v i c e s , products develop-ment, a u x i l i a r y p r oduction f o r p l a n t ' s own use (e.g. power p l a n t ) , and record-keeping and other s e r v i c e s which are c l o s e l y connected w i t h the above p r o d u c t i o n operations. 28. C l a r k Kerr and Abraham S i e g e l , \"The I n t e r i n d u s t r y Prop-e n s i t y to S t r i k e - An I n t e r n a t i o n a l Comparison\", i n I n d u s t r i a l C o n f l i c t , ed. by Arthur Kornhauser, Robert Bub i n and Ar thur M.Ross, (New York: McGraw-Hill Book Company, Inc., 1954), p. 189. CHAPTER I I LITERATURE AND PREVIOUS RESEARCH 1. The Par t played by S t r i k e s i n C o l l e c t i v e Bargaining: In the American scene, p r i o r to 1 9 3 0 , organized l a b o r was r e l a t i v e l y i n e f f e c t i v e among the l a b o r i n g c l a s s e s . The impetus i n the u n i o n i z a t i o n of l a b o r was due to f a c t o r s such as the Great Depression, and then the a s s i s t a n c e of the government, through the l e g i s l a t i o n provided f o r i n the Wagner Act\"*\". This spark of l i f e soon b u r s t out i n t o vigorous and energetic a c t i o n by union o r g a n i z e r s , e s p e c i a l l y i n t o area i n the i n t e n s i v e mass pr o d u c t i o n i n d u s t r i e s such as s t e e l , c o a l , rubber, e l e c t r i c a l goods, automobile manufacturing and the manufacturing of a g r i c u l t u r a l machinery, to name a few. The stage was set and the days i n which the manage-ment could e x p l o i t the s e r v i c e s provided by the employees, w i t h impunity, were numbered w i t h the growing s t r e n g t h of the organized l a b o r . The power wielded by the management over the employees, p r e v i o u s l y uncontested, was counterbalanced by that of the trade union, e s t a b l i s h i n g some s o r t of a status quo. The demands of the employees f o r b e t t e r working c o n d i t -i o n s , p r e v i o u s l y unheeded g e n e r a l l y , were channelled through 1. B. M. Selekman, \"Power and M o r a l i t y . i n Labor R e l a t i o n s \" , i n Changing Patterns i n I n d u s t r i a l R e l a t i o n s , ed. by Frances Bairstow, ( M c G i l l U n i v e r s i t y T h i r t e e n t h Annual I n d u s t r i a l R e l a t i o n s Conference, June 6 and 7 , 1 9 6 l ) p. 6 1 6 . the trade union. The management had to s i t up and take n o t i c e . I n v a r i a b l y the trade union and the management would f i n d themselves s i t t i n g at the conference t a b l e i n an e f f o r t to t r y and i r o n out the demands put forward by the trade union, i n the i n t e r e s t s of the employees. When a deadlock occurred over the i s s u e s of the settlement, w i t h each p a r t y not conceding or agreeing to the demands and o f f e r s of the othe p a r t y , then the trade union would seek recourse i n s t r i k e a c t i o n . The p r i n c i p a l source of b a r g a i n i n g s t r e n g t h of a trade union has been considered to be the c a p a c i t y w i t h i n i t s power to b r i n g the f u n c t i o n s and operations of the company to a s t a n d - s t i l l , through s t r i k e a c t i o n . This avenue of a c t i o n would hurt the company most, through the removal of i t s source of revenue. The s t r i k e as a weapon i n the hands of the trade union, can be viewed i n two dimensions. One i s that i t i s a means f o r i n t i m i d a t i n g and threatening i n order to a t t a i n i t s goals. The trade union would h a r d l y have any p o s i t i o n of power at a l l i f i t d i d not possess at the bare minimum, the p o t e n t i a l a b i l i t y to c a l l f o r t h an e f f e c t i v e s t r i k e . The mere threat of a s t r i k e may be s u f f i c i e n t to s o f t e n up the defences set up by the o p p o s i t i o n , making i t more keen and w i l l i n g to come to a compromise. In some i n d u s t r i e s , t h i s course of a c t i o n has been considered a c h a r a c t e r i s t i c pattern, i n the 2 b a r g a i n i n g process . An attempt has been made to manoeuvre 2. Saul W. Gellerman, \" S t r i k e Threat W i l l D e c l i n e , \" i n Nation  Business, V o l . 51 , No. 7 , J u l y 19&3, p. 37. 17. the management i n t o a s i t u a t i o n i n vihich i t has to p a r t i c i p a t e i n c r i s i s b a r g a i n i n g . The management may thus be put i n a p s y c h o l o g i c a l l y disadvantageous p o s i t i o n . Another common fea t u r e i n labor-management disputes has been that management has not taken p a r t s e r i o u s l y i n the n e g o t i a t i o n s u n t i l the deadline of the s t r i k e has reached a p e r i o d that w i l l make management more keenly aware of the consequences. Due to i t s weak economic p o s i t i o n , or i n the face of a strong union, the management may not choose to take on a s t r i k e . The i s s u e s i n v o l v e d may be considered by the manage-ment as being of such dimensions that i t i s not worthwhile to take on a s t r i k e . I t w i l l , then c a p i t u l a t e to the demands of the trade union. This w i l l be thought of as a complete v i c t o r y f o r the trade union. On the other hand, the surrender of the management i n manner, may cause, the trade union to t h i n k i t has a t t a i n e d a p o s i t i o n much stronger than i t a c t u a l l y i s . Subsequently, i n the f o l l o w i n g n e g o t i a t i o n s , the trade union may be encouraged to.employ s i m i l a r s t r a t e g y even over such matters and i s s u e s that the rank and f i l e do not consider worthwhile to take s t r i k e a c t i o n on. In t h i s way, the leaders of the trade union may f i n d themselves so committed but without gain-i n g support from the members. This c o n t i n u a l f l o u r i s h i n g of the s t r i k e as a weapon f o r i n t i m i d a t i o n , even over issues i n c o n s e q u e n t i a l i n nature, may cause the p r e v i o u s l y permissive management to remove i t s e l f 18. from t h i s p s y c h o l o g i c a l l y disadvantageous p o s i t i o n . The management may have no a l t e r n a t i v e hut to make a choice i n acce p t i n g the challenge given by the trade union and take on the s t r i k e . The trade union too may a c t u a l l y want to p r e c i p -i t a t e the s t r i k e to p o i n t out to the management c l e a r l y that i t has the backing of i t s members and i s capable of f o l l o w i n g through w i t h what i t has threatened to do. This i s the second dimension of the s t r i k e - the a c t u a l f a c t i t s e l f where the union members man the p i c k e t s and the company c l o s e s down i t s o perations. The d u r a t i o n of the s t r i k e a f f e c t s both the trade union and i t s members. I f the management c a p i t u l a t e d during the e a r l y p a r t of the s t r i k e , the members would have considered the s t r i k e worthwhile. The union would have achieved a v i c t o r y . On the other hand, the s t r i k e weapon i s unique i n t h a t i t can be thought of as a double edged sword, c u t t i n g both ways. The s t r i k e can be as dangerous to the user, the trade union, and to the v i c t i m , the management. This i s e s p e c i a l l y s i g n i f i c a n t i n the prolonged s t r i k e . Each p a r t y to the dispute may c o n t r i b u t e to i t s own e x t i n c t i o n i n a s t r i k e , by t h i n k i n g that i t i s i n the p o s i t i o n to o u t l a s t the other p a r t y . Trade union members, who have p a r t i c i p a t e d i n previous s t r i k e s , are probably well.aware that s t r i k e s w i t h i n a c e r t a i n d u r a t i o n w i l l enable them to gain more from the s t r i k e than they have to l o s e . A f t e r the end of t h i s p e r i o d , the p o i n t of d i m i n i s h i n g returns sets i n , and they are q u i t e l i k e l y to' 19-l o s e much more than they w i l l gain even a f t e r t h e i r demands have been met a f t e r a prolonged s t r i k e . Some may take the stand that a p s y c h o l o g i c a l \"gain\" may have been achieved i n the prolonged s t r i k e , i n p u n i s h i n g the management even though they have to take some of the punishment themselves. A s t r i k e i n r e a l i t y , a f t e r a p e r i o d of time, villi generate strong economic pressures on the management, through l o s s of revenue and p o s s i b l e l o s s of remuneration by union members which cannot be o f f s e t by the gains derived from the settlement. The p a r t i e s i n the dispute may thus a r r i v e at a s t a t e of stalemate. P o l i t i c a l pressure and pressure from the p u b l i c adversely a f f e c t e d by the s t r i k e may be exerted on the disputants to get them to r e s o l v e t h e i r c o n f l i c t q u i c k l y and amiably. Each p a r t y w i l l be f o r c e d to r e c o n s i d e r and o f f e r concessions to the other p a r t y , i n an attempt to s e t t l e the s t r i k e . .. A stage w i l l be a r r i v e d at when concessions o f f e r e d w i l l be acceptable to both the p a r t i e s and the c r i s i s w i l l thus be r e s o l v e d . Even though the trade union cannot c l a i m complete v i c t o r y through t h i s course of a c t i o n , i t may be able to accomplish, at l e a s t , a c e r t a i n measure of what i t has set out to a t t a i n . On the other hand, i f the trade union members are not s a t i s f i e d w i t h the outcome of the s t r i k e , e s p e c i a l l y i f l o s s e s outweigh the gains, then the trade union l e a d e r s may f i n d them-selves i n a p r e c a r i o u s p o s i t i o n , the p o s s i b i l i t y of l o s i n g members to a r i v a l union, which may j u s t be w a i t i n g f o r t h i s o pportunity. The trade union leaders may have to take steps to improve the morale of the union members so that the union can s t i l l c a l l on the p o t e n t i a l of the s t r i k e weapon to achieve i t s o b j e c t i v e s . Thus, the threat of the s t r i k e , and i n some cases, r e s o r t i n g to a c t u a l s t r i k e a c t i o n by. the trade union, has been a considerable power which the management has to contend wit h . Both employers and employees recognize the power to c a l l on a s t r i k e as the trade union's u l t i m a t e weapon, through concerte a c t i o n of the employees. 2. I n d i c a t i o n of the Waning Power of the Union to S t r i k e i n  C e r t a i n I n d u s t r i e s due to Automation: A l i t t l e over a decade ago, i t had been reported that the l e v e l of automation i n the telephone i n d u s t r y had reached such a sta.ge that when the trade union went on s t r i k e to f o r c e management to comply to I t s demands, the management had been able to maintain s e r v i c e s by means of employing su p e r v i s o r y and non-union personnel and u s i n g automated equipment. Since then, more evidence has appeared regarding the e f f e c t of automation on 3 s t r i k e s i n t h i s minor i n d u s t r y . This i n f l u e n c e has spread 3 . Business Week, Labor, \"Union w i t h Tomorrow's Problems, Communication Workers of America\", No. 1 8 0 0 , Feb. 2 9 , 1954 p. 9 8 . I t i s reported here that t h i s union i s now faced w i t h problems of the f u t u r e w i t h respect to s t r i k e a c t i v i t ; There Is a tendency towards a v o i d i n g the i d e a of p a r t i c i -p a t i n g i n s t r i k e s . Even i f a s t r i k e d i d o r i g i n a t e , i t could l a s t a l o n g time. Success i n the s t r i k e can only b achieved at the stage when machinery and equipment break down and deferred new i n s t a l l a t i o n s can exert s u b s t a n t i a l pressure on the management. The telephone i n d u s t r y has been considered h i g h l y automated and a l s o 1 employee i n 5 i s a s u p e r v i s o r . 21. out to' a few other i n d u s t r i e s as w e l l . These I n d i c a t i o n s have prompted K i r s h to say that: \"In many more i n d u s t r i e s the time has come, or w i l l soon a r r i v e , when i t w i l l become more and more d i f f i c u l t to wage a s u c c e s s f u l s t r i k e against an automated p l a n t . The machines w i l l operate, whether the manual workers w i l l be on the job or on s t r i k e , and s u b s t i t u t e d non-union personnel w i l l tend the new automated machines and processes. The v u l n e r a b i l i t y of many companies against s t r i k e t h r e a t i s . r e c e d i n g , and l a b o r ' s most powerful instrument i s i t s e l f becoming threatened w i t h obsolescence i n many cases, under the impact of automation. Automation can t r u l y be s a i d to be i n c r e a s i n g l y b l u n t i n g the edge of l a b o r ' s most e f f e c t i v e weapon, the p o t e n t i a l power to r e s o r t to a s t r i k e to enforce i t s demands and c l a i m s . \" 4 On l o o k i n g at t h i s q u o t ation the f o l l o w i n g words come v i v i d l y to one's mind, \"labor's most powerful instrument.... threatened w i t h obsolescence .... under the impact of automation.\" With an i n c r e a s e i n the l e v e l of automation i n i n d u s t r y , the trade union's use of the s t r i k e weapon w i l l be d e c l i n i n g i n e f f e c t i v e n e s s . A number of other authors share the sajne p o i n t of view, expressing t h i s i n a greater or l e s s e r number of words. 4. Benjamin S. K i r s h , Automation and C o l l e c t i v e B a r gaining, (New York: C e n t r a l Book Company, 1964) , p. 80 . 22. These i n c l u d e d B a r b a s h ^ Kheel\u00b0, R a s k i n 7 , Seidman, Selekman 9, and S t e r n 1 0 , to name a few. They r e f e r r e d to the telephone communication and o i l r e f i n i n g i n d u s t r i e s as i n d i c a t i n g more signs that the trade unions s t r i k e weapon might become obsolete due to automation i n these i n d u s t r i e s . Some of them a l s o i n c l u d e d the e l e c t r i c a l u t i l i t i e s and the chemical i n d u s t r i e s i n t h i s category, but these had not been c i t e d as o f t e n as the f i r s t two. These authors only gave b r i e f accounts of what had taken p l a c e . I t i s a l s o of i n t e r e s t to note that W i l l i a m E. D i r e c t o r of the Federal M e d i a t i o n and C o n c i l i a t i o n i n the United S t a t e s , has been c i t e d i n The Hew York as having s a i d that i n a few automated i n d u s t r i e s , the 5 . Jack Barbash, \"The Impact of Technology on Labor Manage-ment R e l a t i o n s , \" i n A d j u s t i n g to Tec h n o l o g i c a l Change, ed. by Gerald G. Somers, Edward L. Cushman and Na\/6 Weinberg, (New York: Harper and Row, P u b l i s h e r s , 1 9 6 3 ) , p. 5 2 . 6 . Theodore W. Kheel, \"The Changing Patterns of C o l l e c t i v e B a r gaining i n the Uni t e d S t a t e s \" , i n Employment Problems  of Automation and Advanced Technology, ed. by Jack S t i e b e r , (London: Macmillan, l9'ob)3 p. 379-7 . A. H. Raskin, \"The Squeeze on the Unions\", i n The A t l a n t i c  Monthly, V o l . 2 0 7 , No. 4 , A p r i l 1 9 6 1 , p. 5 6 . 8 . J o e l Seidman, \"The Sources of Future Growth and Decline i n American Trade Unions\", I n d u s t r i a l R e l a t i o n s Research  A s s o c i a t i o n , Proceedings o f t h e Seventeenth Annual Meeting, Chicago, Dec. 1964, p. 103-9 . Selekman, op. c i t . , p. 6 5 . 1 0 . James L. Stern, \"Automation - End or a New Day i n Unionism?\" i n The Annals of the American Academy of P o l i t i c a l and  S o c i a l Science, V o l . 5 5 0 , Nov. 1 9 o 3 , The C r i s i s i n the  American Trade-Union Movement, s p e c i a l e d i t o r s Solomon B a r k i n and A l b e r t A. Blum, p. 27-1 1 . The New York Times, May 2 4 , 1 9 6 5 , p. 6 , column 3-Simkiri, S e r v i c e m- 11 Times 23-organized l a b o r ' s s t r i k e weapon had become almost u s e l e s s . The D i r e c t o r of the Federal Mediation and C o n c i l i a t i o n S e r v i c e holds the p o s i t i o n of the government's top mediator. 3. Some D e t a i l s o f S t r i k e s A f f e c t e d by Automation: Most of the d e t a i l s of s t r i k e s that have been a f f e c t e d adversely, by automation from the trade union's p o i n t of view, have been ab s t r a c t e d from reports i n the Business Week, The New York  Times, the U.S. News and World Report, and The Wall S t r e e t  J o u r n a l . These s t r i k e s , reported i n a c e r t a i n amount of d e t a i l , r e f e r r e d mainly to the telephone communications i n d u s t r y and the petroleum i n d u s t r y . I t must be c l a r i f i e d at t h i s p o i n t that i n t h i s study, the telephone communications i n d u s t r y i s not i n c l u d e d i n the c a l c u l a t i o n s . I t i s because the telephone communicat-ions i n d u s t r y has been considered as a minor u n i t of the communications s e r v i c e I n d u s t r y , and a l s o due to reasons that w i l l be explained I n Chapter I I I , t h i s minor i n d u s t r y has been omitted. I t i s considered as a matter of i n t e r e s t that the d e t a i l s of s t r i k e s i n the telephone communications i n d u s t r y be reported i n t h i s chapter. (a) The Telephone Communications Industry: The President of the Communication Workers of \"12 America, Joseph A. B e i m e , recounted the in s t a n c e that 1 2 . Joseph A. B e i m e , \"American Labor i n a Changing World\", i n Labor i n a Changing America, ed. by W i l l i a m Haber, (New York: Basic Books, Inc., P u b l i s h e r s , 1 9 6 6 ) , p. 3 2 3 - 3 2 9 . 24. occurred i n 1955 when h i s o r g a n i z a t i o n took up a major s t r i k e a g a i n s t one of the companies i n the telephone communications i n d u s t r y , an i n d u s t r y which he considered f a r more automated than most other i n d u s t r i e s . The company, w i t h approximately 5 0 , 0 0 0 employees on the p a y r o l l , had been designated as one of the major employers i n the i n d u s t r y . This company operated i n n i n e southeastern s t a t e s . The s t r i k e took p l a c e i n the s p r i n g and summer of 1 9 5 5 , and l a s t e d f o r a p e r i o d of seventy-seven days. The s t r i k e had been considered e f f e c t i v e by the trade union according to c e r t a i n measures. The u n i t y among a l l the union members who were i n the s t r i k e had been maintained. There was favourable p u b l i c o p i n i o n supporting the s t r i k e . In the end the management c a p i t u l a t e d and the union considered that i t had achieved a net gain through the s t r i k e . But there was one outstanding f a c t noted by the union during the s t r i k e that made them aware that the s t r i k e was l e s s than s u c c e s s f u l . The main o b j e c t i v e of the s t r i k e , to cause the company's operations to come to a h a l t , or to reduce or minimize revenues to such an extent that i t hurt most, was not achieved e f f e c t i v e l y . The company was.able to provide some s e r v i c e to i t s customers during the s t r i k e , by u s i n g the automated telephone system. Even though the s e r v i c e was not up to the standard of the p r e - s t r i k e c o n d i t i o n s i t was s u f f i c i e n t to p o i n t out that the company could operate l i m i t e d l y without a s s i s t a n c e from s t r i k e - b r e a k e r s . 2 5 . U.S. News and World Report gave some d e t a i l s of the s t r i k e that began on J u l y 11, 1963, between the I n t e r -n a t i o n a l Brotherhood of E l e c t r i c a l Workers and the General Telephone Company of F l o r i d a . Among the 4,200 employees i n the company, 2,800 of them p a r t i c i p a t e d i n the s t r i k e . The remaining 1,400 employees, c o n s i s t i n g of super v i s o r s and non-s t r i k i n g employees, about one t h i r d of the t o t a l employment i n the company, were a.ble to maintain normal telephone s e r v i c e to the l o c a l community. In the face of the i n e f f e c t i v e n e s s of the s t r i k e , v i o l e n c e occurred i n the form of c u t t i n g of cab l e s , sawing down of telephone p o l e s , dynamiting and throw-i n g of ga s o l i n e bombs. This method of i n c r e a s i n g the e f f e c t -iveness of the s t r i k e i n c u r r e d unfavourable p u b l i c o p i n i o n . The outstanding f a c t was that telephone s e r v i c e was not d i s -rupted due to the s t r i k e , but the r e s o r t to damage of the company's pr o p e r t y caused p a r t of the s e r v i c e to be discontinued. (b) The Petroleum Industry: This i n d u s t r y has been the most o f t e n c i t e d i n which the s t r i k e has shown proof of i t s i n e f f e c t -iveness i n the face of automation. The f i r s t i n s t a n c e of these s t r i k e s occurred i n 1959 i n t h i s i n d u s t r y . The trade union that p a r t i c i p a t e d i n these s t r i k e s was the O i l , Chemical and Atomic Workers, OCAW. 14 Business Week reported that the OCAW went on s t r i k e 13. U.S. News and World Report, Labor Week, \"How a Company Keeps Going Despite S t r i k e , Sabotage\", V o l . LV, No. 9, Aug. 2 6 , 1963, p. 77. Business Week, Labor, \"Amoco Beats Union on Job Rules\", No. 15ofa, Jan. 23, I960, p. 113. 26. on J u l y 1 , 1959 at the 800 acre petroleum r e f i n e r y of the American O i l Company i n Texas C i t y , Texas. The s t r i k e l a s t e d 191 days. A l l the 1 , 2 5 0 union members went on s t r i k e . The i s s u e that p r e c i p i t a t e d the s t r i k e was not over demands f o r i n c r e a s e i n wages, but over job s e c u r i t y and the management ma i n t a i n i n g the stand that i t had f u l l r e s p o n s i b i l i t y to operate the r e f i n e r y as a s u c c e s s f u l e n t e r p r i s e . The manage-ment wanted to use the r i g h t of a s s i g n i n g job r u l e s and s e n i o r i t y and a r b i t r a t i o n p r o v i s i o n s which could not be agreed upon by the union. A f t e r p i c k e t l i n e s had been e s t a b l i s h e d f o r foxw hours, the company announced that i t would operate the r e f i n e r y . W i t h i n two months, the company was able to produce an output of 1 0 0 , 0 0 0 b a r r e l s a day, approximately 75 percent of the out-put of the p r e - s t r i k e production. About 300 management people, approximately one quarter of the p r e - s t r i k e l a b o r f o r c e , work-i n g s i x or seven days a week and u s i n g automated equipment produced the output reported. I t had been considered that t h i s a n i l i t y of the company, i n the face of a s t r i k e , to operate the r e f i n e r y and producing s u b s t a n t i a l output, played a major p a r t i n f o r c i n g the union to come around to a settlement. Moral v i c t o r y i n the s t r i k e was achieved by the management, even though the union d i d not acknowledge t h i s . The company r e t a i n e d i t s r i g h t of a s s i g n i n g work and to assess the q u a l i f i c a t i o n s r e q u i r e d to carry out the f u n c t i o n s of each job e f f e c t i v e l y . The outcome of the s t r i k e caused the union to experience a s e r i o u s setback i n i t s p r e s t i g e , and a 2 7 . r e d u c t i o n i n the morale of the union members working i n the r e f i n e r y at Texas C i t y . 