TN 295 No. 9192 ,V lv m i .. . * ■ ft? *Ca /.^•,%% >..iii.V **.^..% ,**\c^.V d»*.«j«i.% ^\c^ /K 111 #*\ 0*8 v> " V'" '/a. ^ ••••• ^ .1-,- V 4y V V u Co^ v^ v « .-or *d» 1 **:Lr* ^ • • • ^^ * ♦ a v ♦ ^^' *y w : m\ V : «* 4 ^ ^^RP 1 ^ v : -- : \<^ * /^^% ^*.{g^>o /timL'% &*-*jsikS jf*i*ik\ c \-^k- ^. . > v^ »v«. ^v A v »iv» o. 0° .^^* °o ^°%. -Jl ?V V-^-V V^'V V-^-> V^'V V-#- > 1 ^\^JL%\ * ^ A v ♦(dOsOi. ^ V->' ,%•• Jf A* t ^ ^ « ^.r "oV 7 r ^0^ II'- A~ «»» "•«•" ^«" 9^ *«,l' ^ ^A * a » » ' / ^V' ■••X" ''^w'V --V v ""• Si r>^- ■ • BUREAU OF MINES INFORMATION CIRCULAR/1988 Characterization of the 1986 Coal Mining Workforce By Shaii J. Butani and Ann M. Bartholomew UNITED STATES DEPARTMENT OF THE INTERIOR -f\U&t ^•^*4' n ^l Information Circular 9192 Characterization of the 1 986 Coal Mining Workforce By Shail J. Butani and Ann M. Bartholomew UNITED STATES DEPARTMENT OF THE INTERIOR Donald Paul Hodel, Secretary BUREAU OF MINES T S Ary, Director jr ^ ^Z& UH {\D< \ \<\Z Library of Congress Cataloging-in-Publication Data Butani, Shail J. Characterization of the 1986 coal mining workforce (Information circular ; 9192) Bibliography: p. 7 Supt. of Docs, no.: I 28.27:9192 1. Coal miners— United States. I. Bartholomew, Ann M. II. Title. HI. Series: Information circular (United States. Bureau of Mines) ; 9192. TN23.tM3~ 622 s 331.7'622334'0973 88-600142 HD8039.M62U6 CONTENTS Page Abstract 1 Introduction 2 Acknowledgments 2 Survey methodology 2 Population 2 Sample 3 Data collection 3 Data coding, entering, and editing 3 Estimation procedures 3 Grouping of characteristics 4 Job title and principal equipment operators 4 Employment size class 4 Present job, present company, and total mining experience 4 Job-related training during last 2 years 4 Age 4 Reliability of estimates 4 Validation of estimates 5 Summary of major findings 5 Application of data for injury analyses 7 Recommendations for future work 7 References 7 Appendix A. — Coal mining industry job title grouping 8 Appendix B. — Coal mining industry equipment operated grouping 11 Appendix C. — Estimation procedures 13 Appendix D. — Reliability of estimates: random group variance technique 14 Appendix E. — Coal mining 1986 workforce estimates 15 Appendix F. — Mining industry population survey letters and questionnaire 57 ILLUSTRATIONS 1. Percentage of 1986 coal mining workforce with at least a high school diploma, by age 6 2. Percentage of 1986 coal mining workforce with at least a high school diploma, by sex 7 3. Percentage of 1986 coal mining workforce with at least a high school diploma, by race 7 TABLES 1. Population and injury statistics for 1986 coal mining sector 2 2. Demographics survey response status: 1986 coal mining sector 3 Coal mining 1986 workforce estimates— E-l. Employment size class, by type of coal mined 15 E-2. Job title, by type of coal mined 15 E-3. Principal equipment operated, by type of coal mined 16 E-4. Work location at mine, by type of coal mined 16 E-5. Experience at job, company, and mining, by type of coal mined 17 E-6. Training received, by type of coal mined 17 E-7. Age distribution, by type of coal mined 18 E-8. Sex, race, and education, by type of coal mined 18 E-9. Job title, by employment size class 19 E-10. Principal equipment operated, by employment size class 20 E-ll. Work location at mine, by employment size class 20 E-12. Experience at job, company, and mining, by employment size class 21 E-13. Training received, by employment size class 22 E-14. Age distribution, by employment size class 22 E-15. Sex, race, and education, by employment size class 23 E-16. Job title, by principal equipment operated 24 E-17. Job title, by work location at mine 26 E-18. Job title, by years of experience at job 27 E-19. Job title, by years of experience at company 28 E-20. Job title, by years of mining experience 29 E-21. Job title, by hours of training received in last 2 yr 30 E-22. Job title, by years of age 31 E-23. Job title, by sex 32 E-24. Job title, by race 33 E-25. Job title, by education 34 E-26. Principal equipment operated, by years of experience at job 35 TABLES— Continued Page E-27. Principal equipment operated, by hours of training received in last 2 yr 36 E-28. Principal equipment operated, by years of age 37 E-29. Principal equipment operated, by sex 38 E-30. Principal equipment operated, by race 39 E-31. Principal equipment operated, by education 40 E-32. Job, company, and mining experience, by work location 41 E-33. Training received, by work location 42 E-34. Age distribution, by work location 42 E-35. Sex, race, and education, by work location 43 E-36. Experience at job, by hours of training received in last 2 yr 44 E-37. Experience at job, by years of age 45 E-38. Experience at job, by sex 46 E-39. Experience at job, by race 46 E-40. Experience at job, by education 46 E-41. Experience at company, by hours of training received in last 2 yr 47 E-42. Experience at company, by years of age 48 E-43. Experience at company, by sex 48 E-44. Experience at company, by race 49 E-45. Experience at company, by education 49 E-46. Age, by education 49 E-47. Age, race, and education, by sex 50 E-48. Age and