15 An a r t i c l e appeared i n the Business Week and i n 16 the U.S. N e w s an d Wo r i d R ep o r t , of a s i m i l a r type of s t r i k e t hat occurred between the union and the Standard'Oil Company (Indiana) at i t s r e f i n e r y i n Sugar Creek (Mo.), near Kansas C i t y . The s t i k e began on J u l y 8 , 1959 and l a s t e d approx-i m a t e l y nine months. Seven hundred and s i x t y members of the OCAW went on s t r i k e over Issues on job s e c u r i t y and management's r i g h t of job assignment. The s t r i k e i n i t i a l l y c l o s e d the r e f i n e r y , but the company was able to commence operations two days a f t e r the s t r i k e began. An average output of over 50 percent of c a p a c i t y was maintained throughout the d u r a t i o n of the s t r i k e . I t appeared that the union was not able to maintain u n i t y among i t s ranks and 200 of the s t r i k e r s returned to t h e i r jobs before the s t r i k e c o l l a p s e d . In the v o t i n g , taken at the term i n a t i o n of the s t r i k e , the l o c a l union decided to r e t u r n to work u n c o n d i t i o n a l l y . They were w i l l i n g to put t h e i r f a i t h i n f u r t h e r n e g o t i a t i o n s on a new co n t r a c t . The management refused to grant the union any concessions i t asked f o r . In the f a l l of 1 9 6 1 , the OCAW went on s t r i k e a gainst 15. Business Week, Labor, \"Wine-month O i l S t r i k e C o l l a p s e s \" , No. 1 5 9 3 , Mar. 1 2 , i 9 6 0 , p. 51. .16. U.S. News and World Report, Labor Week, \" I t Keeps G e t t i n g Harder to Win S t r i k e s \" , Vo. XLVII, N o . ' 2 6 , Dec. 2 8 , 1 9 5 9 , P. 7 1 . ' The output produced during the s t r i k e , reported here, was 7 0 percent of capacity.. 2 8 . the Gulf O i l Corporation i n the company's Port Arthur r e f i n e r y 17 i n Texas. This was reported i n the Business Week and by 18 B l u n d e l l i n The Wall S t r e e t J o u r n a l . The s t r i k e was over i s s u e s concerning job s e c u r i t y and maintenance of management r i g h t s . The s t r i k e l a s t e d f o r a p e r i o d of seventy-two days. The r e f i n e r y ' s p r o d u c t i o n and maintenance f o r c e of 3,700 men maintain s t r i c t p i c k e t l i n e s and none of the s t r i k e r s crossed over to r e t u r n to work during the s t r i k e . During the du r a t i o n of the s t r i k e , the r e f i n e r y was operated by 600 s u p e r v i s o r y and t e c h n i c a l personnel c o n s i s t i n g of approximately one s i x t h of the o r i g i n a l p r o d u c t i o n f o r c e . Output of g a s o l i n e , f u e l o i l and miscellaneous products flowed out of the p l a n t at the r a t e of 130,000 b a r r e l s a day, approximately &5 percent of the p r e - s t r i k e oiitput. Gulf O i l Corporation was c r e d i t e d w i t h an important v i c t o r y i n t h i s dispute. The union agreed that the company be allowed to e x e r c i s e greater d i s c r e t i o n i n the area of job assignments, e s p e c i a l l y i n the c o n t r a c t i n g out of maintenance work. Yet another Instance can be c i t e d of a s t r i k e that took p l a c e i n a h i g h l y automated o i l r e f i n e r y and chemical 17. Business Week, Labor, \"Ten Week S t r i k e at Gulf O i l R e f i n e r y ends as both sides bend on job s e c u r i t y \" , No. 1689, Jan. 13, 1962, p. 96 , An output of l e s s than h a l f the r e f i n e r y ' s c a p a c i t y during the s t r i k e was reported. 18. W i l l i a m E. B l u n d e l l , \"Labor and Automation - O i l Union Finds S t r i k e s Often are I n e f f e c t i v e at Automated P l a n t s \" , The Wall S t r e e t J o u r n a l , V o l . CLIX., No. 14, Jan. 19, 1962, p. 1, Column 1. 2 9 . p l a n t that normally produced 1;>5,000 b a r r e l s of g a s o l i n e a day and more than 50 chemical by-products. Reports on t h i s 19 20 s t r i k e were made by Business Week , The New York Times , 21 and the U.S. News and World Report . The s t r i k e s , over i s s u e s that are s i m i l a r to the other three examples recounted e a r l i e r on, began on August 19, 19^2. The disputants were the 0CAW and the S h e l l Oil-Company at the company's p l a n t s l o c a t e d near Houston, Texas. The s t r i k e l a s t e d f o r a p e r i o d of about a year, i n which 2 ,200 workers went on s t r i k e . I t was mentioned that during the du r a t i o n of the s t r i k e , only f o r t y - e i g h t of the o i l workers remained on the job. The company was able to maintain f u l l p r o duction w i t h the s t r i k e i n progress. This p r o d u c t i o n l e v e l was achieved by employing automated equipment and the e f f o r t s of approximately 1,170 non-union s u p e r v i s o r s , engineers and t e c h n i c i a n s . The r a t i o of prod u c t i o n workers to nonproduction workers was 2 to 1. Work f a l l i n g behind schedule was found only i n engineering works, t e c h n i c a l s t u d i e s and maintenance. At the te r m i n a t i o n of the s t r i k e , the settlement provided the union w i t h a 5 percent pay in c r e a s e f o r i t s members, which was not an i s s u e upon which the s t r i k e was based. The company won major concessions i n the new one year c o n t r a c t , i n a c h i e v i n g i n c r e a s e d f l e x i b i l i t y i n such areas as subcontract 19- Business Week, Labor, \" O i l S t r i k e r s get Global Support\", No. 1750, May 25, 1963, pp. 60-67. 20. E d i t o r i a l , The New York Times, Aug. 12, 1 9 6 3 , p. 20 , c o l . 2, 21. U.S. News and World Report, Labor Week, \"The S t o r y of Two S t r i k e s - What Unions are Running up Ag a i n s t \" , V o l . LV., No. 8, Aug. 19, 1963, p. 97-30. work, r e d u c t i o n of employment and r e a s s i g n i n g workers f o r more e f f i c i e n t p roduction. In summary, i t has been very apparent that the i s s u e s on which the s t r i k e s r e f e r r e d to i n the petroleum i n d u s t r y were based were not a question of wages. They were based on the demands of both the p a r t i e s . The trade union demanded job s e c u r i t y and the r i g h t of the worker to work only at the job which he had been employed. On the other hand, management wanted to r e g a i n the ground i t had l o s t p r e v i o u s l y by grant-i n g concessions to the union. Management wanted the r i g h t to a s s i g n work and e x e r c i s e d i s c r e t i o n a r y powers i n improving the o p e r a t i n g e f f i c i e n c y of the p l a n t . The d u r a t i o n of the s t r i k e s i n these examples had ranged from ten weeks to approximately a year. The outcome of the s t r i k e s had not l e f t much doubt as to whom the v i c t o r s were. There i s no doubt that i t i s i n c r e a s i n g l y d i f f i c u l t f o r the OCAW to win a s t r i k e . 4. Research i n the P r o p e n s i t y to S t r i k e : A m u l t i n a t i o n a l general study on the i n t e r i n d u s t r y p r o p e n s i t y to s t r i k e was 22 c a r r i e d out by Kerr and S i e g e l . The study was confined to democratic i n d u s t r i a l i z e d c o u n t r i e s where s t a t i s t i c a l data on the employment l e v e l s and man-days l o s t i n i n d u s t r i a l disputes f o r the time p e r i o d considered were a v a i l a b l e . This r e q u i r e -ment on the data imposed l i m i t a t i o n s on the study to cover only 2 2 . Kerr and S i e g e l , op. c i t . , pp. 1 8 9 - 2 1 2 . 3 1 . eleven c o u n t r i e s . These c o u n t r i e s comprised of A u s t r a l i a , Czechoslovakia, Germany, I t a l y , the Netherlands, New Zealand, \u2022Norway, Sweden, S w i t z e r l a n d , The U n i t e d Kingdom, and the United States. The study was undertaken w i t h a number of o b j e c t i v e s i n mind. The most important o b j e c t i v e was to determine whether employees i n c e r t a i n i n d u s t r i e s have been more i n c l i n e d to s t r i k e than i n other i n d u s t r i e s . I f t h i s was i n d i c a t e d i n the study, an a n a l y s i s of the r e s u l t s would be c a r r i e d out to assess the c o n t r i b u t o r y f a c t o r s determining the proneness to s t r i k e or not to s t r i k e among these i n d u s t r i e s . The p e r i o d on which the study was'based ranged from 1911 to 1 9 4 9 . None of the data from the c o u n t r i e s s t u d i e d was a v a i l a b l e f o r the f u l l range of t h i r t y - n i n e years. A v a i l a b l e data, on man-days l o s t i n i n d u s t r i a l disputes only covered p a r t of the range, from ei g h t to t h i r t y - f i v e years. Data from s i x c o u n t r i e s covered periods g r e a t e r than twenty years w i t h i n t h i s range. Employment, workers covered by c o l l e c t i v e agreements and trade union membership data was a v a i l -able f o r time periods of one year to t h i r t y - f i v e years. The number of i n d u s t r y groups i n each country s t u d i e d ranged from s i x to twenty-eight. F i v e c o u n t r i e s provided data f o r l e s s than s i x t e e n i n d u s t r y groups, w i t h the remainder p r o v i d i n g g r e a t e r than s i x t e e n . The measurement f o r i n t e r i n d u s t r y p r o p e n s i t y to s t r i k e had used a s i n g l e index. The p r o p e n s i t y to s t r i k e 3 2 . among the i n d u s t r i e s had been \" a r b i t r a r i l y d i v i d e d i n t o f i v e c a t e g o r i e s \" . These c a t e g o r i e s ranged from hi g h , medium high, medium, medium low and low. C a t e g o r i z a t i o n had been based on whether the ranking of man-days l o s t was s u b s t a n t i a l l y or s i g n i f i c a n t l y above, simila.r and s i g n i f i c a n t l y or s u b s t a n t i a l l y below the employment rank. The s p e c i f i c a t i o n of the l i m i t s of cat e g o r i e s w i t h i n which, s u b s t a n t i a l l y , s i g n i f i c a n t l y and about the same would apply, were not provided. \" D e t a i l s about the method of a n a l y s i s of data seemed to be l a c k i n g . From the i n t e r i n d u s t r y p r o p e n s i t y to s t r i k e inform-a t i o n developed, a g e n e r a l i z e d grouping of i n d u s t r i e s was made based on the homogeneity of outstanding b e h a v o r i a l c h a r a c t e r i s t i c s of c e r t a i n i n d u s t r i e s among the c o u n t r i e s . L i m i t a t i o n s i n the s t a t i s t i c a l data confined the number of i n d u s t r i e s i n d i c a t i n g a general p a t t e r n of s t r i k e p r o p e n s i t i e s to s i x t e e n . I n d u s t r i e s that f e l l i n t o the high category c o n s i s t e d .of mining, and, maritime and longshore, medium high - lumber and t e x t i l e , medium - chemical, p r i n t i n g , l e a t h e r , manufacturing ( g e n e r a l ) , c o n s t r u c t i o n and food and kindred prdoucts,: medium low -c l o t h i n g , gas, water and e l e c t r i c i t y and, s e r v i c e , and low -r a i l r o a d , a g r i c u l t u r e and trade. I n the medium category, firms' i n these i n d u s t r i e s v a r i e d g r e a t l y i n t h e i r p r o p e n s i t y to s t r i k e , but t h e i r average behaviour f i t t e d w i t h i n t h i s category. In the c a t e g o r i e s a,t the e x t r e m i t i e s , the f i r m s i n the i n d u s t r i e s showed more consistency of behaviour to f i t w i t h i n these c a t e g o r i e s . 3 3 . The r e s u l t s caused the authors to t h e o r i z e g e n e r a l l y on the c h a r a c t e r i s t i c s c o n t r i b u t i n g to the p r o p e n s i t y to s t r i k e based on two hypotheses: \"Hypothesis 1. The L o c a t i o n of the Worker i n Society. Hypothesis 2. The Character of the Job and the Workers.\" The f i r s t hypothesis was developed from the homogen-eous c h a r a c t e r i s t i c s of i n d u s t r i e s found i n high and medium high c a t e g o r i e s as compared w i t h those i n the medium low and low c a t e g o r i e s . Common c h a r a c t e r i s t i c s that are s i g n i f i c a n t to above medium p r o p e n s i t y to s t r i k e i n d u s t r i e s i n c l u d e d environmental f a c t o r s l i k e working and l i v i n g u n u s u a l l y remote from the general community. This may have r e s u l t e d from n a t u r a l geographical or a r t i f i c i a l communication b a r r i e r s . Employees i n these i n d u s t r i e s form r e l a t i v e l y homogeneous groups through t h e i r common bonds based upon grievances brought about by i s o l a t i o n . Opportunity to a i r grievances to t h i r d p a r t i e s i s l i m i t e d . The employers and employees normally come from d i f f e r e n t backgrounds and t h i s leads to d i f f i c u l t y of communi-c a t i o n . V e r t i c a l and h o r i z o n t a l m o b i l i t y of l a b o r i s constrained by the very nature of the jobs. The employees may thus f e e l that the only way of g e t t i n g the general community to pay a t t e n t i o n to t h e i r grievances w i l l be to r e s o r t to s t r i k e a c t i o n . They a l s o f e e l that the infrequency of t h e i r contacts w i t h the general community w i l l not o b l i g a t e them to consider much the e f f e c t s of any a c t i o n they take, whether or not t h i s w i l l a f f e c t the general community adversely. On the other hand, i n d u s t r i e s c h a r a c t e r i z e d by below medium p r o p e n s i t y to s t r i k e possess vast o p p o r t u n i t i e s to i n t e g r a t e and i n t e r a c t w i t h the general community. Exceptions can be found among workers i n the a g r i c u l t u r a l i n d u s t r y , but t h e i r a b i l i t y to organize i s l i m i t e d through d i s p e r s i o n . I n t e g r a t i o n w i t h the community w i l l o f f e r o u t l e t s to a i r grievances to people who do not share such grievances. This would serve to reduce any f e e l i n g s of p e r s e c u t i o n . Opportun-i t i e s to engage i n a c t i v i t i e s w i t h d i v e r s e i n t e r e s t s , away' from the working environment,'would enable the worker to l i v e w i t h problems imposed by h i s working environment. There i s a l s o i n c r e a s e d o p p o r t u n i t i e s f o r v e r t i c a l and h o r i z o n t a l m o b i l i t y among jobs. Employees i n these i n d u s t r i e s are more o b l i g a t e d and Interwoven w i t h the general community, and have to pay a t t e n t i o n to adverse p u b l i c o p i n i o n which w i l l a r i s e out of any s t r i k e a c t i o n that w i l l cause hardships to the general community. Government and market c o n s t r a i n t s found i n these i n d u s t r i e s a f f e c t t h e i r p r o p e n s i t y to s t r i k e . The second hypothesis was a l s o derived from an exam-i n a t i o n of c h a r a c t e r i s t i c s found inherent i n i n d u s t r i e s among the c a t e g o r i e s . These c h a r a c t e r i s t i c s are not as s i g n i f i c a n t as those described i n the f i r s t hypothesis. Factors i n the environment among some i n d u s t r i e s w i t h above medium p r o p e n s i t y to s t r i k e produce workers who are more l i a b l e to r e s o r t to d i r e c t a c t i o n , than compared w i t h those found i n some i n d u s t r i e s c h a r a c t e r i z e d as possessing below medium, p r o p e n s i t y to s t r i k e . ' Examples of exceptions can be produced which prevent t h i s hypothesis to'be accepted n e a t l y . 3 5 . An i n t e r i n d u s t r y study on strike-proneness had been 23 c a r r i e d . o u t among a number of i n d u s t r y groups i n B r i t a i n . Strike-proneness has been defined as the r e l a t i v e p r o p e n s i t y of workers to p a r t i c i p a t e i n s t r i k e a c t i o n . The measurement of strike-proneness made use of the r e s u l t s of three i n d i c a t o r s . The choice of the u n i t s of measurement are as f o l l o w s : 1. S t r i k e r s as a percentage of workers i n employment per year. 2. Working days l o s t per worker per year. 3 . S t r i k e s per 1 0 , 0 0 0 workers i n employment per year. The study had covered the time p e r i o d 1911 to 1945-There was no s p e c i a l c a t e g o r i z a t i o n of strike-proneness f o r the i n d u s t r y groups examined. The ranking of the i n d u s t r y groups were determined by c o n s i d e r i n g the aggregative e f f e c t of each i n d i c a t o r . The i n d u s t r y groups ranked i n descending order of s t r i k e -proneness f o r the p e r i o d s t u d i e d are as f o l l o w s : -1. Mining and quarrying. 2. T e x t i l e s . 3 . M e t a l , engineering, s h i p b u i l d i n g . 4 . Transport. 5 . B u i l d i n g . 6. C l o t h i n g . 23- K.G.J.C. Knowles, \"Strike-proneness and. i t s Determinants\", i n The American J o u r n a l of Sociology, V o l . LX, No. 3 , Nov. 1 9 5 T , pp. 2 1 5 - 2 l o \\ 56. The author mentioned that the r e s u l t s of t h i s study tended to be confirmed by the r e s u l t s obtained by the Kerr and S i e g e l study, i n terms of the b e h a v i o u r a l c h a r a c t e r i s t i c s of employees found i n these i n d u s t r y groups. Other I n d i c a t o r measurements of s t r i k e a c t i v i t y have 24 been used i n a study c a r r i e d out by Ross and Hartman . The s i x measurements of s t r i k e a c t i v i t y are:-1. I n t e n s i t y of Organization. This i s a measurement of the r a t i o of union membership to n o n ~ a g r i c u l t u r a l employment. 2. Membership involvement r a t i o . This i s an i n d i c a t o r of the r a t i o of the number of workers p a r t i c i p a t i n g I n s t r i k e s to the t o t a l union membership. 3 . Employee involvement r a t i o . This i s the r a t i o of the number Of workers p a r t i c i p a t i n g i n s t r i k e s to the non-a g r i c u l t u r a l employment. 4. Duration of s t r i k e s . This r a t i o has been derived from the number of working days l o s t i n l a b o r disputes d i v i d e d by the number of workers i n v o l v e d i n the dispute. 5. Membership l o s s r a t i o . This i s a measurement of the r a t i o of the working days l o s t to the t o t a l union membership. 24. Arthur M. Ross and Paul T. Hartman, Changing Patterns of I n d u s t r i a l C o n f l i c t , (New York: John Wiley and Sons, Inc., I960), pp. 8-14. This i s an extension of the study by A r t h u r M. Ross and Donald I r w i n on \" S t r i k e Experience i n F i v e C o untries, 1927-19 i !T: An I n t e r p r e t a t i o n 1 ' , i n I n d u s t r i a l and Labor R e l a t i o n s Review, V o l . 4, No. 3 , A p r i l 1 9 5 1 , pp. 323-342. The d e t a i l s of these two s t u d i e s are not discussed here because they are not i n t e r i n d u s t r y comparative s t u d i e s . 3 7 . 6. Employee l o s s r a t i o . This i s an i n d i c a t i o n of the average l o s s of time per hundred n o n - a g r i c u l t u r a l employees. I t has been found that the r a t i o s that are most i n d i c a t i v e of i n d u s t r i a l c o n f l i c t are the three r a t i o s , membership involvement r a t i o , d u r a t i o n of s t r i k e s and member-ship l o s s r a t i o . Many formal t h e o r i e s on i n d u s t r i a l c o n f l i c t have been 25 developed to e x p l a i n the u n d e r l y i n g causes of s t r i k e a c t i v i t y . Each of the three d i s c i p l i n e s , economics, psychology and s o c i o l -ogy are i n t e r e s t e d i n the study of s t r i k e a c t i v i t y . Each d i s c i p l i n e has r e s o r t e d to define the c a u s a t i v e f a c t o r s deter-mining the extend of s t r i k e a c t i v i t y and have developed t h e i r own f a v o u r i t e set of remedies to s o l v e the problems. I t i s noted that some of the s t u d i e s are so s p e c i f i c that they may only be a p p l i c a b l e i n the examination of i n d i v i d u a l scene. Others are so general that they may be a p p l i c a b l e to the whole i n d u s t r i a l scene. Other than the s t u d i e s r e f e r r e d to p r e v i o u s l y , there does not seem to be many st u d i e s on i n t e r -i n d u s t r y s t r i k e a c t i v i t y . I n summary, st u d i e s that'have been c a r r i e d out on the p r o p e n s i t y to s t r i k e , made use of s i n g l e u n i t i n d i c a t o r s or m u l t i - u n i t i n d i c a t o r s to measure the p r o p e n s i t y to s t r i k e . I n t h i s study, the proposed method of a n a l y s i s and computation 25- A good reference of t h i s can be found i n A r n o l d S. Tannenbaum, \"Unions\", i n Handbook of O r g a n i z a t i o n s , ed. by James C-. March, (Chicago: Rand McNallv and Co., .1965), PP. 730-735. 38. chosen i s more s u i t e d to the use of the s i n g l e u n i t i n d i c a t o r f o r measuring the p r o p e n s i t y to s t r i k e . CHAPTER I I I COLLECTION OP DATA 1. L e v e l of Automation i n Industry: There i s l i t t l e doubt about the d i f f i c u l t y i n v o l v e d i n t r y i n g to q u a n t i f y automation. Obstacles to the measurement of the l e v e l of automation i n Indu s t r y are formidable. During a c e r t a i n time p e r i o d , the l e v e l of auto-mation among major group i n d u s t r i e s ana sub-group I n d u s t r i e s under i n v e s t i g a t i o n can be considered to be contained w i t h i n the confines of a c e r t a i n segment i n the continuum s c a l e of measurement f o r automation. In t h i s study, t h i s segment of the continuum i s d i v i d e d up i n t o three c a t e g o r i e s , having a t t r i b u t e c h a r a c t e r i s t i c s of high, medium and low l e v e l s of automation i n i n d u s t r y . Here, i n d u s t r y i n c l u d e s major and sub-group i n d u s t r i e s . An i n d i c a t i o n of the l e v e l of automation i n i n d u s t r y can be derived from the use of the comprehensive d e f i n i t i o n of automation discussed p r e v i o u s l y . Thus, the l e v e l of auto-mation i n i n d u s t r y can be considered as a f u n c t i o n of the l e v e l of i n t e g r a t i o n , l e v e l of feedback technology and the l e v e l of computer technology employed i n that p a r t i c u l a r i n d u s t r y . This.can be denoted i n the form of an equation as f o l l o w s : -40. A i L \u00ab f ( l 1L J x i L + c . C , i l l (1) where = l e v e l of automation i n i n d u s t r y i I^k = l e v e l of i n t e g r a t i o n i n i n d u s t r y i * i L = ^-eve^- o f feedback technology i n i n d u s t r y i C.