education, by race 51 Number of workers and coefficient of variation— E-49. Employment size class, by type of coal mined 51 E-50. Job title, by type of coal mined 52 E-51. Principal equipment operated, by type of coal mined 53 E-52. Work location at mine, by type of coal mined 54 E-53. Experience at job, company, and mining, by type of coal mined 54 E-54. Training received, by type of coal mined 55 E-55. Age, by type of coal mined 55 E-56. Sex, race, and education, by type of coal mined 56 CHARACTERIZATION OF THE 1986 COAL MINING WORKFORCE By Shail J. Butani 1 and Ann M. Bartholomew 2 ABSTRACT In 1986, the Bureau of Mines conducted a probability sample survey, Mining Industry Population Survey, to measure such employee characteristics as occupation; principal equipment operated; work location at the mine; present job, present company, and total mining experience; job-related training during the last 2 yr; age; sex; race; and education. The population estimates are necessary to properly analyze the Mine Safety and Health Administration (MSHA) injury (includes illness and fatality data) statistics; that is, to compare and contrast injury rates for various subpopulations in order to identify those groups that are exhibiting higher than average injury rates. This report uses the survey's results to characterize the U.S. coal mining workforce from March through September 1986. A companion report, Information Circular (IC) 9193, "Characterization of the 1986 Metal and Nonmetal Mining Workforce," provides similar information for the U.S. metal and nonmetal mining industry. 'Mathematical statistician (now with Bureau of Labor Statistics, Washington, DC). Statistical assistant. Twin Cities Research Center, Bureau of Mines, Minneapolis, MN. INTRODUCTION According to the occupational safety and health (OSH) statistics published annually by the U.S. Department of Labor, Bureau of Labor Statistics, the mining industry (excluding oil and gas extraction) always has had one of the highest injury incidence rates among the major industry divisions. One of the primary objectives of the Bureau of Mines is to conduct research in the area of health and safety of the nation's miners, aimed at reducing the incidence rate of work-related injuries, (includes illnesses and fatalities) in the domestic mining indus- try. In order to reduce the overall incidence rate, the Bureau needs to identify which groups or subpopulations of the workforce are exhibiting higher than average incidence rates. To identify the high-risk groups, information about the injured workers and about the entire workforce is required. Present regulations permit MSHA to collect information on all mine injuries requiring medical attention. Hence, a data base containing various characteristics on the injured workforce is available. Since similar information about the entire workforce was not available, the Bureau conducted a probability sample survey called the Mining Industry Population Survey (MIPS), also known as the demographics survey, to collect the neces- sary data. The 1986 survey measured the following character- istics: job title or occupation, principal equipment operated, work location at mine, experience at present job, experience at present company, total mining experience, job-related training during last 2 yr, age, sex, race, and education. This demo- graphics survey provided information about the population at risk and will aid research in pinpointing the hazardous seg- ments of the population, as illustrated by the following example. From MSHA's coal injury data base, it is known that 12,765 males and 197 females working in the U.S. coal mining industry were injured in 1986. If information about the population at risk (i.e., the number of male and female workers for the coal industry in 1986) is not known, then it is not valid to draw the conclusion that male miners are at a much higher injury risk than female miners. The estimates from the demographics survey show that there were a total of 144,859 male workers and 6,119 female workers (table E-23) employed in U.S. coal mining in 1986. Of these workers, the nonoffice workforce identified by occupation or job title consists of 142,363 males and 3,328 females (table E-8). The reason for excluding office workers from the analysis is to account for some of the obvious difference in job risk. It should be noted that in the office worker category, only 2 pet are males and 46 pet are females (table E-23). The added information on the population puts the injury statistics in a better perspective, as shown in table 1 . Table 1 .—Population and injury statistics for 1986 coal mining sector Population statistics Injury statistics Workers pet Injuries pet Lost workdays pet Male Female . 142,363 3,328 97.7 2.3 12,765 197 98.5 302,841 97.9 1.5 6,374 2.1 Total.. 