^ = l e v e l of computer technology i n i n d u s t r y i a^ . = weight c o n t r i b u t e d by i n t e g r a t i o n i n i n d u s t r y i b^ = weight c o n t r i b u t e d by feedback technology i n i n d u s t r y i c^ = weight c o n t r i b u t e d by computer technology i n i n d u s t r y i i = 1 up to t o t a l number of i n d u s t r i e s being studied. In a p a r t i c u l a r i n d u s t r y , even i f i t i s p o s s i b l e to get s t a t i s t i c s on the l e v e l s of. i n t e g r a t i o n , feedback tech-nology and computer technology employed, i t i s . d i f f i c u l t to as s i g n weights a^ , b^ and c^ to these components to a r r i v e at an appropriate measure of the l e v e l of automation. Values To be able to as s i g n values to a^ , b^ and c^ one needs to have a very thorough knowledge of the l e v e l of technology i n the i n d u s t r y and the weights c o n t r i b u t e d by these f a c t o r s . This makes i t more d i f f i c u l t i f the study i n c l u d e s many i n d u s t r i e s . of a \u00b1 , b \u00b1 and c^ are d i f f e r e n t from i n d u s t r y to i n d u s t r y . 41. This d i f f i c u l t y can be overcome i f the values of i n t e g r a t i o n , feedback technology and computer technology can be aggregated i n t o one s i n g l e complete component f o r that p a r t i c u l a r i n d u s t r y . In the comprehensive d e f i n i t i o n of automation employed by S t e t t n e r , i t was s t a t e d that : \" C e r t a i n l y , i n i t s most developed form, automation represents a number of advanced types of mechanization which, i n combination,.have a unique economic and s o c i a l impact. The most c h a r a c t e r i s t i c of these techniques are automatic c o n t r o l , e l e c t r o n i c data p r o c e s s i n g , and numerical c o n t r o l ; and i n the highest form of automation, these techniques are i n t e g r a t e d i n t o a system of process c o n t r o l to achieve automatic ope r a t i o n of a complete p r o d u c t i v e process. Automatic c o n t r o l u t i l i z e s the p r i n c i p l e of c l o s e d loop c i r c u i t or \"feedback\"; the i n p u t of the machine i s made to r e g u l a t e i t s own output so that i t i s c o n s t a n t l y main-t a i n e d w i t h i n set standards of q u a l i t y and accuracy. E l e c t r o n i c data p r o c e s s i n g i s the automatic handling of i n f o r m a t i o n by means of e l e c t r o n i c systems known as computers. With numerical c o n t r o l the operations of machine.tools or machine systems are d i r e c t e d by numerical i n s t r u c t i o n s , recorded on punch cards or tape, which c o n t r o l the movements of the machine through automatic equipment. Process c o n t r o l l i n k s these tech-niques i n such a way as to permit automatic o p e r a t i o n , s u p e r v i s i o n , and c o r r e c t i o n of the productive process from the beginning to end.\"1 The d e f i n i t i o n of \"numerical c o n t r o l \" i n t h i s s t a t e -ment i n d i c a t e s that i t i s based upon the concepts of feedback technology, and e l e c t r o n i c computer technology and need not be d i f f e r e n t i a t e d from them. In e l e c t r o n i c computer tech-nology, data i s processed i n t o the computer i n the form of \"numerical i n s t r u c t i o n s recorded on punch cards or tape.\" 1. Leonora S t e t t n e r , \"Survey of L i t e r a t u r e on S o c i a l and Economic E f f e c t s of T e c h n o l o g i c a l Change\",, i n Employment  Problems of Automation and Advanced Technology, ea. by Jack Stfeb'e'r, (Tendon: MacMillan, l y b b ) , p. 452. 42. The e l e c t r o n i c computer i s capable of supplying d i r e c t i o n f o r the automatic operation of machines through co-operation w i t h automatic c o n t r o l . The l i n k i n g of i n t e g r a t i o n , feedback technology and e l e c t r o n i c computer technology can be aggregated as a s i n g l e complete component known as process c o n t r o l . As an i n d i c a t i o n of the l e v e l of automation i n i n d u s t r y , the l e v e l of process c o n t r o l employed i n the i n d u s t r y can be used. This means that the l e v e l of automation i n i n d u s t r y i s equiv-a l e n t to the l e v e l of process c o n t r o l i n i n d u s t r y , that i s AIL = P C i L \u2022\u2022 <*> where ^\u00b11, ~ -eve^- of process c o n t r o l i n i n d u s t r y i . 2. The Pr o p e n s i t y to S t r i k e : This c l a s s i f i c a t i o n among the i n d u s t r i e s s t u d i e d , i s d i v i d e d i n t o three c a t e g o r i e s c o n t a i n i n g a t t r i b u t e c h a r a c t e r i s t i c s of high, medium and low pr o p e n s i t y to s t r i k e . The i n d u s t r i e s are c l a s s i f i e d by comparing the ranking,of annual work stoppages ( i n thousands of man-hours) i n each i n d u s t r y w i t h the corresponding ranking of the annual average production worker employment l e v e l ( i n thousands). The p r o d u c t i o n worker employment l e v e l i s chosen because prod u c t i o n workers p a r t i c i p a t e \" i n s t r i k e s or are a f f e c t e d by s t r i k e s more than s u p e r v i s o r y workers. The demarcation repres-e n t i n g each category i s determined by making sure that approx-i m a t e l y one t h i r d of the t a l l y o f the frequency of pr o p e n s i t y to s t r i k e values f a l l w i t h i n the medium category. In t h i s way, the c e l l i n d i c a t i n g high or low values of frequency to 43. s t r i k e w i l l \"be dependent more upon the i n d u s t r i e s f a l l i n g w i t h i n the cate g o r i e s of the l e v e l of automation i n i n d u s t r y . 3* Data Used and the Method o f . C o l l e c t i o n : (a). L e v e l of Automation i n Industry. In t h i s study, the s t a t i s t i c a l data have been e x t r a c t e d from an i s s u e of C o n t r o l 2 Engineering , a McGraw-Hill P u b l i c a t i o n on i n s t r u m e n t a t i o n , c o n t r o l , systems and design. The survey of computers and t h e i r a p p l i c a t i o n s has been undertaken by the McGraw-Hill Department of Economics. The sample covered 800 of the l a r g e s t U.S. co r p o r a t i o n s . About 650 of these c o r p o r a t i o n s employed 4 , 9 0 4 d i g i t a l computers i n t h e i r operations. Excluded from t h i s sample are a l l government agencies and educations i n s t i t -u t i o n s . The r e s u l t s of the survey have been produced in.two t a b l e s . The 8 0 0 corporations have been c a t e g o r i z e d i n t o a number of major groiip and sub-group i n d u s t r i e s w i t h the manufacturing i n d u s t r i e s defined according to the Standard I n d u s t r i a l C l a s s i f i c a t i o n (SIC) system i n the 196\"3 Census of  Manufacturers, V o l . 1 1 , Industry S t a t i s t i c s , p a r t 1 and 2 , i s s u e d by the U.S. Department of Commerce. The Standard I n d u s t r i a l C l a s s i f i c a t i o n system a l s o covers non-manufacturing i n d u s t r i e s as w e l l . Major group i n d u s t r i e s are designated w i t h a t w o - d i g i t numerical code... The subgroup i n d u s t r i e s are designated by a code c o n t a i n i n g three numerical d i g i t s and the 2. C o n t r o l Engineering. \" I n d u s t r y 1 s P u l s e \" , V o l , 1 2 , No. 4 , A p r i l 1 9 b 5 , pp. 6 7 , 6 9 . 44. minor i n d u s t r i e s use f o u r numerical d i g i t s . The o b j e c t i v e of u s i n g the code i s to provide a b a s i s f o r u n i f o r m i t y and c o m p a r a b i l i t y i n the recording'and p r e s e n t a t i o n of s t a t i s t i c a l data by'government agencies, trade a s s o c i a t i o n s and p r i v a t e research agencies. Under the heading of Industry, the t a b l e contains an assortment of manufacturing and nonmanufacturing i n d u s t r i e s . These are made up of independent.major group i n d u s t r i e s , combination of two or more major group i n d u s t r i e s , sub-group i n d u s t r i e s and a combination of two or more sub-group i n d u s t r i e s . One t a b l e contains s t a t i s t i c s on the absolute number of computers i n o p e r a t i o n , percentage of companies w i t h no e l e c t r o n i c computers, percentage of companies w i t h e l e c t r o n i c computers that h3,ve been i n operation w i t h i n three time spans and the percentage of companies proposing to expand t h e i r computer operations. The other t a b l e contains data on the percentage of companies i n d i c a t i n g the use of computers f o r a p a r t i c u l a r a p p l i c a t i o n , one of which i s process c o n t r o l . The d e t a i l s of the method of sampling have not been provided. I f the q u e s t i o n a i r e method had been used, the t o t a l number of q u e s t i o n a i r e s sent out that had brought i n 800 r e p l i e s was not i n d i c a t e d . The question a r i s e s as to whether the date, received i s r e p r e s e n t a t i v e of the p o p u l a t i o n . I t i s not known what measure has been used to i n d i c a t e the confines of the group of l a r g e s t U.S. c o r p o r a t i o n s . I f the s a l e s volume i s used, then i t i s p o s s i b l e that.the l a r g e s t corporations 45. may be concentrated among a few i n d u s t r y groups. I t i s not p o s s i b l e to check the spread of the companies i n the i n d u s t r y groups that have r e p l i e d to the q u e s t i o n a i r e against the t o t a l number of establishments i n the i n d u s t r y groups, even though f i g u r e s of the percent of companies w i t h no computers and the absolute number of computers i n operation are a v a i l a b l e . C e r t a i n l a r g e c o r p o r a t i o n s may employ more than one computer each. One a s s i s t i n g f a c t o r , e s p e c i a l l y i n the a p p l i c a t i o n of computers f o r process c o n t r o l , i s that the chance of companies r e p o r t i n g t h i s a p p l i c a t i o n but not owning or l e a s i n g the computer i s l i m i t e d . In process c o n t r o l , I t i s d i f f i c u l t f o r many companies to combine together to make use of a common computer f a c i l i t y , making i t necessary f o r the computer to be present i n the p l a n t that i s operated by i t . There i s a l s o d i f f i c u l t y i n v o l v e d i n determining whether the data r e c e i v e d i s r e p r e s e n t a t i v e of the p o p u l a t i o n i n terms of s t r a t i f i c a t i o n of i n d u s t r y groups i n geographiceJL areas. I t i s not c e r t a i n that the personnel c a r r y i n g out the survey are aware of the p o s s i b l e d i s c r e p a n c i e s a f f e c t i n g the accuracy of the data, due to p o s s i b l e shortcomings i n the sampling method i t s e l f . The Department of Economics of the McGraw-Hill Company has co n s i d e r a b l e experience i n c a r r y i n g out surveys of t h i s nature before. I t has a l s o compiled monthly s t a t i s t i c s and conducted other s t u d i e s on the metal working i n d u s t r i e s and has reported the data and f i n d i n g s i n the American M a c h i n i s t and i n Business Week. I t i s a l s o noted 46, that some of these p a r t i c u l a r data on the number of companies and t h e i r a p p l i c a t i o n s have been quoted i n one of the b u l l e t i n s i s s u e d by the U.S. Bureau of Labor S t a t i s t i c s . Due to the d i f f i c u l t y i n conducting the survey and o b t a i n i n g the data, the sources supplying t h i s p a r t i c u l a r type of data are l i m i t e d . This l i m i t a t i o n has pl a c e d r e s t r i c t i o n s on the a b i l i t y of comparing a v a i l a b l e data w i t h a v a i l a b l e sources. (b) P r o p e n s i t y to S t r i k e : The s t a t i s t i c s used i n computing the p r o p e n s i t y to s t r i k e , namely s t a t i s t i c s on annual work stoppages and the annual average p r o d u c t i o n worker employment l e v e l , both on a n a t i o n a l b a s i s , have been e x t r a c t e d mainly from the U.S. Bureau of Labor S t a t i s t i c s on the f o l l o w i n g : -(a) A n a l y s i s of Work Stoppages.^ (b) Employment and Earnings S t a t i s t i c s f o r the Uni t e d S t a t e s . ^ \u2022\u2022^ e A n a l y s i s of Work Stoppages provides data, on du r a t i o n of each stoppage, number of establishments i n v o l v e d , geographical c l a s s i f i c a t i o n , causes, unions i n v o l v e d , method of t e r m i n a t i o n of stoppages and d i s p o s i t i o n of i s s u e s . Data that are r e l e v a n t to t h i s study are found i n Table A - l . This 3. U n i t e d S t a t e s , Department of Labor, Bureau of Labor S t a t i s t i c s , B u l l e t i n No. 1474, op. c i t . , pp. 27-180. 4. United S t a t e s , Department of Labor, Bureau of Labor S t a t i s t i c s , A n a l y s i s of Work Stoppages, B u l l e t i n Nos. 1136 , I I 6 3 , 1 1 9 b , 1218, 1 2 3 4 , 1258, 1278, 1302, 1339, 1381, 1420, 1-460, and 1525-5. United S t a t e s , Department of Labor, Bureau of Labor S t a t i s t i c s , Employment and Earnings S t a t i s t i c s f o r the Unit e d S t a t e s , 1909-1966, B u l l e t i n No. 1312-4, Oct. 1 9 6 6 . 47. t a b l e provides annual data on work stoppages by i n d u s t r y which covers major group i n d u s t r i e s and sub-group i n d u s t r i e s , both f o r manufacturing as w e l l as non-manufacturing i n d u s t r i e s . Work stoppages i n v o l v i n g s i x or more workers and l a s t i n g f o r a p e r i o d of a f u l l day or at l e a s t one f u l l s h i f t are recorded. I t i s mentioned that any work stoppage i n v o l v i n g l e s s than s i x workers and l a s t i n g f o r a p e r i o d of l e s s than one s h i f t s does not s i g n i f i c a n t l y a f f e c t the value of the data compiled, e s p e c i a l l y when these are reported to the nearest ten man-days i d l e . Coverage of work stoppages i s not based upon a sample. A l l work stoppages above the s p e c i f i e d minimum s i z e and d u r a t i o n t h a t have been reported by a r e l i a b l e source are i n c l u d e d . Sources that supply i n f o r m a t i o n on the occurrence of work stoppages to the Bureau of Labor S t a t i s t i c s have been developed over a number of years. These have been updated o c c a s i o n a l l y when the need a r i s e s to improve the q u a l i t y of the data t h a t are compiled. The updating of sources of s t r i k e i n f o r m a t i o n has been made mainly p r i o r to 1950. I t has been estimated that t h i s improvement of the sources of s t r i k e i n f o r m a t i o n has not a f f e c t e d much the t o t a l number of workers i n v o l v e d and the man-days of Idleness. Common sources most o f t e n r e l i e d upon to give reports on the e x i s t e n c e of work stoppages i n c l u d e d some of the f o l l o w i n g : -(a) e x t r a c t s from d a i l y and weekly newspapers on l a b o r disputes (b) n o t i f i c a t i o n from government agencies i n v o l v e d i n employ-ment s e c u r i t y and i n the mediation of l a b o r disputes. 48. (c) employers and employer a s s o c i a t i o n s , (d) i n t e r n a t i o n a l trade unions and t h e i r p u b l i c a t i o n s . The l a s t two sources supply work stoppage inform-a t i o n on a vo l u n t a r y co-operative b a s i s e i t h e r as the stoppages occur or p e r i o d i c a l l y . When the report of any work stoppages from one of the sources mentioned above has been r e c e i v e d , f u l l d e t a i l s on the work stoppage and other p e r t i n e n t inform-a t i o n are secured by m a i l i n g standard form q u e s t i o n a i r e s to a l l the p a r t i e s i n v o l v e d . Exceptions to t h i s procedure of o b t a i n i n g f u l l i n f o r m a t i o n on the work stoppage have been made o c c a s i o n a l l y . The necessary s t a t i s t i c a l data may be obtained by f i e l d r e p r e s e n t a t i v e s of the Bureau or the p a r t i e s i n v o l v e d i n the work stoppage may be contacted by s t a f f members of the co-operating s t a t e agencies. The annual s t a t i s t i c a l data on work stoppages have been deri v e d from the c o m p i l a t i o n of a c t u a l s t r i k e data provided by the p a r t i e s i n v o l v e d . No t e c h n i c a l s t a t i s t i c a l formulas are used. The fundamental process of c o m p i l a t i o n i n v o l v e d assembling the repor t s on i n d i v i d u a l cases, which are then grouped i n t o i n d u s t r i e s according to the Standard I n d u s t r i a l C l a s s i f i c a t i o n f o l l o w i n g a n a l y s i s , e v a l u a t i o n and c l a s s i f i c a t i o n . The b a s i c u n i t from which the data i s obtained i s the work stoppage regardless of s i z e except the minimum as s p e c i f i e d p r e v i o u s l y . Groups of workers who 6. U n i t e d S t a t e s , Department of Labor, Bureau of Labor S t a t i s t i c s , Techniques of Preparing Major BLS S t a t i s t i c a l  S e r i e s , B u l l e t i n No. U b b , Dec. 1954, Chpts. 1, b and 12. 49. p a r t i c i p a t e d i n a work stoppage because of a common o b j e c t i v e are c l a s s i f i e d as being i n v o l v e d i n a s i n g l e s t r i k e . I t i s a l s o p o s s i b l e f o r c e r t a i n workers to be counted more than once i f they are i n v o l v e d i n more than one stoppage during that year. No r e s t r i c t i o n s are made w i t h regard to geographical d i s t r i b u t i o n of the workers and t h e i r a c t u a l number. In an establishment d i r e c t l y i n v o l v e d i n a work stoppage, a l l employees of the employer are considered a f f e c t e d by the di s p u t e , even when a, stoppage i n one s e c t i o n c l o s e r the , whole p l a n t . This c o n d i t i o n i s maintained r e g a r d l e s s of what p r o p o r t i o n of the t o t a l number of workers are a c t i v e l y p a r t i c -i p a t i n g i n the s t r i k e or merely made i d l e by t h e i r colleagues going on s t r i k e . Adjustments are made i n the computation of man-days of i d l e n e s s , when there i s a s i g n i f i c a n t v a r i a t i o n i n the number of workers made i d l e throughout the whole p e r i o d of the work stoppage. Except f o r t h i s i n s t a n c e , the t o t a l number of man-days i d l e i s computed as the product of the t o t a l number of workers i n v o l v e d and the number of days of i d l e n e s s , w i t h the exception of ho l i d a y s and days not normally worked. The e f f e c t s of a stoppage on other establishments, or i n d u s t r i e s r e s u l t i n g i n t h e i r employees being made i d l e due to shortages of m a t e r i a l or s e r v i c e , sometimes known as secondary i d l e n e s s , are not i n c l u d e d i n the computation of the t o t a l number of man-days of i d l e n e s s . There appeared to be a d i s t i n c t i o n between the number of days of i d l e n e s s where only workdays are used and the du r a t i o n of a work stoppage. The d u r a t i o n of a work stoppage Is computed 50. according to the number of calendar days, i n c l u d i n g non-working days from the beginning u n t i l the end of the work stoppage, r a t h e r than making use of working days. I n instances where a work stoppage has not been terminated by a formal agreement at a d e f i n i t e date, computation of the s t a t i s t i c a l data on the number of man-days of i d l e n e s s i s complicated where the workers begin to s l o w l y t r i c k l e back to t h e i r jobs. A more d e t a i l e d record of the number of men and the number of days of i d l e n e s s w i l l have to be kept. In some i n s t a n c e s , a few stoppages may i n v o l v e workers i n more than one i n d u s t r y d i r e c t l y . Where the stoppages are small as a consequence of the number of days of i d l e n e s s , these are grouped i n the i n d u s t r y w i t h the m a j o r i t y of workers p a r t i c i p a t i n g . On the other hand, where l a r g e i n t e r i n d u s t r y stoppages occur, the a n a l y s i s i n the computation i s made more d e t a i l e d , r e s u l t i n g i n a more p r o p o r t i o n a t e a l l o c a t i o n of the t o t a l number of man-days of i d l e n e s s to each i n d u s t r y . The p o s s i b l e l i m i t a t i o n s t h a t may a f f e c t the accuracy of the data have been considered. One of the unknowns i s whether the sources p r o v i d i n g i n f o r m a t i o n on work stoppa-ges provide s u f f i c i e n t coverage that w i l l encompass a complete count of the number of work stoppages. The p u b l i c i t y given to l a r g e and important work stoppages w i l l not cause any of these to be overlooked. These work stoppages c o n t r i b u t e most to the s t a t i s t i c a l data on the number of workers and of the man-days l o s t . I t 51.-i s presumed that the data not covered i s from sm a l l e r s t r i k e s and that these unreported s t r i k e s do not a f f e c t much the f i g u r e s f o r the number of workers and man-days of i d l e n e s s . I t has been considered that the updating of the sources of s t r i k e i n f o r m a t i o n has not s e r i o u s l y a f f e c t e d the c o n t i n u i t y of the data, even though c o m p a r a b i l i t y of data between periods w i l l r e q u i r e more c a r e f u l a n a l y s i s , i f g r e a t e r accuracy i s r e q u i r e d . Work stoppages concerning few workers or of short d u r a t i o n have not been i n c l u d e d because they have been considered not to have played any s i g n i f i c a n t p a r t i n c o n t r i b u t i n g to the i d l e n e s s or i n t e r r u p t i o n to pr o d u c t i o n and thus of l i t t l e importance to the o v e r a l l t o t a l . Another l i m i t a t i o n i n the c o m p i l a t i o n of data may be due to allowances not being made to account f o r normal stopp-ages due to absences due to i l l n e s s , absenteeism, etc. These occur during the normal employment p e r i o d and w i l l occur during the work stoppage as w e l l . Measurement of secondary i d l e n e s s has been omitted due to the inadequacy of e x i s t i n g instruments to i n d i c a t e or estimate such i n d i r e c t e f f e c t s . There have been instances when the i d l e n e s s of workers d i r e c t l y i n v o l v e d i n a s t r i k e have been p r o p o r t i o n a t e l y l e s s than the i d l e n e s s of other workers which has been caused i n d i r e c t l y . These cases are e s s e n t i a l l y found i n many i n d u s t r i e s w i t h la.rge work f o r c e s and dependent upon the m a t e r i a l s and s e r v i c e s c o n t r i b u t e d by a sm a l l e r i n d u s t r y employing a smaller number of workers. Data provided by the Employment and Earnings S t a t i s t i c s 52. present d e t a i l e d i n f o r m a t i o n i n the non-farm work f o r c e on such areas as t o t a l number of employees, women, prod u c t i o n workers i n manufacturing and mining, c o n s t r u c t i o n workers i n most of the remaining non-manufacturing i n d u s t r i e s . These are recorded i n monthly and annual averages. Included are s t a t i s t i c a l data on weekly and hourly earnings, average weekly and overtime hours, and l a b o r turnover r a t e s . The s t a t i s t i c a l data r e l e v a n t to the study from t h i s source are those on the n a t i o n a l annual averages on employment c o v e r i n g p r o d u c t i o n workers i n manufacturing and mining. Employment l e v e l s w i t h i n i n d u s t r i e s can change f r e q u e n t l y even w i t h i n a month. The use of the annual average f i g u r e s w i l l c a t e r f o r t h i s v a r i a t i o n . The method of compi l i n g p r o d u c t i o n worker s t a t i s t i c a l data i s r e l a t e d to that used to gather t o t a l employment l e v e l data. A complete census of employment c a r r i e d out at frequent i n t e r v a l s would be time consuming due to problems a r i s i n g from c o l l e c t i n g and t a b u l a t i n g the data, and great expense would be i n c u r r e d as w e l l . To o f f s e t these problems, the method used i n compi l i n g the s t a t i s t i c a l data i n c l u d e s measure-ment of the t o t a l tin!verse and e s t a b l i s h i n g t h i s as a bench-mark f o r a c e r t a i n time p e r i o d u n t i l the next measurement of the u n i v e r s e . i s c a r r i e d out, which i s u s u a l l y made annually during the f i r s t quarter of the year. From t h i s u n i v e r s e , a r e p r e s e n t a t i v e sample of about 25 m i l l i o n workers from approximately 1 5 5 , 0 0 0 co-operating establishments are obtained. In 1 9 o 5 , the samples i n mining and manufacturing contained 46 53. and 64 percent of t o t a l employees' r e s p e c t i v e l y . The sample survey w i l l enable monthly employment estimate's to be obtained f o r the i n t e r i m p e r i o d between benchmarks. Current employment estimates are obtained by u s i n g the benchmark and l i n k - r e l a t i v e techniques. Once a new benchmark i s e s t a b l i s h e d these i n t e r i m estimates are updated. The universe of t o t a l non-farm employment i s made up of a comprehensive count of the t o t a l number of persons employed i n n o n - a g r i c u l t u r a l establishments, by i n d u s t r y i n the country. T o t a l f i g u r e s of employment i n these establishments are e x t r a c t e d from s o c i a l insurance r e p o r t s , except f o r i n d u s t r i e s that are covered when s p e c i a l sources such as s p e c i a l e s t a b l i s h -ment censuses, are used. C l a s s i f i c a t i o n of establishments i n t o the various i n d u s t r i e s are made according to the Standard I n d u s t r i a l C l a s s i f i c a t i o n Code on the b a s i s of t h e i r p r i n c i p a l product or a c t i v i t y which had been determined from annual sales or r e c e i p t data f o r the previous calendar year, both f o r the universe and f o r the sample. The design of the sampling procedure uses the c u t - o f f sampling method. A l l establishments i n which the t o t a l number of employees over a c e r t a i n s i z e and i n a c e r t a i n region are inc l u d e d . The c u t - o f f p o i n t i s chosen i n such a manner as to achieve two o b j e c t i v e s , ( l ) to provide an appropriate standard of accuracy and (2) to represent a s u b s t a n t i a l p r o p o r t i o n of 7- U.S. Bureau of Labor S t a t i s t i c s B u l l e t i n No. 1312-4, op. c i t . , p. 7 8 5 . 54. t o t a l employment i n the i n d u s t r y . The p r o p o r t i o n of t o t a l employment v a r i e s from i n d u s t r y to i n d u s t r y because of the e f f e c t of the percent of t o t a l employment i n the p a y r o l l s of l a r g e f i r m s . M o d i f i c a t i o n i n the b a s i c design of the sample i s r e s o r t e d to i n cases where i t i s not p o s s i b l e to o b t a i n t o t a l response from a l l f i r m s above the c u t - o f f p o i n t i n which case some of the smaller establishments are chosen. This a l s o depends on whether the i n d u s t r i e s have a l a r g e r p r o p o r t -i o n of t o t a l employment, that i s found i n l a r g e r or smaller establishments. Data from t h i s sample i s obtained by means of a standard form m a i l q u e s t i o n a i r e . The form of the questiona.ire i s a s i n g l e s h u t t l e schedule which w i l l enable a r e p o r t i n g u n i t (a non-faim establishment) to provide monthly data over a p e r i o d of a calendar year. Information r e q u i r e d i n c l u d e s the entry of i d e n t i f i c a t i o n of p r i n c i p a l product produced or a c t i v i t y , and employment data covering f u l l or p a r t - t i m e employees on the p a y r o l l who r e c e i v e pay f o r the monthly p e r i o d ending nearest the 15th of the month. In a d d i t i o n , f o r mining and manufacturing r e p o r t i n g u n i t s , data on the number of p r o d u c t i o n and r e l a t e d workers i n c l u d e d i n t h e t o t a l employment f i g u r e , are requested. The data computed f i r s t i s the all-employee estimate f o r each b a s i c e s t i m a t i n g c e l l , which may be an i n d u s t r y . The all-employee estimate f o r the c u r r e n t month i s the product of the r a t i o of a l l employees i n the sample establishments f o r . the c u r r e n t month to a l l employees i n the sample establishments 55. f o r the previous month m u l t i p l i e d by the all-employee estimate f o r the previous month. Monthly pr o d u c t i o n worker estimates f o r the same b a s i c e s t i m a t i n g c e l l are computed as a product of the all-employee estimate f o r the c u r r e n t month and the r a t i o of p r o d u c t i o n workers to a l l employees i n the sample establishments f o r the c u r r e n t month. The monthly estimates of p r o d u c t i o n workers f o r major group i n d u s t r i e s and sub-group i n d u s t r i e s are obtained by summing prod u c t i o n worker estimates f o r component c e l l s . The annual average data f o r production workers i s obtained by summing the monthly estimates and d i v i d -i n g by 12. The r e l a t i v e l y l a r g e s i z e of the establishment sample has been Considered a f a c t o r i n m a i n t a i n i n g a h i g h degree of accuracy and r e l i a b i l i t y produced by the estimates. Accumulated e r r o r which may a r i s e from the use of the l i n k - r e l a t i v e tech-nique w i l l be removed by a d j u s t i n g to new benchmarks annually. Changes i n new benchmarks w i l l a l s o c a t e r f o r any changes r e q u i r e d i n the changes of i n d u s t r i a l c l a s s i f i c a t i o n of i n d i v i d u a l establishments due to changes of product or a c t i v i t y during the i n t e r i m p e r i o d . I t appears that changes i n new benchmark values have been c o n t r i b u t e d c h i e f l y by the changes i n the i n d u s t r i a l c l a s s i f i c a t i o n . 4. I n d u s t r i e s Chosen f o r the Study. The v a r i a b l e that i s most d i f f i c u l t to measure and t h e r e f o r e most d i f f i c u l t to o b t a i n s t a t i s t i c a l data on i s automation. Even though i t i s assumed that the l e v e l of automation i n i n d u s t r y i s e q u i v a l e n t to the 5 6 . l e v e l of process c o n t r o l i n i n d u s t r y , there are r e l a t i v e l y fev\/ sources of data on process c o n t r o l . This l a c k of data has d i c t a t e d the type of i n d u s t r i e s and the number of i n d u s t r i e s that have been chosen f o r t h i s study. R e f e r r i n g to the t a b l e on page 6 9 of the A p r i l 1 9 6 5 i s s u e of C o n t r o l Engineering, the f o l l o w i n g major group i n d u s t r i e s have been chosen f o r the study:-A. Manufacturing of Durable Goods. 1. Primary metal i n d u s t r i e s c o n s i s t i n g of i r o n and s t e e l and non-ferrous metals. 2. Machinery. 3. E l e c t r i c a l Machinery. 4. T r a n s p o r t a t i o n equipment c o n s i s t i n g of autos, trucks and p a r t s , aerospace and other t r a n s p o r t a t i o n equipment. 5 and 6. F a b r i c a t e d metals and instruments 7- Stone, c l a y and g l a s s . 8. Miscellaneous manufacturing. B. Manufacturing of Non-durable Goods. 1. Chemicals. 2. Paper and Pulp. 3. Rubber. 4. Petroleum and Coal products. 5. Food and Beverages. 6. T e x t i l e s . 57. C. Mining. The i n d u s t r y , f a b r i c a t e d metals and instruments have been considered to be comprised of two major group i n d u s t r i e s , the f a b r i c a t e d metals and the instruments i n d u s t r i e s . M ining i n c l u d e s metal, c o a l , crude petroleum and n a t u r a l gas, quarry-i n g and non- m e t a l l i c mining. Other major group and sub-group i n d u s t r i e s i n c l u d e d i n t h i s t a b l e but not i n c l u d e d i n the study are r a i l r o a d s , other t r a n s p o r t a t i o n and communications, e l e c t r i c u t i l i t i e s and commercial business. For r a i l r o a d s and other t r a n s p o r t -a t i o n and communications, complete data on non-supervisory workers i s not a v a i l a b l e . In the A n a l y s i s of Work Stoppages, e l e c t r i c , gas and s a n i t a r y s e r v i c e s are aggregated as one minor i n d u s t r y . Since data on man-days i d l e i s ...not a v a i l a b l e to enable t h i s s t a t i s t i c a l grouping to be broken up, e l e c t r i c u t i l i t i e s are omitted. Commercial business i n c l u d e s trade, f i n a n c e and s e r v i c e s . Data on non-supervisory workers f o r f i n a n c e and s e r v i c e s i s incomplete and thus commercial business i s omitted.. Comparing the l i s t of i n d u s t r i e s i n Con t r o l Engineering w i t h that reported by the U.S. Bureau of Labor S t a t i s t i c s on the A n a l y s i s of Work Stoppages and the Employment and Earnings  S t a t i s t i c s , those i n Con t r o l Engineering have major group and sub-group i n d u s t r i e s mixed together. There i s some d i f f i c u l t y i n t y i n g back some of these major group and sub-group i n d u s t r i e s w i t h that reported by the U.S. Bureau of Labor S t a t i s t i c s because.the names i n the former are o f t e n shortened and do not 58. TABLE I. NAMES OP SOME MAJOR GROUP AND SUB-GROUP INDUSTRIES FROM WO SOURCES. Names of Industry Groups from D i f f e r e n t Sources No. Co n t r o l Engineering U.S. Bureau of Labor S t a t i s t i c s 1. Aerospace A i r c r a f t and p a r t s 2. Instruments Instruments and r e l a t e d products. 3- Chemicals Chemicals and a l l i e d products. 4. Paper and Pulp Paper and a l l i e d products. 5. Rubber Rubber and miscellaneous p l a s t i c s products. 6. Petroleum and c o a l products Petroleum r e f i n i n g and r e l a t e d i n d u s t r i e s . 7. . T e x t i l e s . T e x t i l e m i l l products. 59. f o l l o w e x a c t l y that of the l a t t e r . D e t a i l s of minor i n d u s t r i e s or the Standard I n d u s t r i a l C l a s s i f i c a t i o n Code f o r each major group or sub-group i n d u s t r y i n the former are not provided. Table I i s a l i s t of major group and subgroup i n d u s t r i e s which have been provided w i t h names that are not e x a c t l y the same by each source. .A means f o r t y i n g back the names of i n d u s t r i e s provided by these two sources of s t a t i s t i c a l data has been o provided by the p u b l i c a t i o n News Front , In the Table of Contents the names of i n d u s t r i e s are s i m i l a r to those used i n Co n t r o l Engineering, but here there i s a breakdown of the i n d u s t r i e s and the Standard I n d u s t r i a l C l a s s i f i c a t i o n Code i s provided. R e l a t i n g the minor i n d u s t r i e s and t h e i r Standard I n d u s t r i a l C l a s s i f i c a t i o n Code to those found i n the reports of the U.S. Bureau of Labor S t a t i s t i c s , i t i s found that the names of i n d u s t r i e s given i n Co n t r o l Engineering are synonymous w i t h that used i n the U.S. Bureau of Labor S t a t i s t i c s . There may be a tendency i n trade j o u r n a l p u b l i c a t i o n s to use shortened and r e l a t e d names d i f f e r e n t from those used by the U.S. Bureau of Labor S t a t i s t i c s . To ensure that there i s consistency i n u s i n g the data from C o n t r o l Engineering and from the U.S. Bureau  of Labor S t a t i s t i c s , a t a b l e c o n t a i n i n g i n d u s t r y c l a s s i f i e d i n t o major groups and sub-groups w i t h t h e i r corresponding two d i g i t and t h r e e d i g i t Standard I n d u s t r i a l C l a s s i f i c a t i o n Code has been compiled as shown i n Table X V I I I i n the Appendix. 8. News Front, \"The News Front D i r e c t o r y of 7,500 Leading U.S. Manufacturers\", 19Sl, p. 3-CHAPTER IV TESTING OP HYPOTHESIS 1. Theory of the A n a l y s i s of r by k Contingency Table: . The method used i n the t e s t i n g of the hypothesis i s dependent upon the phenomena that i s st u d i e d . In the l e v e l of auto-mation i n i n d u s t r y and the p r o p e n s i t y to s t r i k e , the degree of d i f f e r e n c e w i t h i n each v a r i a b l e cannot r e a d i l y be q u a n t i f i e d , that i s , the scores may not be t r u l y numerical. The two v a r i a b l e s can be c l a s s i f i e d i n t o a number of a t t r i b u t e s . These ca t e g o r i e s are independent i n that assignment of one frequency to a c e l l i n no way a f f e c t s the assignment of any other frequency to that c e l l or any other c e l l . Data thus c a t e g o r i z e d can be t e s t e d f o r s i g n i f i c a n c e by u s i n g :nonp.arametric t e s t s . A : nonparametric s t a t i s t i c a l t e s t i s used on a model which does not l a y down c o n d i t i o n s about the parameters of the p o p u l a t i o n from which the sample has been drawn. In u s i n g the nonparametric s t a t i s t i c a l t e s t s c e r t a i n assumptions are made, such as, the observations are made independently and the v a r i a b l e s under study possess.underlying continuity\"'\". These assumptions are considered fewer and weaker than those connected w i t h parametric t e s t s . . In a d d i t i o n to 1. Sidney S i e g e l , Nonparametric S t a t i s t i c s f o r the Behavioural  Sciences, (New York: McGraw-Hill Book Co., Inc., 1956), P \u2022 31 \u2022' 61. t h i s , the non-parametric t e s t s dispense w i t h the requirement f o r measurement so strong as those found necessary i n para-m e t r i c t e s t s . The chi-square t e s t may he employed to t e s t the s i g n i f i c a n c e of the d i f f e r e n c e s among independent groups, when the data i n the form of frequencies can be a l l o c a t e d to c a t e g o r i e s . The chi-square technique r e q u i r e s that each' observation be obtained i n such a manner that i f the value of any one observation i s known, i t i s not p o s s i b l e to make an a p r i o r i p r e d i c t i o n of the value of any other observation. I n order that the chi-square t e s t can be a p p l i e d , the frequencies w i l l have to be arranged i n the form of a t a b l e as shown:'in Table I I . When data, i s c l a s s i f i e d accord-i n g to two or more a t t r i b u t e s , the t a b l e thus formed Is g e n e r a l l y known as a contingency t a b l e . An r by k con-tingency t a b l e i s made up of a t a b l e possessing r rows and k columns. R e f e r r i n g to Table I I , A and B are the two v a r l a t e s where A i s d i v i d e d Into k c a t e g o r i e s and B i n t o r c a t e g o r i e s . Let Column headings = A, , A 0, A- ... A. ... A, 1 2' p j K Row headings = B-^ , B 2, B- ... B^ ... B r Observed c e l l frequencies = 0 ^ . where s u b s c r i p t i represents the row and sub-s c r i p t j represents the' 62. TABLE I I . r by k CONTINGENCY TABLE A 2 A 3 \u2022 \u2022 \\ Row To t a l B l \u00b0u \u00b012 \u00b013 \u2022 \u2022 \u00b0lk n r B 2 \u00b021 \u00b022 \u00b023 \u2022 \u00b02j \u2022 \u00b02k n2. B 3 \u00b031 \u00b032 \u00b033 \u2022 \u2022 \u00b03k n3. \u2022 \u00ab \u2022 \u2022 \u2022 \u2022 \u2022 B i \u00b0il 0 i 2 O- -z i3 \u2022 o. . \u2022 n. I . \u2022 \u2022 \u2022 \u2022 \u2022 \u2022 \u2022 \u2022 \u2022 B r r l 0 r 2 \u00b0r3 \u2022 \u2022 \u00b0rk n r. Column T o t a l n . i n . 2 \".3 \u2022 n . k N column to which the r e s p e c t i v e c e l l belongs. Row t o t a l of observed frequencies = n. = E 0. 1J (3) Column t o t a l of observed frequencies = n . = E 0, ' 3 i = l 10 (4) r k T o t a l number of frequences = N = E n . = E n (50 6 3 . 2. Chi-square: The acceptance or r e j e c t i o n of a s t a t i s t i c a l hypothesis i s determined on whether i t i s known about what to expect i f the hypothesis i s true. To achieve t h i s , i t i s necessary to compute the frequency values which w i l l be expected i n the v a r i o u s c e l l s or components of an r by k contingency t a b l e i f the hypothesis of independence i s true. L e t E. . be the expected frequency f o r the c e l l d efined by the i t h row and the k t h column. This expected frequency value can be determined by m u l t i p l y i n g the t o t a l number of frequencies by the product of the p r o b a b i l i t y of g e t t i n g a frequency i n t o the i t h row and the p r o b a b i l i t y p of g e t t i n g a frequency f a l l i n g i n t o the k t h column. The n i . n i two p r o b a b i l i t i e s can be denoted by and -j^- r e s p e c t i v e l y . Therefore, n. h . (n. )(n .) Thus, under the hypothesis of independence, the expected value of the f r e q u e n c i e s , E. . , f o r any c e l l , can be computed as the r e s u l t of the product of the row t o t a l , n. , to which the c e l l belongs and the column t o t a l , n ., , to which the c e l l belongs and then d i v i d i n g by the t o t a l number of f r e q u e n c i e s , N . The sum of the expected c e l l frequencies f o r any row or column i s equal to the sum of the observed c e l l frequencies f o r that corresponding row or column. 2. The r a t i o n a l e f o r t h i s computation i s explained i n John E. Preund, Modern Elementary S t a t i s t i c s , Second E d i t i o n , (Englewood C l i f f s ; N . J . , P r e n t i c e H a l l , Inc., . 1 9 6 5 ) , PP- 272-281. The expected c e l l frequencies have been computed i n order to t e s t the n u l l hypothesis, H O , that there i s no r e l a t i o n s h i p between A and B . The b a s i s upon which the d e c i s i o n i s made to accept or r e j e c t t h i s hypothesis w i l l be determined by a comparison between the observed c e l l f r e q u e n c i e s , Q. . } and the expected c e l l f r e q u e n c i e s , E. . , i f the n u l l i J i j hypothesis, H q , i s true. Depending upon the l e v e l of s i g n i f i c a n c e of the t e s t that i s r e q u i r e d , i f the d i f f e r e n c e s between 0. . and E. . are small,, t h i s w i l l i n d i c a t e the f a c t that the h u l l hypothesis, H Q , should be accepted. But on the other hand, i f the d i f f e r e n c e s between the frequencies are s u b s t a n t i a l , t h i s w i l l i n d i c a t e the f a c t that the n u l l hypo-t h e s i s , H O , should be r e j e c t e d . The v a r i a t i o n between the two sets of frequencies may be s u b s t a n t i a l , but i t i s necessary to determine whether these d i f f e r e n c e s may be a t t r i b u t e d by chance or whether they show that the n u l l hypothesis, H q , i s f a l s e which means that there i s a dependence between A and B . The measure or c r i t e r i o n upon which the d e c i s i o n i s based can be expressed a l g e b r a i c a l l y as f o l l o w s : c r k (0. . - E. . ) 2 x = \u00a3 s -12 i i _ -....(7) i = l j = l E. . p where y. = a s t a t i s t i c c a l l e d chi-square and i t s symbol i s the greek l e t t e r c h i w i t h the exponent 2 . r k \u00a3 \u00a3 = a double summation s i g n ' i n d i c a t i n g that a l l c e l l s i = l j - l are i n c l u d e d i n the summation. 65. There e x i s t s a t h e o r e t i c a l d i s t r i b u t i o n which i s c a l l e d the chi-square d i s t r i b u t i o n . I f the n u l l hypothesis of independence i s t r u e , the r e s u l t i n g sampling d i s t r i b u t i o n agrees very c l o s e l y w i t h t h i s t h e o r e t i c a l d i s t r i b u t i o n . This i s the reason why the name, chi-square, has been chosen as the c r i t e r i o n f o r t e s t i n g . t h e n u l l hypothesis of independence. The shape of one on the t h e o r e t i c a l chi-square d i s t r b u t i o n s i s as shown i n Figure 1. 3- Degrees of Freedom: The shape of the chi-square d i s t r i -b u t i o n depends on the number of degrees of freedom or the number of independent v a r i a t e s . In Figure 1 , t h i s chi-square d i s t r i b u t i o n has 4 degrees of freedom. Y i n d i c a t e s the 3 o r d i n a t e s c a l e of the curve. The values of Y f o r each chi-square d i s t r i b u t i o n v a r i e s w i t h the number of degrees of freedom. The f i g u r e shows that the curve i s skex^ed to the r i g h t and the t e s t f o r the n u l l hypothesis, H Q , i s a one-t a i l e d t e s t . The area under the curve i s equal to one. I f the l e v e l of s i g n i f i c a n c e i s assumed as .05 , then the area under the curve f a l l i n g w i t h i n the r e j e c t i o n r e g i o n (shaded) i s equal to . 0 5 . When the number of degrees of freedom i s d f - 2 * f \u2022 Y \u00ab i (X 2) 2 e\" 2 , 2 d f \/ 2 . r ( i | ) where T i n d i c a t e s the gamma f u n c t i o n . From Quinn McNemar, P s y c h o l o g i c a l S t a t i s t i c s , Second E d i t i o n , (New York: John Wiley and Sons, Inc., 1 9 5 4 ) , pp. 2 1 8 - 2 1 9 . 