145,691 100.0 12,962 100.0 309,215 100.0 Since the difference between the population and injury distribution is relatively large, it would be interesting to further investigate the source of variation. Could it be due to varia- tions in the job mix by sex? Hence, the present research will aid in finding solutions to reduce the injury incidence rates for the high-risk groups. That is, the collected information will be used to compare and contrast the demographics composition of the hazardous groups with those of the safer groups. Thus, through present research, the differences and similarities between the two groups can be defined. The purpose of this report is to provide the U.S. coal mining population estimates for March through September 1986 by various characteristics. This information is essential to performing the injury data analysis which is the ultimate goal of the survey. ACKNOWLEDGMENTS The authors thank the officials of the U.S. Department of Labor, MSHA, for submitting the MIPS package to the Office of Management and Budget for its clearance to collect the data. Special thanks go to Kathy Snyder, public affairs spe- cialist, Office of Information and Public Affairs, MSHA, for initiating the study, and to Edwin Thomasson, research liaison officer, Technical Support, MSHA, for his continuous effort and support. SURVEY METHODOLOGY POPULATION The MIPS covered all workers employed in the anthracite coal (SIC 3 111), bituminous coal (SIC 121), metal (SIC 101-106, 109, 281), stone (SIC 141, 142, 324, 327), sand and gravel (SIC 144), and nonmetal (SIC 131, 145, 147, 149, 289, 299) mining industries of the United States during the period 3 The Standard Industrial Classification (SIC) was revised in 1987; the industry group numbers used here are those in effect at the time of the MIPS. March through September 1986. This report gives estimates only for the coal mining (SIC 111 and 121) sector; IC 9193 gives estimates for the 1986 metal and nonmetal mining sector. The information pertaining to the mine employees in- cluded in the survey was collected through the mine operators, because a comprehensive sampling frame (name and address file) of the workers in mine establishments was not available, and cost considerations prohibited the data collection through personal visits. The number of universe units (establishments under MSHA's jurisdiction) covered by the scope of this survey was approximately 18,350, with a total employment level of about 350,000. The number of establishments and employ- ment for the coal mining sector was about 7,750 and 160,000, respectively. The scope of the data for the employees covered by this survey is the same as that of the data collected by MSHA form 7000-1 for the mine accidents, injuries, illnesses, and fatalities, and MSHA form 7000-2 for quarterly mine employment and coal production. The collection of the fun- damental statistics reported on these two forms is required by law (30 U.S.C. 813; 30 CFR 50). SAMPLE The principal feature of the survey sample design was its use of two-stage stratified random sampling. The primary sampling units (first stage) were the mine establishments; the secondary sampling units were employees within each of the chosen mine establishments. The characteristics used to strat- ify the primary units were the industry (anthracite coal, bituminous coal, metal, stone, sand and gravel, nonmetal); mine type (underground, surface, plant or mill); employment size class (1-19, 20-49, 50-99, 100-249, 250-499, 500-999, 1 ,000 and above); and status code (active, intermittent). Since the first three stratification characteristics are highly correlated with the characteristics that the survey was to measure, use of stratified sampling increased the efficiency of the sample design and thus resulted in a smaller required sample size. The fourth characteristic, status code, was chosen so that nonre- sponse adjustment could be made within more homogenous groups. This is desirable because proportionately higher num- bers of nonmailable, out-of-business, refusal, etc., responses are reported from intermittent mine establishments than from active mine establishments. The sampling frame used for this survey was the 1985 preliminary address and employment file maintained by MSHA. A probability sample of 1,476 coal establishments from a universe of 7,733 coal mining establishments was selected by stratifying the frame as previously described and using a systematic sampling procedure with a random start for each stratum. The employees within an establishment were selected by using a systematic sampling procedure with a common random start for each employment size class. A brief description of the sample allocation is as follows. For larger employment size classes, the allocation procedure placed all of the establishments on the frame in the sample as primary sampling units from which the employees were sub- sampled at a low frequency rate. As employment size class decreased, smaller and smaller proportions of the establish- ments were included as primary sampling units, but the employees within the establishments were subsampled at a higher frequency rate. The use of this procedure gave each employee, to the extent possible, about the same probability of inclusion in the sample, thus reducing the sampling variability. In order to limit the response burden for any one establish- ment, a maximum sample of 50 employees per establishment was selected. DATA COLLECTION The MIPS was conducted from March through September 1986 by mail questionnaire through the Bureau's Twin Cities (MN) Research Center. A reproduction of the original letter, followup letter, and the questionnaire bearing the Office of Management and Budget clearance number authorizing col- lection of the data are included in appendix F. Table 2 gives a summary of the results for the coal mining sector from the original and followup mailings, as well as from telephone calls to the nonrespondents. Table 2.