67-l a r g e , the r e s u l t a n t c\\irve approximates c l o s e l y to a normal curve. A t a b l e denoting the c r i t i c a l values of chi-square i s a v a i l a b l e , by computing from the t h e o r e t i c a l chi-square 4 d i s t r i b u t i o n . This t a b l e has two s c a l e s , the v e r t i c a l s c a l e showing the number of degrees of freedom and the h o r i z o n t a l s c a l e i n d i c a t i n g the p r o b a b i l i t y under the n u l l hypothesis, p H Q > that x i s gre a t e r or equal to chi-square. I t has been considered an unusual occurrance that a problem should i n v o l v e more than t h i r t y degrees of freedom. 2 When x i s computed by an r b y k contingency t a b l e , the equation used to compute the number of degrees of freedom i s df = ( r - l ) ( k - 1) (8) I t can be shown t h a t , s i n c e the sum of the expected c e l l f requencies of any row or column must be equal to the sum of the observed c e l l frequencies f o r that row or column, then, i n an r by k contingency t a b l e , i f ( r - l ) ( k - l ) of the expected c e l l frequencies have been computed, a l l the remaining E- \u2022 may be obtained by subtracting,, from the t o t a l s of the rows and the columns. I n genera l , a contingency t a b l e composed of r rows and k columns has ( r - l ) ( k - 1) independent c e l l s . Subject to ..the l i m i t a t i o n s imposed by the problem, the independent c e l l s possess freedom to take on any values. When 4. See Table XXIV i n the Appendix.. 68. a problem has a l a r g e r number of independent c e l l s , there are more chances f o r random sampling v a r i a t i o n s to take p l a c e . With the number of the c e l l s t hat can f l u c t u a t e independently of the others being i n c r e a s e d , there, is. more leeway f o r f l u c t -u a t ions i n random sampling to be i n c l u d e d i n the operation. Allowance f o r t h i s has been taken i n t o account i n computing the c r i t i c a l values f o r chi-square mentioned p r e v i o u s l y . o 4 . The C r i t e r i o n f o r X : I f there e x i s t s r e l a t i v e l y l i t t l e v a r i a t i o n between the observed and the expected c e l l f r e q u e n c i e s , t h e i r d i f f e r e n c e ( 0 . . - E. \u2022) and x w i l l be r e l a t i v e l y s m a l l . I f there e x i s t s a r e l a t i v e l y l a r g e v a r i a t i o n between the observed and the expected c e l l frequencies 2 2 t h e i r d i f f e r e n c e and x w i l l be l a r g e . Small values of x w i l l support the n u l l hypothesis, H Q , w h i l e l a r g e values of 2 2 X w i l l c o n t r i b u t e to i t s r e j e c t i o n . Whether the X i s l a r g e enough to r e j e c t or support the n u l l hypothesis, H Q , w i l l be based on the chi-square d i s t r i b u t i o n and the l e v e l of s i g n i f i c a n c e r e q u i r e d . For example, suppose that the l e v e l of s i g n i f i c a n c e , a = . 0 5 i s r e q u i r e d i n the t e s t . The n u l l hypothesis, H , can be t e s t e d w i t h the f o l l o w i n g c r i t e r i o n : o 2 Reject the n u l l hypothesis, H , i f X i s g r e a t e r than x 05 a n c^ a c c e P t the hypothesis (or reserve judgement) 2 2 i f x 1 S l e s s than or equal to x 05 ' 69-When x i s greater than x , the v a r i a t i o n between the observed and expected c e l l frequencies are too l a r g e to be due to chance alone. The presumption can be made that the sample frequencies have been drawn from a.pop-u l a t i o n where the c h a r a c t e r i s t i c s being s t u d i e d are not inde-pendent of each other. I t can be concluded that a r e l a t i o n -2 ship e x i s t s between A and B . When x i s l e s s than or 2 equal to x 05 3 ^ n e n u H hypothesis, H q , cannot be r e j e c t e d . , The v a r i a t i o n between the observed and expected c e l l frequencies may be a t t r i b u t e d to chance. There i s much l i k e l i h o o d that the observed sample r e l a t i o n s h i p s are nothing more than that caused by random sampling v a r i a t i o n . Judgement can be reserved or i t can be concluded that there i s no r e l a t i o n s h i p between A and B . p In c a x r y i n g out the x t e s t , there i s one r e q u i r e -ment t h a t i s necessary to ensure that the t e s t i s not l e s s 2 meaningful. The x sampling d i s t r i b u t i o n has been form-u l a t e d to approach c l o s e l y the t h e o r e t i c a l chi-square d i s t r i b -u t i o n from which the tables, are complied. Thus, i t i s important that the t e s t should not be used when the expected c e l l frequencies are very s m a l l . A r u l e of thumb, considered r e l a t i v e l y safe and used by many s t a t i s t i c i a n s , i s to use 2 the x c r i t e r i o n when none of the expected c e l l frequencies 2 i s l e s s than 5 . A more s p e c i f i c c r i t e r i o n f o r the x t e s t has- been recommended that when the number of degrees of freedom, df. i s greater than 1 , then fewer than 20 percent of the c e l l s should possess an expected frequency of l e s s than 70. 5\u2022, and no c e l l should possess an expected frequency of l e s s 5 than 1. There are a l s o other c o n d i t i o n s and requirements p necessary f o r the a p p l i c a t i o n of the x a n a l y s i s f o r i t s use to he v a l i d . These i n c l u d e the f o l l o w i n g : 1. The sample observations must be independent of each other. 2. The sample observations must be drawn at random from the area or p o p u l a t i o n sampled. 3. The data must be expressed i n o r i g i n a l u n i t s and not i n percentage or r a t i o form. In t h i s study, the two . v a r i a b l e s , the l e v e l of auto-mation i n i n d u s t r y and the p r o p e n s i t y to s t r i k e are each d i v i d e d i n t o three c a t e g o r i e s c o n t a i n i n g h i g h , medium and low a t t r i b u t e s . The n u l l hypothesis, H Q , w i l l be t e s t e d on a three by three contingency t a b l e possessing (3-1)(3-1) = 4 degrees of freedom. 5. The Contingency C o e f f i c i e n t , C : A f t e r i t has been shown that a c o r r e l a t i o n between the two q u a l i t a t i v e v a r i a b l e s meet 2 the l e v e l of s i g n i f i c a n c e r e q u i r e d by employing the x c r i t e r i o n , i t i s necessary to o b t a i n an i n d i c a t i o n of the s t r e n g t h of t h i s r e l a t i o n s h i p . The measure of the s t r e n g t h of a s s o c i a t i o n or c o r r e l a t i o n between two sets of a t t r i b u t e s 5. W i l l i a m G. Cochran, \"Some Methods f o r Strengthening the Common x 2 t e s t s \" , i n B i o m e t r i c s , V o l . 10, 1954, pp. 418-420. 71. can be determined by employing the contingency c o e f f i c i e n t , o 5 When the two v a r i a b l e s possess a greater degree of a s s o c i a t i o n , then a higher value of C i s derived. The degree of a s s o c i a t i o n can be computed from a contingency t a b l e o f the frequencies by u s i n g the formula Contingency c o e f f i c i e n t , C = \u2014 ( 9 ) X +N The symbols used i n t h i s formula are s i m i l a r to those used i n the r by k contingency t a b l e discussed e a r l i e r . For contingency t a b l e s that have a r e l a t i v e l y l a r g e number of rows a,nd columns, the contingency c o e f f i c i e n t , C , i s s i m i l a r to the o r d i n a r y c o r r e l a t i o n c o e f f i c i e n t i n the respect that they have values c l o s e to 0 when there i s no c o r r e l a t i o n and c l o s e to 1 when the a s s o c i a t i o n i s strong. There I s a l i m i t a t i o n to t h i s s i m i l a r i t y when the contingency t a b l e possess r e l a t i v e l y , few rows and columns. When there i s an equal number of rows and columns i n a contingency t a b l e , r = k . Then, Upper l i m i t of C = ( 10) M is. v In a three by three contingency t a b l e , C has a maximum value of = 0 . 8 l 6 . The f a c t that the upper l i m i t of the c o n t i n -gency c o e f f i c i e n t , C , i s a f u n c t i o n of the number of ca t e g o r i e s 6 . S i e g e l , op. c i t . , pp. 1 9 6 - 2 0 2 . imposes a l i m i t a t i o n on the comparison of two contingency c o e f f i c i e n t s unless I t i s ensured that they have been derived from contingency t a b l e s of the same s i z e . The contingency c o e f f i c i e n t , C , i s a p p l i c a b l e i n determining the s t r e n g t h of the r e l a t i o n s h i p between two sets of a t t r i b u t e s r e g a r d l e s s of the shape of the p o p u l a t i o n they have been derived from, whether the v a r i a b l e s are continuous or d i s c r e t e , and whether they are orderable or not. T h i s , and the ease of computations has Contributed to i t s a p p l i c -a t i o n . 6. A n a l y s i s of the Data: (a.) L e v e l of Automation i n Industry. Process c o n t r o l data i s not a v a i l a b l e f o r P e r i o d 1 , but i s a v a i l a b l e f o r P e r i o d 2 , s i n c e the data has been reported i n 1 9 S 5 . Data on the percent-age of e l e c t r o n i c computers by i n d u s t r y group that were oper-a t i o n a l p r i o r to 1959 and p r i o r to 1965 i s a v a i l a b l e , i n the form of age of o p e r a t i n g e l e c t r o n i c computers. I t i s assumed that the percentage of op e r a t i n g e l e c t r o n i c computers i s d i r e c t l y p r o p o r t i o n a l to the a p p l i c a t i o n of process c o n t r o l by u s i n g e l e c t r o n i c computers f o r each p o i n t i n time. Therefore, \u00b0 * \u00b0 ' 1 9 5 9 \/ \\ P - C ' l 9 5 9 = o T c ^ \" ^ x p- c- 1 9 6 5 . . . . ( l l ) 7 3 . where P.C. = a p p l i c a t i o n of process c o n t r o l u s i n g e l e c t r o n i c computers (per cent) O.C. = operati n g e l e c t r o n i c computers (per cent) . The s u b s c r i p t denotes the year that i s a p p l i c a b l e . The r e s u l t s of the c a l c u l a t i o n s f o r P. 0 . - ^ 5 0 , a r e shown i n Table I l i a . The percentage f i g u r e f o r o p e r a t i n g e l e c t r o n i c computers f o r 1965 i s 100 percent. In the computation of the l e v e l of automation i n i n d u s t r y , the i n d u s t r i e s are ranked i n descending order u s i n g the process c o n t r o l f i g u r e s f o r 1959 that have been computed. On i n s p e c t i o n of the data, i t i s noted that there are s i x i n d u s t r i e s showing zero values f o r a p p l i c a t i o n of process c o n t r o l . This i s about one t h i r d the t o t a l number of i n d u s t r i e s s t u d i e d . I f the i n d u s t r i e s w i t h zero values are a l l o c a t e d to the low category, then i n d u s t r i e s a l l o c a t e d to the h i g h cate-gory have a p p l i c a t i o n of process c o n t r o l values between 3 . 5 and ( 3- 5 2~ \u00b0) = 1 .75 \u2022 The i n d u s t r i e s a l l o c a t e d to the medium category have-applic-ation- of process c o n t r o l values between 1 . 7 5 and zero, as shown i n Table I l i a . An a l t e r n a t i v e method of a l l o c a t i n g i n d u s t r i e s to each category by means of values of a p p l i c a t i o n of process c o n t r o l f a l l i n g w i t h i n the o n e - t h i r d range of the maximum and minimum values have been computed as shown i n Table I l l b . I n d u s t r i e s f a l l i n g w i t h i n each category should possess the 7 4 . TABLE I l i a . COMPUTATION OF LEVEL OF AUTOMATION IN INDUSTRY - PERIOD 1. Industry Process R a t i o of Oper- Process C o n t r o l a t i n g E l e c . Comp. Co n t r o l 1965 1959 to Operat- 1959 (percent) i n g E l e c . Comp. (percent) 1965 L e v e l of Automation i n Industry Petroleum and Coal Products 50 Mining 52 E l e c t r i c a l Machinery 27 Chemicals 21 Stone, Clay and Glass 6 Other Transpo r t a t i o n Equipment . 8 Machinery 23 F a b r i c a t e d Metals and Instruments 17 Nonferrous Metals 13. Misc. Manufacturing 28 Autos, Trucks and Parts 15 Iron and S t e e l 58 Aerospace Paper and Pulp 24. Rubber 25 Food and. Beverages 0 T e x t i l e s 28 7 100 5 100 7 100 7 100 24 100 10 100 . 3 100 3 100 3 100 1 100 1 100 0 100 0 loo 0 100 0 100 0 100 0 100 3 . 5 2 . 5 1 . 8 9 1.47 1 . 4 4 0 . 8 0 . 6 8 0 . 5 1 0 . 3 9 O .28 0 . 1 5 0 0 0 0 0 High Cut o f f P o i n t Medium r C u t o f f \"point Low Source: Control Engineering, V o l . 1 2 , NO, 4 , A p r i l 1 9 6 5 , pp. 67 ,6; 7 5 . f o l l o w i n g range of values of a p p l i c a t i o n of process c o n t r o l : High Category = 3 . 5 to ( 3 - 5 - 3 ' 5 , f \u00b0) = 2 . 3 3 Medium Category = 2 . 3 3 to ( 2 . 3 3 - \u00b0 ) = 1 . 1 7 Low Category = 1 .17 to zero. When Table I l l b i s examined, i t can be seen that approximately two-thirds of the major group and subgroup i n d u s t r i e s f a l l w i t h i n the low category, a l a r g e c o n c e n t r a t i o n of i n d u s t r y groups i n a s i n g l e category. For P e r i o d 2 , computation f o r the a l l o c a t i o n of i n d u s t r i e s to each category u s i n g the o n e - t h i r d range i s shown i n Table I I I c . I n d u s t r i e s f a l l i n g w i t h i n each category should possess the f o l l o w i n g range of values of a p p l i c a t i o n of process c o n t r o l : High Category = 58 to (58 - 5 \u00b0V \u00b0) = 3 8 . 6 7 Medium Category = 3 8 . 6 7 to ( 3 8 . 6 7 - \u2014 - 1 \u2014 ; ) = 1 9 - 3 4 Lovr Category = 1 9 . 3 4 to zero. I t must be noted that the c a t e g o r i z a t i o n of the i n d u s t r i e s to the var i o u s l e v e l s of automation i n i n d u s t r y has been derived from data a p p l i c a b l e f o r that p e r i o d . In c e r t a i n cases, i t may be argued that c e r t a i n i n d u s t r i e s may have been misplaced i n the d i f f e r e n t c a t e g o r i e s . I n the e a r l y stages ; o f the a p p l i c a t i o n of process c o n t r o l u s i n g e l e c t r o n i c computers, snags are p l e n t i f u l and thus making t h i s a p p l i c a t i o n not so 7 6 . TABLE I I l b . COMPUTATION OP LEVEL OP AUTOMATION IN INDUSTRY USING ALTERNATIVE CUTOFF POINTS - PERIOD 1. Industry-Process C o n t r o l 1959 (percent) L e v e l of Automation In Industry Petroleum and Coal Products Mining E l e c t r i c a l Machinery Chemicals Stone, Clay and Glass Other T r a n s p o r t a t i o n Equipment Machinery F a b r i c a t e d Metals and Instruments Nonferrous Metals Misc. Manufacturing Autos, Trucks and p a r t s I r o n and S t e e l Aerospace Paper and Pulp Rubber Food and Beverages T e x t i l e s 3-5 2 . 6 1 . 8 9 1 .47 1 . 4 4 0 . 8 0 . 6 9 0 . 5 1 0 . 3 9 0 . 2 8 0 . 1 5 0 0 0 0 0 0 High C u t o f f P o i n t Medium Cu t o f f P o i n t Low Source: C o n t r o l Engineering, V o l . 1 2 , No. 4 , A p r i l 1 9 6 5 , pp. 67 and 6 9 . 77. TABLE I I I c . COMPUTATION OF LEVEL OF AUTOMATION IN INDUSTRY - PERIOD 2 . Industry Process C o n t r o l 1965 (percent) L e v e l of Automation In Industry Iron and S t e e l Mining Petroleum and Coal Products Aerospace T e x t i l e s Misc. Manufacturing E l e c t r i c a l Machinery Rubber Paper and Pulp Machinery Chemicals F a b r i c a t e d Metals and Instruments Autos, Trucks and Parts Nonferrous Metals Other T r a n s p o r t a t i o n Equipment Stone, Clay and Glass Food and Beverages 58 52 50 46 28 28 27 25 24 23 21 17 15 13 8 6 High C u t o f f P o i n t Medium Cutoff P o i n t l o y 7 Source: C o n t r o l Engineering, V o l . 1 2 , No. 4, A p r i l 1 9 6 5 , P- 6 9 . 7 8 . e f f e c t i v e . One of these i n d u s t r i e s i s pulp and paper. I t 7 has been reported 1 that i n t h i s i n d u s t r y , during P e r i o d 2 , some i n i t i a l t e e t h i n g t r o u b l e s have occurred i n the use of e l e c t r o n i c computers f o r process c o n t r o l . I t appeared that at l e a s t 2 of the e a r l y operators of e l e c t r o n i c computer systems have taken then out of operation. Once these d i f f i c u l t i e s have been s t r a i g h t e n e d out, there i s l i t t l e doubt that the i n d u s t r i e s w i l l be placed i n the c o r r e c t category, but these changes w i l l only be made a f t e r P e r i o d 2 when the data i n d i c -ates t h i s . (b) P r o p e n s i t y to S t r i k e : S t a t i s t i c a l data f o r Periods 1 g and 2 on annual work stoppages and annual average production worker employment l e v e l s f o r major group i n d u s t r i e s can be e x t r a c t e d d i r e c t l y from the p u b l i c a t i o n s of the U.S. Bureau of Labor S t a t i s t i c s . E x t r a computations are necessary f o r groupings of sub-group i n d u s t r i e s or p a i r e d grouping of major group industries\u2022where the data i s comprised of an aggregate r a t h e r than a s i n g l e u n i t . The computations f o r i n d u s t r y groups comprised of groupings of sub-group i n d u s t r i e s or p a i r e d groupings of major group i n d u s t r i e s i s shown i n the f o l l o w i n g t a b l e s : Table IV. Iron and S t e e l Data f o r the i r o n and s t e e l i n d u s t r y i s derived from 7. United S t a t e s , Department of Labor, Bureau of Labor S t a t i s t i c s , B u l l e t i n No. 1474, o p . , c i t . , p. 1 6 2 . 8 . Data on annual work stoppages f o r sub-group i n d u s t r i e s f o r 1951 and 1954 i s not a v a i l a b l e i n the l o c a l l i b r a r i e s . 7 9 . TABLE IV. IRON AND STEEL Production Workers ( i n thousands) Work Stoppages ( i n thousands of man-days) Year B l a s t Furn-aces, S t e e l -works and Basic S t e e l Products Ir o n and S t e e l Found. I r o n and S t e e l \u00a3 Columns ( l ) a n d ( 2 ) B l a s t Furn-aces, S t e e l -works and Basic S t e e l Products Ir o n and S t e e l Found. Iron and S t e e l 2 Columns ( 4)and ( 5 ) ( 1 ) ( 2 ) ( 3 ) ( 4 ) ( 5 ) ( 6 ) 1951 6 2 0 . 2 237 . 3 8 5 7 . 5 n. a. n. a. n. a. 1952 5 4 1 . 5 2 2 6 . 1 7 6 7 . 6 2 0 , 4 0 0 6 2 3 2 1 , 0 2 3 1953 6 2 0 . 4 2 1 7 . 5 8 3 7 . 9 522 462 984 1954 546.1 1 8 2 . 5 7 2 8 . 6 n. a. n. a. n. a. 1955 6 0 4 . 5 2 0 1 . 8 8 0 6 . 3 759 243 1 , 0 0 2 1956 5 9 5 . 4 2 1 1 . 2 8 0 6 . 6 1 1 , 3 0 0 292 1 1 , 5 9 2 1957 6 0 0 . 1 2 0 1 . 0 8 0 1 . 1 436 200 opo 1958 436.5 1 6 2 . 7 649.2 198 347 545 1959 4 7 0 . 9 1 8 1 . 5 6 5 2 . 4 3 6 , 6 0 0 590 3 7 , 1 9 0 i 9 6 0 5 2 8 . 4 173-3 7 0 1 . 7 472 5 4 l 1 , 0 1 3 1961 4 7 8 . 4 150 \u2022 O 6 3 5 . 0 224 162 386 1962 4 7 6 . 3 1 6 3 . 7 64o.O 195 216 411 . 1963 4 7 9 . 1 1 6 8 . 3 647.3 . 285 128 4 l 3 1964 5 1 5 . 8 1 8 1 . 7 . 6 9 7 . 5 181 316 497 1965 54l 193 734 342 513 855 Source: United States, Department of'Labor, Bureau of Labor S t a t i s t i c s , B u l l e t i n s on A n a l y s i s of  Work Stoppages and Employment and Earnings S t a t i s t i c s f o r the United States'. \u2022 n.a. = not a v a i l a b l e . 80. TABLE V. N0NPERR0US METALS Production Workers ( i n thousands) Work Stoppages ( i n thousands of man-days) Year Primary Metal I n d u s t r i e s Iron and S t e e l Nonferrous Metals Column ( l ) minus Column ( 2 ) Primary Metal I n d u s t r i e s I r o n and S t e e l Nonferrous metals\u2022 Column (4) minus Column (5) (1) ( 2 ) (3) (4) (5) (6) 1951 1 , 1 7 5 . 1 8 5 7 . 5 3 1 7 . 6 n. a. n. a. n. a. 1952 1 , 0 8 4 . 7 7 6 7 . 6 317 \u2022 1 2 3 , 0 0 0 2 1 , 0 2 3 1 ,977 1953 1 , 1 7 2 . 6 8 3 7 . 9 3 3 4 . 7 1 ,510 984 526 1954 1 , 0 1 7 . 9 7 2 8 . 6 2 8 9 . 3 n. a. n. a. n. a. 1955 1 , 1 1 5 . 8 8 O 0 . 3 3 0 9 . 5 1 , 5 7 0 1 , 0 0 2 568 1956 1 , 1 3 1 . 6 8 0 6 . 6 3 2 5 . 0 1 2 , 7 0 0 1 1 , 5 9 2 1 , 1 0 8 1957 1 , 1 1 7 . 9 8 0 1 . 1 3 1 6 . 8 1 , 150 636 514 1958 9 2 8 . 0 649.2 2 7 8 . 8 711 545 166 1959 9 5 3 . 8 6 5 2 . 4 3 0 1 . 4 3 9 , 0 0 0 3 7 , 1 9 0 1 , 8 1 0 i 9 6 0 9 9 3 . 8 7 0 1 . 7 2 9 2 . 1 1 , 8 8 0 1 , 0 1 3 867 1961 9 1 4 . 6 6 3 5 . 0 2 7 9 . 6 oo5 386 279 1962 937 . 3 640.0 2 9 7 . 3 872 4 l l 461 1963 9 4 7 . 4 647 . 3 3 0 0 . 1 637 413 . 224 1964 1 , 0 0 3 . 6 6 9 7 . 5 3 0 6 . 1 1 , 0 1 0 497 513 1965 1 , 0 5 7 . 8 734 ' 3 2 3 . 8 . 1 , 3 9 0 855 535 Source: U n i t e d S t a t e s , Department of Labor, Bureau of Labor S t a t i s t i c s , B u l l e t i n s on A n a l y s i s of Work Stoppages and Employment and Earnings S t a t i s t i c s f o r the United States. n.a. = not a v a i l a b l e . 81. TABLE VI. AUTOS, TRUCKS AND PARTS; AEROSPACE,. AND OTHER TRANSPORTATION EQUIPMENT Production workers ( i n thousands) Work Stoppages ( i n thousands of man-days) Year Transport-a t i o n Equipment (1) Autos, Trucks and Parts. (Motor Vehicles and Equipment) (2) Aerospace ( A i r c r a f t and Parts) (3) Other Trans-po r t a t i o n Equipment Column ( l ) minus Columns (2) and (3) (4) Transport-ation Equipment (5) [Autos, Trucks and Parts. (Motor Vehicles and (Equipment) ; (6) Aerospace ( A i r c r a f t and Parts) (7) Other Trans-porta t i o n Equipment Column (5) minus Columns (6) and (7) (8) 1951 1,213.1 681.8 348.4 182.9 n.a. n. a\u00bb n. a. n.a. 1952 1,331.4 618.7 495.4 217-3 2,230 684 927 ' 619 1953 1,542.9 739.4 586.2 217.3 2,730 781 1,350 599 1954 1,331.4 601.5 560.2 169.7 n.a. n.a. n. a. n.a. 1955 l , 4 l 4 . l 718.3 525.5 170.3 1,910 1,210 403. . '297 1956 1,364.3 619.5 561.0 183.8 1,800 495 1,040 .265 1957 1,395.0 ; 601.7 591.4 201.9 1,170 860 88.2 221.8 1958 1,120.6 452.5 491.9 176.2 4,310 3,870 308 132 1959 1,163.4 . 537.5 445.7 180.2 1,390 367 312 711 i960 . 1,107.4 563.3.. 369.6 174.5 3,550 487 1,190 1,873 1961 992.7 479.1 347.7 165.9 2,500 2,240 35.6 224.4 \u202219.6 2 1,059.9 534.O 349.1 176.8 1,410 650 555 205 1963 1,112.3 573.6 350.8 187.9 678 523 53.7 101.3 1964 1,119-6 579.2 \u2022338.6 201.8 6,410 5,920 160 330 1965 1,238.1 659.5 357.0 221.6 2,630 868 946 816 Source: United States, Department of Labor, Bureau of Labor S t a t i s t i c s , B u l l e t i n s on Analysis of Work Stoppages and, Employment and  Earnings S t a t i s t i c s f o r the United States. i i . a . - not a v a i l a b l e . 8 2 . TABLE V I I . FABRICATED METALS AND INSTRUMENTS Production Workers ( i n thousands) Work Stoppages ( i n thousands of man-days) Year F a b r i c -ated Metal Products: (1) I n s t r u -ments and Related Products ( 2 ) F a b r i c a t e d Metals, and Instruments Columns (1 ) and ( 2 ) ( 3 ) F a b r i c -ated Metal Products (4) I n s t r u -ments, and Related Products ( 5 ) . F a b r i c a t e d Metals and Instruments Columns (.4) and (5) ( 6 ) 1951 883.O 2 2 2 . 5 1 , 1 0 5 . 3 1 , 5 0 0 127 1 ,427 1952 8 5 9 . 4 2 5 5 . 2 1 , 0 9 2 . 6 2 , 4 5 0 297 2 ,727 1953 9 3 7 - 4 2 4 9 . 8 1 , 1 8 7 , 2 1 , 6 9 0 246 \u2022 1 , 9 5 6 1954 8 5 1 . 1 2 5 1 . 0 1 , 0 8 2 . 1 1 , 2 0 0 145 1 , 3 4 5 1955 8 9 7 . 8 2 2 9 . 6 1 , 1 2 7 - 4 1 , 5 9 0 694 2 , 2 8 4 1956 9 0 0 . 7 2 5 6 . 1 1 , 1 3 6 . 8 1 , 4 2 0 134 1 , 5 5 4 1957 9 1 5 . 2 2 5 5 . 1 1,146 .5 7 1 5 202 915 1958 8 2 4 . 5 214 .8 1 , 0 3 9 . 5 1 , 2 2 0 235 1 , 4 5 5 1959 8 6 8 . 5 2 5 0 . 5 1 , 0 9 8 . 8 5 , 1 5 0 158 5 , 5 0 8 i 9 6 0 8 7 4 . 5 2 5 2 . 6 1 , 1 0 6 . 9 579 9 4 . 8 6 7 5 . 8 1961 8 2 6 . 0 2 2 5.I 1 , 0 4 9 . 1 1 , 1 3 0 170 1 , 5 0 0 1962 8 6 5 . 7 2 2 9 . 1 1 , 0 9 2 . 8 651 4 l 8 1 , 0 5 9 1963 8 8 1 . 6 2 5 2 . 5 1 , 1 1 5 - 9 516 122 658 . 1954 9 1 4 . 0 2 5 4 . 0 1,148 .0 1,550 170 1,720 1965. 9 8 2 . 4 247 . 5 1 , 2 2 9 . 7 1 , 4 3 0 109 1 , 5 5 9 Source: United S t a t e s , Department of Labor, Bureau of Labor S t a t i s t i c s , B u l l e t i n s on A n a l y s i s o f  Work Stoppages and Enployment and Earnings S t a t i s t i c s f o r the United States. 83. the aggregate of two sub-group i n d u s t r i e s . One c o n s i s t s of b l a s t furnaces, steelworks and b a s i c s t e e l products and the other of i r o n and s t e e l f o u n d r i e s . Table V. Nonferrous metals. The primary metal i n d u s t r i e s are composed of the sub-group i n d u s t r i e s , i r o n and s t e e l , and nonferrous.metals. Data, on nonf errous metals i s obtained as the r e s i d u a l from the primary metal i n d u s t r i e s a f t e r the values f o r the i r o n and s t e e l i n d u s t r y have been deducted. The nonferrous metal i n d u s t r y c o n s i s t s of primary and secondary sm e l t i n g , r e f i n i n g , r o l l i n g , drawing and a l l o y i n g of nonferrous metals, non-f e r r o u s foundries and miscellaneous primary metal i n d u s t i e s . Table VI. Autos, Trucks and P a r t s ; Aerospace  and Other T r a n s p o r t a t i o n Equipment. The major gro\\ip i n d u s t r y , t r a n s p o r t a t i o n equipment, c o n s i s t s of the sub-group i n d u s t r i e s autos, trucks and p a r t s ; aerospace, and other, t r a n s p o r t a t i o n equipment. Data f o r autos, trucks and p a r t s , and aerospace can be recorded d i r e c t l y from the sources of the data. The data on other t r a n s p o r t a t i o n equipment i s computed as the r e s i d u a l from the t r a n s p o r t a t i o n equipment major group i n d u s t r y a f t e r the values f o r autos, trucks and p a r t s , and aerospace have been deducted. The other t r a n s p o r t a t i o n equipment i n d u s t r y con-s i s t s of ship and boat b u i l d i n g and r e p a i r i n g , and r a i l r o a d equipment. 84. TABLE V i l l a . PRODUCTION WORKERS EMPLOYED IN INDUSTRY DURING YEAR - PERIOD 1. 1951 1952 195 3 19! 54 1955 1956 1957 1958 1959 Industry-Production Workers (1000) Ranking Production Workers (1000) Ranking Production Workers (1000) Ranking Production Workers (1000) Ranking Production Workers (1000) Ranking Production Workers (1000) Ranking Production Workers (1000) Ranking Production Workers (1000) Ranking Production Workers (1000) Ranking Iron and Steel 858 6 768 7 838 6 729 6 806 6 ! 807 6 801 6 649 6 652 6 Nonferrous Metals 318 14 317 14 335 14 289 14 310 14 325 14 317 x5 279 14 301 14 Machinery 1,130 3 1,164 2 1,183 3 1,046 3 1,069 3 1,159 2 1,143 3 946 3 1,027 3 E l e c t r i c a l Machinery 866 5 . 909 5 1,029 5 884 5 924 5 975 4 959 4 857 4 969 4 Autos, Trucks and Parts 682 8 619 8 739 8 602 8 718 7 620 8 602 8 453 12 538 8 Aerospace 348 12 495 10 586 9 560 9 526 9 561 9 591 9 492 9 446 12 Other Transportation Equipment 183 16 217 16 217 16 170 16 170 16 184 16 202 16 176 16 180 16 Fabricated Metals and Instruments 1,105 4 1,093 3 1,187 2 1,082 2 1,127 2 1,137 3 1,145 2 1,039 2 1,099 2 Chemicals 503 10 506 9 523 10 503 10 518 10 526 IP 519 10 494 8 506 9 Paper and Pulp 435 11 422 12 443 12 44l 12 454 12 465 12 463 12 454 11 472 11 Rubber 271 15 270 15 288 15 257 15 288 15 291 15 290 15 264 15 290 15 Stone, Clay and Glass 507 9 480 11 . 494 11 464 11 495 11 507 11 493 11 458 10 496 10 Petroleum and Coal Products 173 17 169 17 173 17 167 17 163 17 ; 161 17 157 17 147 17 l4o 17 Food and Beverages 1,338 1 1,331 1 1,330 1 1,297 1 1,292 1 1,302 1 1,263 1 1,222 1 1,222 1 T e x t i l e s 1,146 2 1,073 4 1,064 4 953 4 962 4 944 5 893 5 833 5 857 5 Misc. Manufacturing 346 13 333 13 357 13 327 13 330 13 j 333 13 315 14 300 13 313 13 Mining 840 7 801 6 765 7 686 7 680 8 1 701 7 695 7 611 7 590 7 Source: United States, Department of Labor, Bureau of Labor S t a t i s t i c s , B u l l e t i n on Employment and Earnings S t a t i s t i c s f o r the United States. 85. TABLE VHIb. PRODUCTION WORKERS EMPLOYED IN INDUSTRY DURING YEAR PERIOD 2. I960 1961 1962 1963 1964 1965 Industry Production Workers (1000) Ranking Production Workers (1000) Ranking Production Workers (1000) Ranking Production Workers (1000) Ranking Production Workers (1000) Ranking Production Workers (1000) Ranking : Iron and Steel 702 6 635 6 640 6 647 6 697 6 734 6 Nonferrous Metals 292 15 280 15 297 15 300 15 306 15 324 15 Machinery 1,036 3 976 4 1,038 4 1,059 3 1,120 3 1,208 2 E l e c t r i c a l Machinery 996 4 979 3 1,051 3 1,034 4 1,037 4 1,140 4 Autos, Trucks and Parts 563 8 479 9 534 7 574 7 579 7 660 7 Aerospace 370 12 348 12 349 12 351 12 339 12 357 13 Other Transportation Equipment 175 16 166 16 177 16 188 16 202 16 222 16 Fabricated Metals and Instruments 1,107 2 1,049 2 1,093 2 1,114 2 1,148 2 1,230 1 Chemicals 510 9 505 8 519 8 525 8 529 8 545 8 Paper and Pulp 480 11 478 10 486 10 486 10 489 11 499 10 Rubber 293 14 288 14 317 13 323 13 336 13 367 12 r Stone, Clay and Glass 492 10 469 11 478 11 484 11 494 10 504 9 Petroleum and Coal Products 138 17 130 17 126 17 120 17 114 17 112 17 Food and Beverages 1,212 1 1,190 1 .1,178 1 1,167 1 1,157 1 1,155 3 T e x t i l e s 835 5 805 5 812 5 793 5 798 5 823 5 Misc. Manufacturing 314 13 304 13 313 14 310 14 318 14 33T 14 Mining 570 7 532 7 512 9 498 9 497 9 492 11 Source: United States, Department of Labor, Bureau of Labor S t a t i s t i c s , B u l l e t i n on Employment and Earnings S t a t i s t i c s f o r the U.S. I 1 ir \u2022- \u2022 * \u2022 \u2014\u2022 TABLE IXa. WORK STOPPAGES OCCURRING IN INDUSTRY DURING YEAR PERIOD 1. 8 6. 19 51 195\u00a3 > 1953 1954 1955 1956 1957 1958 1959 Industry Work Stoppages (1000 man-days) Ranking Work Stoppages (1000 man-days) Ranking Work Stoppages (1000 man-days) Ranking Work Stoppages (1000 man-days) Ranking Work Stoppages (1000 irian-days) Ranking Work v Stoppages (1000 man-days) Ranking Work Stoppages (1000 man-days) Ranking Work Stoppages (1000 man-days] Ranking Work Stoppages (1000 man-days] Ranking Iron and Steel n. a. 21,023 1 984 6 n.a. 1,002 7 11,592 1 636 5 545 7 37,190 1 Nonferrous Metals n. a. 1,977 5 526 12 n. a. 568 10 1,108 6 514 8 166 12 1,810 6 Machinery 3,370 3,990 3 2,150 1 1,350 3,800 1 3,630 2 1,380 1 2,760 2 2,820 4 E l e c t r i c a l Machinery 1,040 1,180 7 1,620 3 1,010 3,300 2 3,050 3 785 4 1,030 5 820 9 Autos, Trucks and Parts n. a. 684 14 781 9 n.a. 1,210 5 495 11 860 3 3,870 1 367 14 Aerospace n. a. 927 10 1,350 4 n. a. 403 13 1,040 7 88 17 308 9 312 15 Other Transportation Equipment n. a. 619 16 599 10 n.a. 297 14 265. 15 222 14 132 16 711 10 Fabricated Metals and Instruments 1,427 2,727 4 1,936 2 1,345 2,284 y 1,554 4 915 2 1,453 3 3,308 3 Chemicals 201 621 15 825 8 159 634 9 399 381 10 318 8 422 13 Paper and Pulp 494 815 12 222 16 77 197 15 233 16 256 11 . 252 11 442 12 Rubber 700 912 11 493 13 1,620 490 12 580 9 420 9 147 13 1,930 5 Stone, Clay and Glass 231 810 13 316 14 300 495 11 994 8 614 6 1,200 4 1,230 8 Petroleum and Coal Products 56 1,110 8 105 17 50 51 17 174 17 233 13 141 - 14 550 11 Food and Beverages 819 1,250 6' 1,210 5 694 974 8 513- 10 574 7 661 6 1,720 7 T e x t i l e s 3,490 1,070 9 593 11 573 1,400 4 426 12 212 15 111 17 229 16 Misc. Manufacturing 195 \u2022224 17 280 15 186 191 16 295 14 201 16 141 14 179 17 2 Mining 1,290 4,310 2 846 7 845 1,080 6 1,320 5 240 12 302 10 5,650 Source: United States, Department of Labor, Bureau of B u l l e t i n s on Analysis of Work Stoppages. Labor S t a t i s t i c s , n.a. = not a v a i l a b l e 87. ( \"' ' TABLE IXb. WORK STOPPAGES OCCURRING IN INDUSTRY DURING YEAR PERIOD 2. i . . ' . . . \u2022 I960 1961 1962 1963 1964 1965 Industry Work Stoppages (1000 man-days) Ranking Work Stoppages (1000 man-days) Ranking Work Stoppages (1000 man-days) Ranking Work Stoppages (1000 man-days) Ranking Work Stoppages (1000 man-days) Ranking Work Stoppages (1000 man-days) Ranking Iron and Steel 1,013 5 386 8 411 12 413 10 497 9 855 7 Nonferrous Metals 867 6 279 12 .461 10 224 12 513 8 535 12 Machinery 1,240 3 1,240 3 1,200 1 845 2 1,140 3 1,870 1 E l e c t r i c a l Machinery 1,260 2 716 4 631 6 835 3 859 5 795 10 Autos, Trucks and Parts 487 10 2,240 1 650 5 523 5 5,920 1 868 6 Aerospace 1,190 4 36 17 555 8 54 17 160 15 946 3 Other Transportation Equipment 1,873 1 224 13 205 14 101 15; 330 13 816 9 Fabricated Metals and Instruments 674 8 1,300 2 1,069 2 638 4 1,720 2 1,539 2 Chemicals 314 11 441 7 767 4 481 6 337 12 737 11 Paper and Pulp 136 14 324 9 436 11 146 14 580 7 931 4 Rubber 261 12 215 14 159 16 1,100 1 452 10 443 13 Stone, Clay and Glass 228 13 458 6 318 13 459 8 412 11 836 8 Petroleum and Coal Products 80 15 316 10 522 9 338 11 164 14 33 17 Food and Beverages 651 9 589 5 6l4 7 444 9 866 4 928 5 Textiles 34 17 39 16 100 17 193 13 124 174 15 Misc. Manufacturing 74 16 125 15 178 15 95 16 146 16 164 16 Mining 700 7 310 11 983 3 481 6 808 6 431 14 Source: . United States, Department of Labor, Bureau of Labor Statistics, Bulletins on Analysis of Work Stoppages. 88. Table V I I . F a b r i c a t e d metals and instruments. This i s a p a i r e d grouping of the major group i n d u s t r i e s the f a b r i c a t e d metal products Industry and the instruments and r e l a t e d products i n d u s t r y . The f o l l o w i n g t a b l e s have been compiled to determine the c u t o f f p o i n t s denoting each of the three c a t e g o r i e s of the p r o p e n s i t y to s t r i k e . The a. t a b l e s r e f e r to P e r i o d 1 and the b. ta b l e s r e f e r to P e r i o d 2. Table V I I I . Production Workers Employed i n Industry during Year. .The annual average values of the pr o d u c t i o n worker employment l e v e l s are recorded a g a i n s t the corresponding i n d u s t r y f o r the p a r t i c u l a r year. The i n d u s t r i e s are then ranked i n descending order according to the s i z e of the values. Table IX. Work Stoppages o c c u r r i n g i n Industry  during Year. The same procedure i s repeated here except that work stoppages data, i s used i n s t e a d of pr o d u c t i o n worker data. Table X. Ranking of Production Workers and Work  Stoppages among I n d u s t r i e s . The rankings of prod u c t i o n workers among I n d u s t r i e s i n Table V I I I and the rankings of work stoppages among i n d u s t r i e s i n Table IX are brought together i n Table X. f o r each year. The d i f f e r e n c e between the ranking Of p r o d u c t i o n workers and the\"\"ranking of work stoppages f o r corresponding i n d u s t r i e s are 89. \u2022TABLE Xa. RANKING OP PRODUCTION WORKERS AND WORK STOPPAGES AMONG INDUSTRIES PERIOD 1. 1951 1952 1953 1954 . 1955 1956 1957 195 8 1959 Industry-P S P-S P S ! P-S P S P-S P S P-S P S P-S P S P-S P S P-S S P-S P S P-S Iron and Steel 7 1 6 6 6 0 6 7 -1 6 1 5 6 5 \u20221 6 7 -1 6 1 5 Nonferrous Metals 14 5 9 14 12 2 14 10 4 14 6 8 13 8 5 14 12 2 14 6 8 1 Machinery 2 3 -1 3 1 2 3 1 2 2 2 0 3 1 2 3 2 1 3 4 -1 E l e c t r i c a l Machinery 5 7 -2 5 3 2 5 2 3 4 3 1 4 4 0 4 5 -1 4 9 -5 Autos, Trucks and Parts 8 14 -6 8 9 -1 7 5 2 8 11 -3 8 3 5 12 1 11 8 14 -6 Aerospace 10 10 0 9 4 5 9 13 -4 9 7 2 9 17 -8 9 9 0 12 15 -3 Other Transportation Equipment 16 16 0 16 10 6 16 14 2 .16 15 1 16 14 2 16 16 0 16 10 6 Fabricated Metals and Instruments n 3 4 -1 2 2 0 : n. a. 2 3 -1 3 4 -1 2 2 0 2 3 - l ; 2 3 -1. Chemicals 9 15\" -6 10 8 2 10 9 1 10 13 -3 1.0 10 0 8 8 0 9 13 -4 Paper and Pulp 12 12 0 12 16 -4 12 15 -3 12 16 -4 12 11 1 11 11 0 11 12 -1 Rubber 15 11 4 15 13 2 15 12 3 15 9 6 15 9 6 15 13 2 15 5 10 Stone, Clay and Glass 11 13 -2 11 14 -3 11 11 0 11 8 3 11 6 5 10 4 6 10 8 2 Petroleum and Coal Products 17 8 9 17 17 0 17 17. 0 17 17 0 17 13 4 17 14 3 17 11 6 Food and Beverages 1 6 -5 1 5 -4 1 8 7 1 10 -9 1 7 -6 1 6 -5 1 7 -6 T e x t i l e s 4 9 -5 4 11 -7 4 4 0 5 12 -7 5 15 -10 5 17 -12 5 16 -11 Mi s c. Manufac turing 13 17 -4 13 15 -2 13 16 -3 13 14 -1 14 16 -2 13 14 -1 13 17 -4 Mining 6 2 4 7 7 0 8 6\" 2 7 5 2 7 12 -5 7 10 -3 7 2 5 P = Ranking of Production Workers among Industries S = Ranking of Work Stoppages among Industries, n.a. = not available 90. TABLE Xb. RANKING OP PRODUCTION WORKERS-AND WORK STOPPAGES AMONG INDUSTRIES PERIOD 2. Industry-I960 1961 1962 1963 1964 1965 P S P-S P s P-S P s P-S P s P-S P s P-S P S P-S Iron and Steel 6 5 1 6 8 -2 6 12 -6 6 10 -4 6 9 -3 6 7 -1 Nonferrous Metals 15 6 9 15 12 3 15 10 5 15 12 3 15 8 7 15 12 3 Machinery 3 3 0 4 3 1 4 1 3 3 2 1 3 3 0 2 1 1 . E l e c t r i c a l Machinery 4 2 2 3 4 -I 3 6 -3 4 3 . 1 4 5 -1 4 10 -6 Autos, Trucks and Parts 8 10 -2 9 1 8 7 5 2 7 5 2 7 1 6 7 6 1 Aerospace 12 4 8 12 17 -5 12 8 4 12 17 -5 12 15 -3 13 3 10 \\ Other Transportation Equipment 16 1 15 16 13 3 16 14 2 16 1.5 1 16 13 3 16 9 7 Fabricated Metals and Instruments 2 8 -6 2 2 0 2 2 0 2 4 -2 2 2 0 1 2 -1 Chemicals 9 11 -2 8 7 1 8 4 4 8 6 2 8 12 -4 8 11 -3 Paper and Pulp 11 14 -3 10 9 1 10 11 -1 10 14 -4 11 7 4 10 4 6 Rubber 14 12 2 14 14 0 13 16 -3 13 1 12 13 10 3 12 13 -1 Stone, Clay and Glass 10 13 -3 11 6 5 11 13 -2 11 8 3 10 11 -1 9 8 . 1 Petroleum and Coal Products 17 15 2 17 10 7 17 9 8 17 11 6 17 14 3 17 17 0 Food and Beverages 1 9 -8 1 5 -4 1 7 -6 1 9 -8 1 4 -.3 3 5 -2 T e x t i l e s 5 17 -12 5 16 -11 5 17 -12 5 13 -8 5 17 -12 5 15 -.10 Mls c. Manufac turing 13 16 . -3 13 15 -2 14 15 -1 14 16 -2 14 16 -2 14 16 -2 Mining 7 7 0 7 11 -4 9 3 6 0 6 3 9 6 3 11 14 -3 P = Ranking of Production Workers among Industries. S = Ranking of Work Stoppages among Industries. 91. TABLE XIa. FREQUENCY OP |P-S| . PERIOD 1. ip-sl Frequency of P-S| During Year \u2022 Horizontal Total Average of Horizontal Total Cumulative Average of Horizontal Total 1 1 1951 1952 1953 1954 1955 1956 1957 1958 1959 0 3 4 3 2 3 4 - 19 4 1 2 1 3- 4 2 5 3 20 2 \u2022 2 6 4 2 3 2 1 20 4 3 - 1 4 3 2 1 11 10 4 3 2 2 1 1 - 2 11 5 2 1 - 1 4 . 1 3 12 6 n.a. 3 1 n.a. - 1 2 1 4 12 15 7 -. 1 1 1 - - - 3 3 7 15? 8 \u2022- - - 1 1 - 3 3 \u2022 7 1 57 9 2 - - 1 - - - 3 3 7 16^ 10 - - . - - 1 - 1 2 2 7 11 - - - - - 1 1 2 2 7 12 - - - - - 1 - 1 l 7 17 V e r t i c a l T o t a l n.a. 17 17 n. a. 17 17 17 17 17 119 17 Cutoff Point P = Ranking of Production Workers among Industries. S = Ranking of Work Stoppages among Industries, n.a. = not ava i l a b l e Assume P-S <_ | l | = Medium TABLE Xlb. FREQUENCY OF j P-S| . PERIOD 2. I P - S ! Frequency of .I.P-SI During Year Horizontal Average of Horizontal Cumulative Average of Horizontal 1 r I960 1961 1962 1963 1964 1965 T o t a l Total Total 0 2 2 1 - 2 1 8 ' 3 1 1 4 2 3 2 6 18 3 2 5 2 4 \" V i 2 17 3 2 3 3 \u2022 7 3 21 xof - 2 2 2 2 - 8 12 i 5 - 2 1 1 - 4 2 3 12| 3 6 1 - 3 1 1 ' 2 8 14 7 - 1 - - 1 1 3 1 2 8 2 1 1 2 - - 6 1 151 9 1 - - - - - 1 1-F 10 S - - - - 2 2 1 3 16 11 - 1 - - - - 1 1 o\" 12 1 1 1 1 - 4 2 3 12 - - . - - - -14 - \u2022 - - - - - - -15 1 - - - - - 1 1 F 17 V e r t i c a l T o t a l 17 17 17 17 17 \u202217 102 17 . \u2014 ; _ , Cutoff Point P = Ranking, of Production Workers among Industries 4^ < < S = Ranking of Work Stoppages among Industries A s s u m e p _ g < ( 2 j _ M e d \u00b1 u m 9 3 -computed. Table XI. Frequency of |P-S|. |P-S[ denotes the absolute value i r r e s p e c t i v e of s i g n of P-S , where P i s the ranking of pr o d u c t i o n workers among i n d u s t r i e s and S i s the ranking of work stoppages among i n d u s t r i e s . The frequencies of |P-S| are compiled f o r each year. For each p e r i o d , the frequencies of j P-S J are t o t a l l e d and then averaged by d i v i d i n g by the number of years of data a v a i l a b l e vii t h i n that p e r i o d . A cumulative average of t h i s t o t a l i s compiled. The c r i t e r i o n f o r e s t a b l i s h i n g the l i m i t s to each category of the p r o p e n s i t y to s t r i k e i s determined by ensuring that o n e - t h i r d of the count on the frequency of the p r o p e n s i t y to s t r i k e values f a l l w i t h i n the medium category. The |P-S| value that w i l l be chosen to maintain t h i s c r i t e r i o n can be obtained by comparing the cumulative average of the frequencies of |P-Sf agai n s t the numerical f i g u r e which i s o n e - t h i r d the t o t a l number of i n d u s t r y groups in. the study. There are 17 i n d u s t r y groups and o n e - t h i r d of t h i s i s I I - R 2 3 ~ O * In P e r i o d 1, Table XIa. i n d i c a t e s that t h i s value corresponds approximately w i t h that value of the cumulative average of the frequencies of \u2022 ]P-S| f o r |P-S| = 1 . Thus, the medium category of the p r o p e n s i t y to s t r i k e w i l l be scored when i n d u s t r i e s have values of P-S l e s s than or equal to the absolute value of 1 f o r each year i n P e r i o d 1. 94. In P e r i o d 2, Table X l b . i n d i c a t e s that the v a l i i e 1 7 2 of = 5 ^ l i e s between the values of the cumulative average of the frequencies of |P-S| f o r |P-S| = 1 and | P - S | = 2 . I f |P-S| = 1 i s chosen as the c r i t e r i o n f o r the medium category, then the weights are higher i n the high and low ca t e g o r i e s and lower i n the medium category. I f |P\u2014 S| = 2 i s chosen, the weight i n the medium category i s higher than that i n the high and low c a t e g o r i e s . I t i s proposed to define the medium category f o r P e r i o d 2 by u s i n g P-S values that are l e s s than or equal to the absolute value of 2 . Before the t e s t of the n u l l hypothesis, H q , can be c a r r i e d out, i t i s necessary that the data be compiled i n the form of a three by three contingency t a b l e as proposed. This has been c a r r i e d out i n the f o l l o w i n g t a b l e s where the a. and b. t a b l e s are f o r P e r i o d 1 and the c. t a b l e i s f o r Pe r i o d 2. Table X I I . L e v e l of Automation i n Industry against  P r o p e n s i t y to S t r i k e . For P e r i o d 1, Tables X l l a . and X l l b . are compiled from data derived from Tables I l i a , and I l l b . and Table Xa. Each category of p r o p e n s i t y to s t r i k e contains sub-unit c e l l s f o r each year w i t h i n the p e r i o d f o r each i n d u s t r y . The c r i t e r i o n f o r the s c o r i n g f o r the medium category have been defined. The high category i s scored when the i n d u s t r i e s possess values of P-S greater than the p o s i t i v e value of 1 i n the p o s i t i v e range, that i s , the ranking of pr o d u c t i o n workers i s lower ( l a r g e r numerical value) than the ranking of I TABLE JCIIa. LEVEL OP AUTOMATION IN INDUSTRY AGAINST PROPENSITY TO STRIKE - PERIOD 1. i 1 . i Industry Propensity to Strike High ' 5 1 '52 '52 ' 5 4 ' 5 5 ' 5 6 '57 ' 5 8 ' 5 9 Medium .'51 1 5 2 ' 5 3 ' 5 4 ' 5 5 ' 5 6 ' 5 7 ' 5 8 ' 5 9 Low '51 ' 5 2 ' 5 3 ' 5 4 ' 5 5 ' 5 6 ' 5 7 ' 5 8 ' 5 9 Btvel of Automation In Industry Xi \u00a3 Petroleum and Coal Products Mining E l e c t r i c a l Machinery 1 . I l l 1 1 1 1 1 1 10 1 1 1 1 1 1 1 7 1 1 1 1 4 21 Btvel of Automation In Industry \u2022 H T3 OJ S Chemicals Stone, Clay and Glass Other Transport-ation Equipment Machinery Fabricated Metals and Instruments Nonferrous Metals Misc. Manufactur-ing Autos, Trucks and Parts 1 . 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 . 1 1 22 1 1 1 1 1 1 1 I 1 1 1 I I 1 1 1 1 1 1 1 1 21 I 1 1 1 1 I I 1 1 1 1 1 1 13 5 6 Btvel of Automation In Industry o Iron and Steel Aerospace Paper and Pulp Rubber Food and Beverages Textiles 1 1 1 1 1 1 1 1 1 1 1 1 12 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 19 42 \u2014 . \u2014 _ _ \u2022 4 4 3 9 . 3 6 Defining Propensity to Strike Categories. P-S > - 1 = Low P-S <. | l | = Medium P-S > 1 = High 96. TABLE X l l b . LEVEL OP AUTOMATION IN INDUSTRY (ALT. CUTOFF POINTS) AGAINST PROPENSITY TO STRIKE - PERIOD 1. Industry-Propensity to Strik e High '51 '52 '53 '54 '55 *56 '57 '58 '59 Medium '51 '52 '53 '54 '55 '56 '57 '58 '59 Low '51.'52 '53 '54 '55 \u00bb56 '57 '58 '59 w Petroleum and Coal Products Mining 1 1 1 8 1 1 S u -p w c O \u2022H -P o -P o H > CD H i E l e c t r i c a l Machinery| Chemicals Stone, Clay and Glass 1 1 1 1 1 1 1 1 1 1 1 1 7 1 1 1 1 1 1 o Other Transport-a t i o n Equipment Machinery Fabricated Metals and Instruments Nonferrous Metals Mi s c. Manufac tur-i n g Autos, Trucks and Parts Iron and Steel Aerospace Paper and Pulp Rubber Food and Beverages T e x t i l e s 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 29 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 28. 1 1 1 1 1 1 1 1 1 1 1 27 Defining Propensity to Strik e Categories. P-S > - 1 = Low P-S <. | l | = Medium P-S > 1 \u00ab= High 44 39 36 TABLE ; >XIIc. LEVEL OP AUTOMATION IN INDUSTRY AGAINST PROPENSITY TO STRIKE - PERIOD 2. Industry Propensity to Strik e High '60 '61 '62 '63 '64 '65 Medium '60 '61 '62 '63 \u00ab64 '65 Low '60 '61 '62 '63 '64 '65 \u2022 Level of Automation in Industry Xi Iron and Steel Mining Petroleum and Coal Products Aerospace 1 1 1 1 1 1 1 1 1 1 10 1 1 1 1 1 1 6 1 1 1 1 1 1 1 1 8 24 Level of Automation in Industry \u2022H TJ 0) s T e x t i l e s Misc. Manufacturing E l e c t r i c a l Machinery Rubber Paper and Pulp Machinery Chemicals 1 1 1 1 1 1 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 22 1 1 1 1 1 1 1 1 1 1 1 1 1 1 14 42 Level of Automation in Industry o Fabricated Metals and Instruments Autos, Trucks and Parts Nonferrous Metals Other Transportation Equipment Stone,, ...Clay and Glass Food and Beverages 1 1 1 1 1 1 1 1 1 1 1 1 1 1 14 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 15 1 1 1 1 1 1 1 7 36 : . . 30 43 29 Defining Propensity to St r i k e Categories. P-S > - 2 = Low P-S < |2| = Medium P-S > 2 = High 98. the work stoppages among i n d u s t r i e s . S i m i l a r l y , the low category i s scored when the i n d u s t r i e s possess values of P-S greater than the negative value of 1 i n the negative range, that i s , the ranking of pr o d u c t i o n workers among i n d u s t r i e s i s higher ( s m a l l e r numerical value) than the ranking of the.work stoppages among i n d u s t r i e s . The scores f o r each c e l l are then t o t a l l e d and row and column t o t a l s are computed. The d i f f e r e n c e across the p r o p e n s i t y to s t r i k e , . as i n d i c a t e d by an i n s p e c t i o n of the column t o t a l s , i s approximately.2 2 percent \"between maximum and minimum. The high and low weights are found i n the high and low ca t e g o r i e s r e s p e c t i v e l y . For P e r i o d 2, Table X I I c . i s compiled by repea t i n g the same procedure except that the high category i s scored when the i n d u s t r i e s possess values of P-S g r e a t e r than the p o s i t i v e value of 2 i n the p o s i t i v e range and the low cate-gory i s scored when the i n d u s t r i e s possess values of P-S greater than the negative value of 2 i n the negative range. The d i f f e r e n c e across c a t e g o r i e s of p r o p e n s i t y to s t r i k e i s approximately 48 percent w i t h the medium category a l l o c a t e d a higher weight w h i l e the weights of the other two ca t e g o r i e s are approximately the same. 7. Computation: The t o t a l observed c e l l frequencies f o r each c e l l , 0. . , row t o t a l s , n. , column t o t a l s , n . , and the t o t a l number of frequencies, N t from Tables X l l a . , b. and c. are t r a n s f e r r e d to Tables - X l l l a . . b. 99. and c. r e s p e c t i v e l y . The expected c e l l frequencies f o r each c e l l , E. \u2022 > are computed according to equation (6) and i j i n s e r t e d i n brackets i n each c e l l to d i f f e r e n t i a t e t h i s from 2 the observed c e l l f r equencies. The values of the x c r i t e r i o n and the contingency c o e f f i c i e n t , C , are then computed. TABLE X H I a . LEVEL OP AUTOMATION IN INDUSTRY AGAINST PROPENSITY TO STRIKE CONTINGENCY TABLE -PERIOD 1. P r o p e n s i t y to S t r i k e Row High Medium Low T o t a l omation ry High 10 ( 7 . 7 6 5 ) \u20227 ( 6 . 8 8 2 ) 4 ( 6 . 3 5 3 21 of Auti Indus t: Medium 22 ( 2 0 . 7 0 6 ) 21 ( 1 8 . 3 5 3 ) 13 (16.941) 56 Level in Low 12 ( 1 5 . 5 2 9 ) 11 ( 1 3 . 7 6 5 ) 19 ( 1 2 . 7 0 6 ) 42 Column T o t a l 44 39 36 119 2 _ ( 1 0 - 7 - 7 6 5 ) 2 ( 7 - 6 . 8 8 2 ) 2 ^ ( 4 - 6 . 5 5 5 ) 2 , ( 2 2 - 2 0 . 7 0 o ) 2 \u2022 \" 7 . 7 b 5 6T8B2 ' b . 3 5 3 20.700 ( 2 1 - 1 8 . 5 5 5 ) 2 , ( 1 5 - 1 6 . 9 ^ 1 ) 2 ^ ( 1 2 - 1 5 . 5 2 9 ) 2 , ( 1 1 - 1 5 . 7 6 5 ) 2 18 . 5 5 5 \" I 5 T 9^I ' 1 5 3 2 9 T 15T7o5 + ( 1 9 - 1 2 . 7 0 6 ) 2 1 2 . 7 O b = 0 . 5 4 5 + 0 . 0 0 2 + 0 . 8 7 1 + 0 . 0 8 1 4-O .382 -f O.917 + 0 . 8 0 2 + 0 . 5 5 5 + 3 . 1 1 8 = 7 . 5 7 1 1 0 0 . R e f e r r i n g to Table XXIV. i n the Appendix, on the c r i t i c a l values of the chi-square, u s i n g 4 degrees of free-dom, x 05 ^*as a v a l u e o r\" 9'49 . Therefore 2 x . 0 5 X from, the sampling d i s t r i b u t i o n i s l e s s than I f the l e v e l of s i g n i f i c a n c e , a = . 0 5 i s accepted, then the n u l l hypothesis, H Q , i s not r e j e c t e d . This i n d i c a t e s that there I s no r e l a t i o n s h i p between the l e v e l of automation i n i n d u s t r y and the p r o p e n s i t y to s t r i k e i n P e r i o d 1 . Contingency c o e f f i c i e n t , C V 7.21 .731 71+119 = 0 . 2 4 1 TABLE X H I b . LEVEL OF AUTOMATION IN INDUSTRY USING ALTER-NATIVE CUTOFF POINTS AGAINST PROPENSITY TO STRIKE CONTINGENCY TABLE - PERIOD 1 . P r o p e n s i t y to S t r i k e \" Rov; T o t a l High Medium Low Level of Automation in Industry High 8 (5.175) 4 (4.588) 2 (4 .235) 14 Level of Automation in Industry Medium 7 (7.765) \u2022 7 (6 .882) 7 (6 .353 21 Level of Automation in Industry Low 29 ( 3 1 . 0 5 9 ) 28 (27.529) 27 (25.412) 84 Column T o t a l 44 39 36 119 1 0 1 . In Table X l l l b . an i n s p e c t i o n of the values of the expected c e l l f r e q u e n c i e s , E. . , i n d i c a t e s that i n two c e l l s , the values are l e s s than 5 \u2022 The number-of c e l l s w i t h expected c e l l frequencies of l e s s than 5 i s approximately 22 percent of the t o t a l number of c e l l s . This does not s a t i s f y the requirement that i f the number of degrees of freedom i s gr e a t e r than 1 , then fewer than 20 percent of the c e l l s should possess values on expected frequencies of 9 l e s s than 5\u00ab Since t h i s requirement i s not s a t i s f i e d , f u r t h e r computations f o r t h i s t a b l e are omitted. TABLE X I I I c . LEVEL OP AUTOMATION IN INDUSTRY AGAINST PROPENSITY TO STRIKE CONTINGENCY TABLE - PERIOD. 2. Prop e n s i t y to S t r i k e . Row To t a l High Medium Low Level of Automation in Industry High 10 (7 . 0 5 9 ) 6 (10.118) 8 (6.824) 24 Level of Automation in Industry Medium 6 (12.355) 22 (17.706) 14 (11-941) 42 Level of Automation in Industry Low 14 (10.588) 15 (15 . 1 7 6 ) 7 (10.255) 56 Column T o t a l 50 45 29 102 9- Cochran, op. c i t . , pp. 4 1 8 - 4 2 0 . 1 0 2 . 2 _ ( 1 0 - 7 . 0 5 9 ) 2 j . ( 6 - 1 0 , l l 8 ) 2 , ( 8 - 6 . 8 2 4 ) 2 ( 6 - 1 2 . 5 5 5 ) 2  x - 77059 ' 10.118 T . 6.824\" + 1 2 . 3 5 3 ( 2 2 - 1 7 . 7 0 6 ) 2 ^ (14 - 1 1 .941) 2 ^ ( 1 4 - 1 0 . 5 8 8 ) 2 (15^15-176) :  + 17.705 + 11.941 \" + 1 0 . 5 8 8 + 1 5 . 1 7 b 4 . ( 7-lQ.2 5 5 ) 2  + 10 . 2 3 5 = 1 . 2 2 5 + I . 6 7 6 + 0 . 2 0 3 + 3 . 2 6 7 + 1.041 + 0 . 3 5 5 + 1 . 0 9 9 -:\u2022 + 0.002 + 1.002 = 9 . 8 9 ? P X 05 h a s a v a l u e \u00b0\u00a3 9.49 \u2022 Therefore x from p the sampling d i s t r i b u t i o n i s gre a t e r than x 05 \u2022 I f t h e l e v e l of s i g n i f i c a n c e , a = ' .05 i s accepted, then the n u l l hypothesis, H Q , i s r e j e c t e d . This i n d i c a t e s that there i s a r e l a t i o n s h i p between the l e v e l of automation i n i n d u s t r y and the p r o p e n s i t y to s t r i k e i n P e r i o d 2 . Contingency c o e f f i c i e n t , C = J ^ t j g ^ f g \" = 0 . 2 9 7 2 \u2022 The contingency c o e f f i c i e n t , C , and the x c r i t e r i o n i n d i c a t e s that there i s a s i g n i f i c a n t , though not p a r t i c u l a r l y s t r o n g , c o r r e l a t i o n between the l e v e l of auto-mation i n i n d u s t r y and the pr o p e n s i t y to s t r i k e i n P e r i o d 2. CHAPTER V INTERPRETATION OP THE RESULTS 1. The R e s u l t s : The t e s t of the n u l l hypothesis, H Q , \u2022 s u b s t a n t i a t e d the f a c t that i n P e r i o d 1, the l e v e l of auto-mation i n i n d u s t r y had not reached a stage that would exert a strong b e a r i n g on s t r i k e a c t i v i t y , i f the l e v e l of s i g n i f -icance used i n t h i s study i s accepted. I t i s proposed not to develop the r e s u l t s a r r i v e d at f o r Per i o d 1 any f u r t h e r . In P e r i o d 2, the t e s t of the n u l l hypothesis, H Q , d i d I n d i c a t e that the l e v e l of automation i n i n d u s t r y d i d a f f e c t the p r o p e n s i t y to s t r i k e . R e f e r r i n g to Table X I I I c . on the observed frequency t o t a l s f o r each c e l l , I t w i l l be noted that i n d u s t r i e s w i t h h i g h l e v e l of automation i n d i c a t e a . h i g h a f f i n i t y w i t h h i g h p r o p e n s i t y to s t r i k e [ c e l l ( 1 , 1 ) ] . Medium l e v e l of automation i n d u s t r i e s i n d i c a t e , a high a f f i n i t y w i t h medium p r o p e n s i t y to s t r i k e [ c e l l ( 2 , 2 ) ] , and low l e v e l of automation i n d u s t r i e s i n d i c a t e a high a f f i n i t y w i t h high p r o p e n s i t y to s t r i k e [ c e l l (~5,l)]> The l a s t p a r t of t h i s statement r e q u i r e s f u r t h e r q u a l i f i c a t i o n . Looking at the row designated by low l e v e l of automation i n i n d u s t r y , the medium p r o p e n s i t y to s t r i k e c e l l t o t a l of observed frequencies ( c e l l 5,2) has a s l i g h t l y g r e ater value compared w i t h that of the high p r o p e n s i t y 104. to s t r i k e c e l l t o t a l [ c e l l ( 3 , 1 ) ] . But, on examining the column t o t a l s , i t w i l l he noted that the weight given to the medium p r o p e n s i t y to s t r i k e column i s approximately 45 percent higher than that of the hig h p r o p e n s i t y to s t r i k e column. Table XIV has been compiled to provide a b e t t e r i d e a of the e f f e c t of e q u a l i z i n g the weights of each column, t o t a l , and subsequently amending the observed frequency values found i n each c e l l . TABLE XIV. EFFECT OF EQUALIZING THE COLUMN TOTALS. Propensi t y to S t r i k e Row T o t a l High Medium Low rt o \u2022rH High 10x4 po = 11.3 r 34 = 4.7 \u00b0 29 = 9.4 25.4 f Autom; ndustry Medium ; : 3 4 ox\u2014-pO = 6 . 8 22x|^ = 17.4 I 4 x ^ 29 = 16.4 40.5 Level o in I Low l 4 x ^ po = 15.9 I 5 x | i = 11.9 f%29 = 8 . 2 36 .0 Column Total. 30x4g = p4 43x-g = 34 29>'\u00a7 - 34 102 The eq u a l i z e d column t o t a l value i s ^ = \u2014~\u2014 ^ 34 . To achieve t h i s e q u a l i z a t i o n , each column t o t a l and each c e l l value i s m u l t i p l i e d by an e q u a l i z i n g f a c t o r . The e q u a l i z i n g f a c t o r f o r each column t o t a l i s the same as that f o r each i n d i v i d u a l c e l l appearing i n the same column, and has a value 105. of the new column t o t a l d i v i d e d by the o r i g i n a l column t o t a l value. The e f f e c t of e q u a l i z i n g the column weights does not e f f e c t the statement put forward p r e v i o u s l y . In f a c t , t h i s supports the e x p l a n a t i o n that i n the row i n d i c a t i n g low l e v e l of automation i n i n d u s t r y , the observed c e l l value f o r high p r o p e n s i t y to s t r i k e can be considered to be i n d i c a t i v e of s. higher value than that f o r the observed c e l l value f o r medium pr o p e n s i t y to s t r i k e . According to the d e f i n i t i o n of p r o p e n s i t y to s t r i k e , an i n d i c a t i o n of high p r o p e n s i t y to s t r i k e , c a n be a t t r i b u t e d to an i n c r e a s e i n the values of man-days of i d l e n e s s due to work stoppages, because the values of the. average annual production worker employment l e v e l s are r e l a t i v e l y s t a t i c across the time p e r i o d designated by P e r i o d 2. The i n c r e a s e i n the values of man-days of i d l e n e s s can be due to two causes: 1. Small number of s t r i k e s but each t a k i n g a l o n g d u r a t i o n before a settlement i s reached, on the average. 2. Large number of s t r i k e s but each t a k i n g a short d u r a t i o n before :a settlement i s reached, on the average. Long s t r i k e s are defined here as l a s t i n g l o nger than one month, and short s t r i k e s as l a s t i n g l e s s than one month. An-analysis of supplementary data ha.s been recorded i n Tables XIX., XX., XXI., and XXII. i n the Appendix, to determine the average.number of work stoppages and the average d u r a t i o n of s t r i k e s f o r each c e l l . The r e s u l t s of t h i s 106. computation have been c o l l e c t e d together as shown i n Table XV. appended below, as an a i d i n comparing the r e s u l t s that have been obtained f o r P e r i o d 2 . TABLE XV. CELL VALUES OF AVERAGE NUMBER OF WORK STOPPAGES (UPPER LEFT HALF) AND AVERAGE DURATION OF STRIKES (LOWER RIGHT HALF) - PERIOD 2 . P r o p e n s i t y to S t r i k e High Medium Low 1 Level of Automation in:Industry High 5 9 . 9 y S \/ 3 9 - 8 7 7 - 7 y \/ y \/ 2 0 . 8 82 y \/ \/ : 9 . 5 1 Level of Automation in:Industry Medium 103 y S \/ \/ 2 2 . 3 103 yS \u2022 \/ 1 6 . 2 6 0 . 5 yS \/ 1 3 - 5 1 Level of Automation in:Industry Low o5 X yS 2 0 . 6 144 y\/ 14 . 0 5 1 7 6 . 1 y S y S 1 1 . 2 The average d u r a t i o n of s t r i k e s i s computed as the r a t i o of man-days i d l e due to di s p u t e s , to the number of workers i n v o l v e d 1 . R e f e r r i n g to c e l l ( 1 , 1) and c e l l ( 3 , 1 ) i n Table XV. i t w i l l be noted that'the average d u r a t i o n of s t r i k e s among i n d u s t r i e s i n c e l l ( 1 , 1) i s approximately double that of c e l l ( 3 , 1 ) . But, the average number of work stoppages among 1. Ross and Hartman, op. c i t . , pp. 8-l4. 107. i n d u s t r i e s i n c e l l ( 3 , 1 ) i s higher than, that of c e l l ( 1 , 1 ) . This i n d i c a t e s that the tendency f o r high p r o p e n s i t y to s t r i k e i n i n d u s t r i e s that have a t t a i n e d a hig h l e v e l of automation i s because these i n d u s t r i e s experience on the average, a r e l a t i v e l y small number of s t r i k e s but each extend-i n g over a l o n g d u r a t i o n . On the other hand, i n i n d u s t r i e s that have maintained a low l e v e l of automation, the tendency f o r r e l a t i v e l y high p r o p e n s i t y to s t r i k e i s a t t r i b u t e d to the f a c t that these i n d u s t r i e s experience on the average, a r e l a t i v e l y l a r g e r number of s t r i k e s but each extending over a s h o r t e r d u r a t i o n , compared w i t h the i n d u s t r i e s that have achieved h i g h l e v e l of automation. A study of s t r i k e a c t i v i t y i n the Un i t e d States over a p e r i o d of ten years between 1927 and 1936 had been reported p by Peterson . The r e s u l t s derived from t h i s study i n d i c a t e d that s t r i k e s of short d u r a t i o n had a greater tendency of success from the workers' p o i n t of view than s t r i k e s of lo n g d u r a t i o n . S t r i k e s that l a s t e d l e s s than one month were- con-s i d e r e d to be of short d u r a t i o n and those l a s t i n g one month or more were considered to be of l o n g d u r a t i o n . The longest s t r i k e s have been considered to be l a s t i n g three months or longer. The p r o p o r t i o n of the longest s t r i k e s l o s t by the unions were higher than those l o s t i n lo n g s t r i k e s . 2. Florence Peterson, S t r i k e s i n the Un i t e d S t a t e s , l880- 1936, United S t a t e s , Department of Labor, Bureau of Labor S t a t i s t i c s , B u l l e t i n No. 6 5 1 , 1 9 3 3 , pp. 7 6 - 7 8 . 108. Suppose i t should happen that t h i s trend i n the s t r i k e a c t i v i t y had been continued i n P e r i o d 2 . Then, si n c e s t r i k e s experienced by i n d u s t r i e s w i t h high l e v e l of auto-mation and a s s o c i a t e d w i t h high p r o p e n s i t y to s t r i k e , tended to l a s t f o r a lo n g d u r a t i o n on the average, s t r i k e a c t i v i t y i n these i n d u s t r i e s might tend to be l e s s s u c c e s s f u l from the workers' p o i n t of view. I n d u s t r i e s w i t h low l e v e l of auto-mation that had a. greater a f f i n i t y w i t h high p r o p e n s i t y to s t r i k e experienced s t r i k e s g e n e r a l l y of short d u r a t i o n . S t r i k e a c t i v i t y i n these i n d u s t r i e s might have a g r e a t e r tendency i n a c h i e v i n g success from the workers' p o i n t of view. 2. Factors r e l a t e d to the L e v e l of Automation i n Industry  that tended to i n c r e a s e the d u r a t i o n of s t r i k e s : A n a t u r a l development a r i s i n g from the employment of automation i n i n d u s t r i e s that have achieve a high l e v e l of automation possess excess pr o d u c t i o n c a p a c i t y over general market demands. In t r o d u c i n g automatic equipment i n t o a company r e q u i r e s heavy f i n a n c i a l investments which i n turn are a s s o c i a t e d w i t h metic-ulous p l a n n i n g by the management. I t w i l l be planned f o r automatic equipment to be used f o r a number of years before replacement. To c a t e r f o r the growth of the company, excess p r o d u c t i v e c a p a c i t y w i l l be i n c l u d e d . Some i n d u s t r i e s possess the a b i l i t y of supplying the annual market demand while only o p e r a t i n g the p l a n t s f o r e i g h t or nine months of the year. This reserve of prod u c t i o n c a p a c i t y strengthens the ' a b i l i t y of the management to weather a l o n g s t r i k e . The f e a r of management to take on a s t r i k e i s reduced.. Before a, s t r i k e 1 0 9 . commences, the management i s able to use t h i s excess product-i o n c a p a c i t y to s t o c k p i l e t h e i r i n v e n t o r y . . E x t r a storage space can be rented t e m p o r a r i l y f o r s t o r i n g the excess m a t e r i a l s or equipment produced. The a b i l i t y to use excess pro d u c t i o n c a p a c i t y i s aided by the 1947 amendments to the N a t i o n a l Labor \u20225 R e l a t i o n s Act . This l e g i s l a t i o n i n c l u d e d a requirement f o r s i x t y - d a y s ' n o t i c e of c o n t r a c t t e r m i n a t i o n and t h i r t y - d a y s ' n o t i c e to the government before any s t r i k e a c t i v i t y could commence. This advance warning system i n c r e a s e s the company's a b i l i t y to i n c r e a s e output p r i o r to a s t r i k e . The excess pro d u c t i o n c a p a c i t y due to automation a l s o enables management, a f t e r a s t r i k e , to meet market demands not s a t i s f i e d d u r i n g the s t r i k e . The s t e e l i n d u s t r y has been c i t e d as an example. Market requirements f o r s t e e l a f t e r the k 116 day s t r i k e i n 1959 , were s a t i s f i e d w i t h i n s i x months a f t e r the end of the s t r i k e . This s t r i k e i n v o l v e d h a l f a m i l l i o n trade union members and has been considered as the longest work stoppage caused by unions i n the h i s t o r y of the i n d u s t r y . In s p i t e of t h i s , when the combined net p r o f i t s of the major s t e e l producers had been computed f o r 1 9 5 9 , i t i n d i c a t e d that t h i s was 5 percent higher than that of the previous year. The i n c r e a s e i n the l e v e l of automation i n i n d u s t r y has c o n t r i b u t e d to the change i n the mix between production and nonproduction workers i n the i n d u s t r y . In manufacturing 3 . James L. Stern, \"Discussion. D e c l i n i n g U t i l i t y of the S t r i k e \" , i n I n d u s t r i a l and Labor R e l a t i o n s Review, V o l . 1 8 , No. 1 , Oct. 1964, pp. 62-66. . 4 . Raskin, op. c i t . , pp. 5 5 - 5 7 -110. i n d u s t r i e s , automation has r e s u l t e d i n the r e d u c t i o n of some b l u e - c o l l a r jobs. The mining i n d u s t r y too has been a f f e c t e d . One of the spe c t a c u l a r reductions i n employment l e v e l s has been found i n the c o a l mining i n d u s t r y . In the s o f t c o a l mining i n d u s t r y , i t has been found that w i t h i n 40 years s i n c e World War 1 , employment had been reduced from 7 0 0 , 0 0 0 to l e s s that 2 0 0 , 0 0 0 . In the hard c o a l mining i n d u s t r y , f o r the corresponding p e r i o d , the r e d u c t i o n was from 1 8 0 , 0 0 0 to 1 3 , 0 0 0 . Reduction of some b l u e - c o l l a r jobs would c o n t r i b u t e to the r e d u c t i o n of the s t r e n g t h of unions r e p r e s e n t i n g these workers. Although new jobs have been created by automation, these had been found predominantly among engineers, t e c h n i c i a n s and w h i t e - c o l l a r workers. These workers are hard to organize. A study on the s i g n i f i c a n c e of union members among w h i t e - c o l l a r employees i n the manufacturing I n d u s t r i e s i n d i c a t e d that 8 percent were union members i n I960 . Mining had been i n c l u d e d v\/ith other p u b l i c u t i l i t i e s end c o n s t r u c t i o n and f o r t h i s category, 4 percent of the w h i t e - c o l l a r workers were union members. W i t h i n the l a s t two decades, the r a t i o .of non-pro d u c t i o n workers to t o t a l employment has been i n c r e a s i n g r a p i d l y as shown by data compiled i n Table X X I I I . i n the Appendix. In the aerospace and, petroleum and c o a l products i n d u s t r i e s , there were approximately 2 nonproduction workers 5- Benjamin Solomon and Robert K. Burns, \" U n i o n i z a t i o n of W h i t e - c o l l a r Employees, Extent, P o t e n t i a l and I m p l i c a t i o n s \" , i n The Journal of Business, The Graduate School of Business of the U n i v e r s i t y of Chicago, V o l . XXXVI, No. 2 , Apr. 1 9 6 3 , p. 153-111. to 3 p r o d u c t i o n workers on the average by 1965\u2022 This represents a s u b s t a n t i a l r e s e r v o i r of stand-by work f o r c e p o t e n t i a l . Except f o r l e s s than 10 percent of the t o t a l as i n d i c a t e d p r e v i o u s l y , these nonproduction workers are outside the union b a r g a i n i n g u n i t . This o u t - o f - u n i t p o t e n t i a l work f o r c e can be employed by the management to operate the automated pr o d u c t i o n equipment and s a t i s f y market demands during a s t r i k e . The d i s c u s s i o n , c a r r i e d out i n Chapter I I on the d e t a i l s of s t r i k e a c t i v i t y i n the petroleum i n d u s t r y i n P e r i o d 2, i n c l u d e d data on nonproduction workers o p e r a t i n g the p l a n t during a s t r i k e . The data has been c o l l e c t e d together as shown i n Table XVI, to i n d i c a t e the e f f e c t i v e n e s s of employ-i n g nonproduction workers i n t h i s i n d u s t r y to operate the automatic p r o d u c t i o n equipment when the pr o d u c t i o n workers went on s t r i k e . TABLE XVI. INDICATING EFFECTIVENESS OF NONPRODUCTION WORKERS DURING STRIKES IN THE PETROLEUM INDUSTRY -PERIOD 2 . Year Company L o c a t i o n of R e f i n e r y R a t i o of Non-pro d u c t i o n workers to t o t a l employment Output During S t r i k e (per-centage of p r e - s t r i k e output 1959 American O i l Texas C i t y 1 5 \u20222=. 75 1961 Gulf O i l Port Arthur 1 7 50 1962 S h e l l O i l Houston 1 3 ^ \u2022 1 0 0 1 1 2 . The automated p r o d u c t i o n process has been considered to employ l i t t l e d i r e c t l a b o r to operate. I n d i r e c t l a b o r i s i n the form of maintenance and i n s p e c t i o n a c t i v i t i e s . '. In some automated i n d u s t r i e s , major maintenance work has been contracted out\u00b0 to f i r m s o u t s i d e . This i n c r e a s e s the management's a b i l i t y to operate the p l a n t i n the presence of a s t r i k e . The a b i l i t y of nonproduction workers to operate a s t r i k i n g p l a n t may be dependent upon the l e v e l s of s k i l l r e q u i r e d i n the automated p r o d u c t i o n process. The nonproduction workers are normally b e t t e r t r a i n e d and educated. In some cases, they may be the persons who i n s t r u c t the p r o d u c t i o n workers on how to operate the automated p r o d u c t i o n process. At a p i n c h , these persons can operate the automated pr o d u c t i o n 7 process themselves. In a study c a r r i e d out by B r i g h t , i t has been found that w i t h an i n c r e a s e i n the l e v e l of automation i n i n d u s t r y , there i s a tendency -for s k i l l requirements to be r a i s e d up to a c e r t a i n p o i n t . A f t e r t h i s p o i n t , the p r o d u c t i o n processes are so automated that s k i l l requirements are taken away from the p r o d u c t i o n worker. At h i g h l e v e l s of automation i n i n d u s t r y , i n the m a j o r i t y of cases, s k i l l requirements f o r opera t i n g the p l a n t may be brought to a. minimum. Reports from some st u d i e s i n d i c a t e d that only a few hours are r e q u i r e d to i n s t r u c t the p r o d u c t i o n worker on how to operate the automatic pr o d u c t i o n equipment. With the higher l e v e l of t r a i n i n g and 6 . J. R.. Duncan, '''The Impact of Automation on Bargaining\", i n Canadian Labor, V o l . 1 2 , No. 1 , Jan, 19^7, p. S. 7 . ' James R. B r i g h t , \"Does Automation Raise S k i l l Requirements?\" i n Harvard Business Review, V o l . 3&3 No. 4 , July-August. . 1 9 5 8 , PP- ~ 113. education of the nonproduction worker over that of the product-i o n worker, even i f f u r t h e r i n s t r u c t i o n i s necessary i n order to operate the prod u c t i o n equipment, sho r t e r i n s t r u c t i o n time w i l l only be r e q u i r e d . I f there i s evidence of a pending s t r i k e by the prod u c t i o n workers, the management can conduct t h i s i n s t r u c t i o n during the p e r i o d j u s t p r i o r to the s t r i k e . This w i l l reduce any apprehension that the management may f e e l regarding damage to the expensive equipment\u2022while o p e r a t i n g the s t r u c k p l a n t w i t h r e l a t i v e l y inexperienced personnel. 3\u00ab Comparing some of the r e s u l t s w i t h the General P a t t e r n  of S t r i k e P r o p e n s i t i e s : The i n d u s t r y groups i n t h i s study that are common w i t h those found i n the Kerr and S i e g e l study are mining, t e x t i l e , chemical, manufacturing (general) and, food and kindr e d products. The comparative p r o p e n s i t y to s t r i k e c l a s s i f i c a t i o n values are compiled as shown i n Table XVII. 114. TABLE XVII. COMPARISON OP SOME COMMON RESULTS WITH THE GENERAL PATTERN OP STRIKE PROPENSITIES. Pro p e n s i t y to S t r i k e I n dustry Group P e r i o d 1 P e r i o d . 2 Kerr and Si.egel Study Mining High High High T e x t i l e Low Low Medium High \u2022 Chemical . Not defined Medium Medium Manufac t u r i n g (general) Medium Medium Medium Pood and k i n d r e d products Low Low Medium For Periods 1 and 2 the a l l o c a t i o n of the i n d u s t r y group to the p a r t i c u l a r p r o p e n s i t y to s t r i k e category i s determined by the frequencies of the p r o p e n s i t y to s t r i k e alone f o r the p e r i o d derived from Tables X l l a . and X I I c . I f the frequencies of the p r o p e n s i t y to s t r i k e are predominant i n a p a r t i c u l a r category, then the Industry group i s s a i d to possess that p a r t i c u l a r l e v e l of p r o p e n s i t y to s t r i k e . When the frequencies of p r o p e n s i t y to s t r i k e f a l l e q u a l l y w i t h i n two or three c a t e g o r i e s , then, the p r o p e n s i t y to s t r i k e f o r that i n d u s t r y i s s t a t e d as. not defined. The i n d u s t r y group c o n t a i n i n g manufacturing (general) i s a vague d e s c r i p t i o n as defined i n the Kerr and S i e g e l study. This Industry group i n c l u d e s metal working which i s found i n miscellaneous manufacturing, e l e c t r i c a l machinery,, machinery, f a b r i c a t e d metals and instruments, t r a n s p o r t a t i o n 115, equipment and the primary metal i n d u s t r i e s . The pr o p e n s i t y to s t r i k e f o r t h i s i n d u s t r y group i s c a t e g o r i z e d by aggregat-i n g the predominant category of pr o p e n s i t y to s t r i k e found i n each i n d u s t r y w i t h i n the group. In Table XVII. the d i f f e r e n c e s i n the pr o p e n s i t y to s t r i k e are found i n t e x t i l e and, food and ki n d r e d products. This i n d i c a t e s to some degree that there are some exceptions to the expl a n a t i o n of the general p a t t e r n of s t r i k e p r o p e n s i t i e s . I t i s q u i t e p o s s i b l e that the d i f f e r e n c e s may be due to the time p e r i o d undertaken i n t h i s study i s short or that other f a c t o r s may a f f e c t the general p a t t e r n of s t r i k e p r o p e n s i t i e s . For Periods 1 and 2 , the i n f o r m a t i o n known on the remaining i n d u s t r y groups are i n s u f f i c i e n t to e x p l a i n t h e i r l e v e l s of p r o p e n s i t y to s t r i k e alone as being caused by beh a v i o u r a l environmental f a c t o r s such as i s o l a t i o n and opport-u n i t y to i n t e r a c t w i t h the general community. 4. Development of a Model: A f t e r the d i s c u s s i o n on the vari o u s f a c t o r s that are derived e i t h e r d i r e c t l y or i n d i r e c t l y from the l e v e l of automation i n i n d u s t r y that a f f e c t the pr o p e n s i t y to s t r i k e , i t has been thought appropriate that a model be developed to e x p l a i n the r e l a t i o n s h i p between the two v a r i a b l e s . This model i s shown i n Figure I I . The l e v e l of automation i n i n d u s t r y i s considered to be r e l a t e d to the p r o p e n s i t y to s t r i k e through the outcome of the s t r i k e . I n an i n d u s t r y that has achieved high l e v e l o f FIGURE 2. LEVEL OF AUTOMATION IN INDUSTRY - PROPENSITY TO STRIKE MODEL. LEVEL OF AUTOMATION IN INDUSTRY VARIABLES RELATED TO LEVEL OF AUTOMATION IN INDUSTRY (a) Di r e c t l y - 1. Production Related Capacity 2. R a t i o of non-produ c t i o n workers to t o t a l employment (b) Inversely- 1. Strength of Rela t e d Union STRIKE WORKER ENVIRONMENT VARIABLES 1. L o c a t i o n of workers i n the general community 2. Character of Job and Worker OUTCOME PROPENSITY OF STRIKE TO STRIKE FEEDBACK H H ON 117-automation, the trade unions g e n e r a l l y f i n d i t d i f f i c u l t to win a s t r i k e . They may t r y to swing the outcome of the s t r i k e i n t h e i r favour \"by pro l o n g i n g the s t r i k e i n the hope that breakdowns of machinery and maintenance requirements w i l l a i d them. This i n c r e a s e s the i n d u s t r y ' s p r o p e n s i t y to s t r i k e . I f the workers' environmental f a c t o r s support the p r o p e n s i t y to s t r i k e , then t h i s w i l l r e i n f o r c e f u r t h e r the i n d u s t r y ' s p r o p e n s i t y to s t r i k e . On the other hand, i f the workers' environmental f a c t o r s do not support the p r o p e n s i t y to s t r i k e , even i f the i n d u s t r y has achieved a high l e v e l of automation, t h i s may reduce the i n d u s t r y ' s p r o p e n s i t y to s t r i k e . For P e r i o d 2, there are a few e x c e p t i o n a l cases. I f the outcome of the s t r i k e i s p e r p e t u a l l y unfavourable to the trade union, the trade union may l o s e the w i l l to s t r i k e . ' This may even-t u a l l y l e a d to the i n d u s t r y being c a t e g o r i z e d as having low pr o p e n s i t y to s t r i k e . In i n d u s t r i e s that can only maintain a low l e v e l of automation, the trade unions may be more c e r t a i n of a favourable outcome out of the s t r i k e . I f the workers' environmental f a c t o r s support the p r o p e n s i t y to s t r i k e , there vii 11 be a l a r g e r number of s t r i k e s , but the favourable outcome from the trade union's p o i n t of view can be achieved i n a short s t r i k e . This w i l l i n c r e a s e the p r o p e n s i t y to s t r i k e . Exceptions are p o s s i b l e where the workers' environmental f a c t o r s reduce the p r o p e n s i t y to s t r i k e . CHAPTER VI CONCLUSION The t e s t oh the n u l l hypothesis, H Q , i n d i c a t e d that there i s no r e l a t i o n s h i p between the l e v e l of automation i n i n d u s t r y and the pr o p e n s i t y to s t r i k e f o r P e r i o d 1, where-as t h i s t e s t i n d i c a t e d that there i s a r e l a t i o n s h i p between these two v a r i a b l e s f o r P e r i o d 2, at and only at the l e v e l  of s i g n i f i c a n c e , a = .05 \u2022 The value of the l e v e l of s i g n i f -icance here i s emphasized. The l e v e l of s i g n i f i c a n c e that Is accepted draws a l i n e between whether the n u l l hypothesis, H Q , i s accepted or r e j e c t e d . The expl a n a t i o n of the r e s u l t s that have been computed i s dependent upon t h i s l e v e l of s i g n i f i c a n c e , a = .05. In P e r i o d 1, i t i s considered that the presence of automation i n i n d u s t r y i s not strong enough to a f f e c t sub-s t a n t i a l l y the p r o p e n s i t y to s t r i k e . Among the major group and sub-group i n d u s t r i e s that have been s t u d i e d , there have not appeared reports r e f e r r i n g to t h i s p e r i o d that automation has a f f e c t e d the trade union's a b i l i t y to stage a s u c c e s s f u l s t r i k e . On the other hand, f o r P e r i o d 2, repor t s have appeared that i n some cases, the trade unions, have been unable to stage a s u c c e s s f u l s t r i k e from t h e i r p o i n t of view. 119. The degree of accuracy of the r e s u l t s i s dependent mainly on the assumptions made and the type of data that i s used. The data used i s secondary data, and t h i s has been adapted f o r t h i s study. As f a r as p o s s i b l e , c o n s i s t e n c y i n the e x t r a c t i o n of data from the various sources has been maintained i n usi n g the Standard I n d u s t r i a l C l a s s i f i c a t i o n Code developed by the United S t a t e s , Bureau of the Budget. The c h a r a c t e r i s t i c s of the l e v e l of automation i n i n d u s t r y and the pr o p e n s i t y to s t r i k e are such that only a q u a l i t a t i v e method of measurement can be employed. At the most, the method used here i n measuring automation i n i n d u s t r y i s an i n d i c a t i o n of the r e l a t i v e l e v e l s of automation to which the i n d u s t r i e s can be c l a s s i f i e d . The p r o p e n s i t y to s t r i k e has been measured by data that had been c o l l e c t e d on the a c t u a l occurance of the s t r i k e i t s e l f . I t i s not i n d i c a t i v e immed-i a t e l y whether the outcome of the s t r i k e has changed the workers' p r o p e n s i t y to s t r i k e . This may only be made apparent i f the study has been c a r r i e d out i n the long-run, or an o p i n i o n survey has been c a r r i e d out on the workers v;ho have p a r t i c i p a t e d i n the s t r i k e , immediately a f t e r the s t r i k e has been terminated. I t must be mentioned that the l e v e l of automation i n i n d u s t r y does not always have to assume the r o l e of an a c t i v a t o r on the p r o p e n s i t y to s t r i k e . The i n d u s t r y ' s l e v e l of prop-e n s i t y to s t r i k e may a f f e c t t h e . l e v e l of automation i n t h i s i n d u s t r y under c e r t a i n c o n d i t i o n s . I f an i n d u s t r y .is capable of being automated, high p r o p e n s i t y to s t r i k e i n the i n d u s t r y may be one of the c h i e f c o n t r i b u t o r y f a c t o r s a f f e c t i n g the 120. management's d e c i s i o n to speed-up t h e i r automation programme. The r e s u l t s of the study, on the , whole , are i n d i c -a t i v e of a general trend f o r the p a r t i c u l a r i n d u s t r y groups and the periods under study. The tendency of the r e s u l t s to show c e r t a i n c h a r a c t e r i s t i c s have been due to the appear-ance of these c h a r a c t e r i s t i c s on a m a j o r i t y of occasions. There are exceptions to t h i s general trend, but these are only found i n the m i n o r i t y . A d e t a i l e d study w i l l have to be c a r r i e d out to o b t a i n a more p r e c i s e i d e a regarding these exceptions. Thus, any general statement of the r e s u l t s of \u2022this study, when r e f e r r i n g to s p e c i f i c i n d u s t r i e s , should be made w i t h the r e s e r v a t i o n about exceptions which are co n t r a r y to the g e n e r a l trend. On the whole, the study f o r each p e r i o d has been c a r r i e d out f o r a short time span. For P e r i o d 2, e s p e c i a l l y , the r e s u l t s may be i n d i c a t i v e of short-run or t r a n s i t o r y e f f e c t s . In the short-run, e q u i l i b r i u m may not have been a t t a i n e d . In the long-run, the trend i n the r e l a t i o n s h i p between the l e v e l of automation i n i n d u s t r y and the p r o p e n s i t y to s t r i k e may not be s i m i l a r to the r e s u l t s obtained i n t h i s study. 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Industry Standard I n d u s t r i a l C l a s s i f i c a t i o n Code Major Group Sub-group Two D i g i t Code Three D i g i t Code Primary Metal I n d u s t r i e s Iron and S t e e l Nonferrous Metals 33 3.^ 1, 332 333 to 3 3 6 , 339 Machinery 35 351 to 359 E l e c t r i c a l Machinery 35 361 to 3 6 7 , 369 T r a n s p o r t a t i o n Equipment Autos, Trucks and Parts 371 Aerospace 37 372 Other Transport-a t i o n Equipment 373 to 375, 379 F a b r i c a t e d Metals 34 341 to 349 and Instruments 38 381 to 387 Chemicals .. 28 281 to 2 8 7 , 289 Paper and Pulp 26 261 to 266 Rubber 30 301 to 5 0 3 , 3 0 6 , 307 Stone, Clay and Glass 32 321 to 329 Petroleum and Coal Products 29 2 9 1 , 2 9 5 , 299 Food and Beverages 20 201 to 209 T e x t i l e s 22 221 to 229 Misc. Manufactur-i n g 39 391, 393 to 396, 398, 399 Mining 10 to 14 101 to 1 0 6 , 1 0 8 , 1 0 9 , 1 5 1 , 132, 138, l 4 l , 142, 144, 145, 147 to 149. Source: United S t a t e s , Department of Labor, Bureau of Labor S t a t i s t i c s , Employment and Earnings S t a t i s t i c s f o r the  United States, 190lFT9oo= B u l l e t i n \"No. '\u00a3512 - 4 , Oct. i960. 133-ANALYSIS OP SUPPLEMENTARY DATA - PERIOD 2. Reference to the d u r a t i o n of s t r i k e s recorded i n Table XX. have been made i n the d i s c u s s i o n of the l i t e r a t u r e on the p r o p e n s i t y to s t r i k e i n Chapter I I , as an i n d i c a t o r of s t r i k e a c t i v i t y 1 . The average d u r a t i o n of s t r i k e s i s computed as the r a t i o of man-days i d l e due to work stoppages found i n Table IXb. to the number of workers i n v o l v e d which i s found i n Table XIX. Computation of the average number of work stoppages i n each c e l l as recorded i n Table XXI. i s obtained from data found i n Tables X I I c . and XIX. The average d u r a t i o n of s t r i k e s i n each c e l l found i n Table XXII. have been computed from Tables X I I c . and XX. 1. Ross and Hartman, op. c i t . , pp. 8-l4. 124. TABLE XIX. NUMBER OF WORK STOPPAGES BY MAJOR GROUP AND SUB-GROUP INDUSTRIES - PERIOD 2. Industry-Number of Work Stoppages beginning during year Number of Workers (Thousands) Involved I960 1961 1962 1963 1964 1965 I960 1961 1962 1962 1964 1965 Iron and Steel 95 70 93 . 78 98 122 74 48 45 41 49 52 Mining 154 .154 159 153 155 188' 49 28 52 46 82 72 3 Petroleum and Coal Products 12 17 10 14 22 12 2 15 7 2 5 1 >> Aerospace 28 14 19 12 19 22 82 2 221 8 20 15 dusti T e x t i l e s 30 35 30 . 26 27 44 5 6 7 12 8 21 Mi s c. Manufac turing 54 56 54 46 49 54 5 10 7 8 9 7 \u2022H E l e c t r i c a l Machinery 102 114 99 109 105 127 97 67 64 44 62 52 o \u2022H \u2022H Rubber 53 65 43 82 67 92 20 22 15 22 20 55 n3 \u00a7 \u2022 >\\ Med Paper and Pulp 52 62 63 54 79 91 9 15 19 9 29 29 +\u2022* Machinery 144 176 196 171 191 266 69 89 62 59 120 112 o Chemicals 91 94 103 104 94 102 22 14 29 20 21 29 Level Fabricated Metals and Instruments 224 210 258 220 251 297 50 110 58 46 87 95 Autos, Trucks and Parts 70 62 56 58 66 84 82 272 45 54 344 71' Nonferrous Metals 63 56 83 52 75 82 20 26 4p 14 29 25 o Other Transportation Equipment 24 24 25 21 26 27 25 22 14 11 22 50 Stone, Clay and!.Glass 98 130 113 118 117 129 18 24 16 20 22 71 Fo6$ and Beverages .184 177 206 158 186 227 66 80 55 52 55 57 Source: U.S. Department of Labor,. Bureau of Labor S t a t i s t i c s , B u l l e t i n s on Analysis of Work Stoppages. TABLE XX. AVERAGE DURATION OP STRIKES IN INDUSTRY - PERIOD 2 . Industry-Average (days Duration of S t r i k e s of I d l e n e s s ) I960 1961 1962 1963 1964 1965 I r o n and S t e e l 13-7 8 . 0 9 . 1 1 0 . 1 1 0 . 1 1 6 . 0 High M i n i n g 14 . 3 8 . 2 1 8 . 9 1 0 . 4 9 - 7 6 . 0 High P etroleum and Coal Products 40 . 0 2 1 . 0 7 4 . 6 1 7 9 . 0 3 3 - 0 3 3 . 0 >> Aerospace 14.5 1 8 . 0 2 3 . 9 6 . 8 8 . 0 1 2 . 5 . W <\u2014t T e x t i l e s 6 . 8 6 . 5 14 . 3 14 . 8 1 5 . 5 8 . 3 rt H p; Misc. Manufacturing 14 . 8 1 2 . 5 2 5 . 4 1 1 . 9 1 6 . 2 2 3 . 4 \u2022H rt E l e c t r i c a l Machinery 1 3 - 0 1 0 . 7 9 - 9 1 8 . 9 1 3 . 6 1 5 . 1 tomatio Medium Rubb er Paper and Pulp 8 . 7 1 5 - 1 9 . 4 2 1 . 6 1 0 . 6 2 2 . 2 3 4 . 4 1 6 . 2 1 5 . 0 14 . 9 8 . 1 2 3 . 8 Machinery 1 8 . 0 1 3 . 9 1 9 . 1 14 . 2 . 9 . 5 1 6 . 6 C M O \u2022\u2014l Chemicals 14.3 3 1 . 5 2 6 . 5 24 . 0 1 6 . 0 2 5 . 4 F a b r i c a t e d Metals and Instruments 1 3 . 4 1 1 . 8 1 8 . 4 1 3 - 8 1 9 . 8 1 6 . 2 Autos, Trucks and P a r t s 5 . 9 8 . 2 1 4 . 4 9-7 1 7 . 2 1 2 . 1 Nonferrous Metals 4 3 . 2 1 0 . 7 1 1 . 5 1 6 . 0 1 3 . 2 1 5 . 3 O Hi Other T r a n s p o r t a t i o n Equipment 7 5 . 0 4 . 2 1 3 . 4 9 . 4 1 5 . 4 1 6 . 2 Stone, Clay and Glass 1 2 . 7 1 9 . 1 1 9 . 9 2 3 . 0 1 7 . 9 1 1 . 8 ' Food and Beverages 9 . 9 \u2022 7 . 4 1 1 . 1 8 . 4 1 5 - 7 I 6 . 3 136. TABLE XXI. COMPUTATION OP AVERAGE NUMBER OF WORK STOPPAGES FOR EACH CELL - PERIOD 2. Industry id Iron and Steel Mining Petroleum and Coal Products Aerospace Number of Work Stoppages High Propensity to Strike I960 1961 1962 1963 1964 1965 17 159 153 155 10 14 22 28 Average 19 599 \u201e - 10 -22 59.9 Medium Propensity to Strike I960 1961 1962 1963 1964 1965 95 70 123 154 12 12 Average = \u00ab= 77.7 Low Propensity to Strike I960 1961 1962 1963 1964 1965 93 78 98 154 188 14 Average 656 ~8~ 12 19 = 82 T e x t i l e s Misc. Manufacturing E l e c t r i c a l Machinery Rubber Paper and Pulp Machinery Chemicals 82, 67 79 91 Average = 196 103 618 = 103 : * \u2022 56 102 114 53 65 62 144 176 91 94 Average 54 46 49 54 109 105 93 63 171 191 266 104 2262 30 54 35 30 36 ^  37 99 43 44 137 52 54 94 102 22 103 Average = 847 = 60.5 o Fabricated Metals and Instruments Autos, Trucks and Parts Nonferrous Metals Other Transportation Equipment Stone, Clay and Glass Food and Beverages 62' 66 70 56 63 56 83 53 75 83 24 24 130 118 36 37 25 113 210 258 220 251 297 58 84 224 31 117 139 227 Average = = 65 Average = = 144 98 184 177 206 158 186 Average = - i 2 ^ = 176.1 127. TABLE XXII. COMPUTATION OP AVERAGE DURATION OF STRIKES FOR EACH CELL - PERIOD 2. Average Duration of Strikes (days of idleness) .Industry- -High Propensity to Strike 19.60 1961 1962 1963 1964 1965 Medium Propensity to St r i k e I960 1961 1962 1963 1964 1965 -Low Propensity to Strike I960 1961 1962 1962 1964 1965 Iron and Steel 13.7 8.0 16.0 9.1 10.1 10.1 Mining 18.9 10.4 9-7 14.3 8.2 6.0 High Petroleum and Coal Products 21.0 74.6 179.0 33.0 40.0 33.0 >> L i High Aerospace 14.5 23.9 3Q7 S Average = 12.5 = 39-75 Average = 1 2 ^ , Q = 20.8 18.0 6.8 8.0 Average = 1^2. = 9.5 ust: T e x t i l e s 6.8 6.5 14.2 14.8 15.5 8.2 Ind Misc. Manufacturing 12.5 25.4 11.9 16.2 23.4 14.8 \u2022H E l e c t r i c a l Machinery 13.0 10.7 18.9 13.6 9.9 15.1 ion \u2022H Rubber 34.4 15.0 8.7 9-4 8.1 10.6 4-5 \u00a7 Med Paper and Pulp 14.9 23.8 21.6 22.2 15.1 16.2 -P Machinery 19.1 18.0 12-9 14.2 9.5 16.6 vel of J Chemicals 26.5 Average = = 22.3 14.2 21.5 24.0 Average = = 16.2 16.0 Average = ^ p p ^ = 12-5 25.4 cu Hi Low F a bricated Metals and Instruments Autos, Trucks and Parts Nonferrous Metals Other Transportation Equipment 8.2 42.2 10.7 11.5 75-0 4.2 17.2 16.0 12.2 15.3 15.4 16.2 11.8 18.4 13.8 19.8 16.2 5.9 14.4 9.7 12.1 12.4 9.4 12.4 Stone, Clay and Glass 19.1 23.0 19.9 17.9 H.8 12.7 Food and Beverages Average = 2 ^ ' 2 = 20.6 16.2 Average = 2 ^ , S = 14.05 9-9 7.4 11.1 8.4 15.7 Average = 7-y-^ = 11.2 1 3 8 . TABLE X X I I I . RATIO OF NONPRODUCTION WORKERS TO TOTAL EMPLOYMENT Industry R a t i o of Nonproduction Workers to T o t a l Employment (percent) 1947 1951 1959 1965 I r o n and S t e e l 1 1 . 9 1 2 . 5 1 8 . 4 1 7 . 1 High M i n ing 8 . 8 9 - 6 1 9 - 4 2 2 . 1 High P etroleum and Coal Products 2 3 . 1 25.1 3 5 . 2 3 8 . 2 stry Aerospace 2 5 . 9 2 5 . 7 3 8 . 1 42.8 Indui T e x t i l e s 6 . 1 7 . 4 9 - 4 1 0 . 7 ri \u2022H Mi sc. Manufac t u r i n g 1 2 . 8 14.8 1 9 . 3 2 0 . 0 ri o ~-i E l e c t r i c a l Machinery 2 1 . 7 2 2 . 3 3 0 . 6 3 1 . 3 Automat: \u2022H CD Rubber Paper and Pulp 1 8 . 6 1 2 . 7 1 8 . 9 14.9 2 2 . 3 1 9 . 6 2 2 . 2 22.1. n Machinery 2 0 . 9 2 2 . 4 2 9 . 3 3 0 . 0 vel ( Chemicals 24.8 2 8 . 9 3 7 - 5 3 9 - 8 CD hi F a b r i c a t e d Metals and Instruments 1 7 . 4 1 9 . 4 2 5 . 1 2 5 . 7 Autos, Trucks and Parts 1 8 . 5 1 8 . 1 2 2 . 1 2 1 . 6 Low Nonferrous Metals 15.3 1 7 . 0 2 1 . 6 2 0 . 4 \u2022 Other T r a n s p o r t a t i o n Equipment 1 1 . 9 14.5 1 8 . 9 1 7 . 8 Stone, Clay and Glass 1 2 . 3 1 3 . 6 1 7 . 9 1 9 . 7 Food and Beverages 2 2 . 5 2o .0 31 .7 3 4 . 1 Source: Table C - 3 . Manpower Report of the Prec 3ident and A Report on Manpower Requirements, Resources, U t i l i z a t i o n and T r a i n i n g , by the United States Department of Labor, Trans-m i t t e d to the Congress, A p r i l 1 9 6 7 . TABLE XXIV. TABLE OF CRITICAL VALUES OF CHI SQUARE P r o b a b i l i t y under H Q that x >. c h i square . 9 9 . . 9 8 \u2022 \u2022 95 . 9 0 . 8 0 \u2022 7 0 . 5 0 . 3 0 . 2 0 . 1 0 . 0 5 . 0 2 . 0 1 . 0 0 1 1 . 0 0 0 1 6 . . 0 0 0 6 3 . 0 0 3 9 .016 . 0 6 4 . 15 .46 1 .07 1.64 2 . 7 1 3-84 5 . 4 l 6 . ,64 1 0 . 8 3 2 . 0 2 .04 . 1 0 . 2 1 . 4 5 . 7 1 1 . 3 9 2.41 3 . 2 2 4 . 6 0 5 . 9 9 7 . 8 2 9 . 2 1 1 3 . 8 2 3 . 12 .18 . 3 5 . 5 8 1 . 0 0 1 . 4 2 2 .37 3 . 6 6 4.64 6 . 2 5 7 . 8 2 9.84 1 1 . 3 4 1 6 . 2 7 ; 4 , 3 0 . 4 3 . 7 1 1.05 1 . 6 5 2 . 2 0 3 , 3 6 4 . 8 8 5 . 9 9 7 - 7 8 9 . 4 9 I I . 6 7 1 3 . 2 8 18.46 \u2022 . 5 . 5 5 . 7 5 1.14 1 . 6 l 2 . 3 4 3 . 0 0 4 . 3 5 6 . 0 6 7 . 2 9 9.24 1 1 . 0 7 13 .29 1 5 . 0 9 2 0 . 5 2 6 . 8 7 . 1 . 1 3 1.64 2 . 2 0 3 . 0 7 3 . 8 3 5 . 3 5 7 . 2 3 8 . 5 6 10 .64 1 2 . 5 9 1 5 . 0 3 1 6 . 8 1 22.46 7 1.24 1 . 5 6 2.17 2 . 8 3 3 . 8 2 4 . 5 7 6 . 3 5 8 . 3 8 9 . 8 0 1 2 . 0 2 14.07 1 6 . 6 2 18 .48 2 4 . 3 2 8 1 . 6 5 2.03 2 . 7 3 3 . 4 9 4 . 5 9 5 . 5 3 7 . 3 4 9 , 5 2 1 1 . 0 3 1 3 . 3 6 1 5 . 5 1 1 8 . 1 7 2 0 . 0 9 2 6 . 1 2 9 2 . 0 9 2 . 5 3 3 - 3 2 4 . 17 5 . 3 8 6 . 3 9 8 . 3 4 1 0 . 6 6 12 .24 14.68 1 6 . 9 2 1 9 . 6 8 2 1 . 6 7 2 7 . 8 8 10 2 . 5 6 3 . 0 6 3 . 9 4 4 . 8 6 6 . 1 8 7 - 2 7 9 . 3 4 1 1 . 7 8 1 3 . 4 4 1 5 . 9 9 1 8 . 3 1 2 1 . 1 6 2 3 - 2 1 . 2 9 - 5 9 Source: Sidney S i e g e l , Nonparametric S t a t i s t i c s f o r the Behav i o u r a l Sciences, (New York: McGraw-Hill Book Co., Inc., 1 9 5 6 ) , p. 2 4 9 . 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