— Demographics survey response status: 1986 coal mining sector Overall Usable Industry Population Sample res P° nse "J^^ res P° nse No. pet No. pet Anthracite coal 406 141 124 88 105 84 80 Bituminous coal 7,327 1,335 1,112 83 858 538 63 Total 7,733 1,476 1,236 84 963 622 65 1 Nonrespondents + usables + refusals + unusables (excludes out-of- businesses, nonmailables, duplicates, temporary inactives, and new busi- nesses under construction). A brief description of the response terms follows: Response code Description Nonrespondent Received no response from the establishment. Usable Establishment provided usable data. Refusal Establishment refused to provide any data. Unusable Establishment provided data that were not in usable format. Nonmailable Establishment's address was either insufficient or wrong. Duplicate Data were combined with another establishment's data. Out-of-business Establishment was permanently closed. New business Establishment was in development stage. Temporary inactive... Establishment was temporarily not operating. As part of the data collection phase, all the returns were reviewed and edited for completeness and reasonableness of the data. Whenever there were inconsistencies, the respondents were called for reconciliation. Also, almost all of the respon- dents that had initially refused to participate in the survey were contacted by phone. Approximately 80 pet of these respon- dents ultimately supplied data. Adjustments for those mine establishments that did not supply the data, or supplied partial data, are explained in the "Estimation Procedures" section and in appendix C. DATA CODING, ENTERING, AND EDITING The returns underwent a very comprehensive review and editing process in order to (1) minimize the reporting differ- ences among the respondents (establishments), (2) ensure consistency of coding among the individual worker entries, (3) ensure the accuracy of the data entry, and (4) ensure compat- ibility of occupation and equipment coding with the MSHA injury data base. ESTIMATION PROCEDURES In a simple random sampling plan, all units are sampled with the same sampling ratio. To derive the population esti- mates, the sample units are weighted (replicated) by the inverse of the sampling ratio. Because of efficiency consideration, the data for this demographics study were collected using a complex survey design. Hence, the data for each worker, the ultimate sampling unit, were not equally weighted. Instead, the population estimates were derived by weighting data for each worker with the appropriate final weight of the data, which was the product of the following three factors: (1) the inverse of the sampling ratio with which the primary sampling unit (establishment) was sampled; (2) a nonresponse adjustment factor that was computed separately for each sampling stratum and assigned to all responding establishments in a stratum to account for those establishments in that stratum that did not respond; and (3) the inverse of the sampling ratio with which the secondary sampling units (workers) were selected. A detailed discussion of the different weights and estimation formulas are given in appendix C. In statistical terms, the survey's estimates of the population total were based on a Horvitz-Thompson estimator (7). 4 No adjustment was made for partial nonresponse. That is, the characteristics that were left blank by the respondents were coded as unspecified and were, naturally, weighted by their appropriate final weight in computing the population estimates. The percentage unspecified for a particular charac- teristic gives the user an indication of the completeness of the schedules. GROUPING OF CHARACTERISTICS The original data base has detailed data for the charac- teristics mentioned below. For purposes of publication, the detailed data were combined into groups. Please contact the authors to obtain detailed data or a different grouping of the data for any or all of the characteristics. Job Title and Principal Equipment Operated Since the original data base has about 100 codes for each of these two categories (see appendixes A and B), the entries were combined into 20 to 25 groups. Similarities of the job title or principal equipment operated, and number of workers in each entry were two of the main criteria used in forming the groups. Employment Size Class The classes used for this characteristic are the standard size class definition used by MSHA. Because there were less than three mines for the size class having 1,000 or more employees, the estimates for this class were computed sepa- rately and then were combined with the estimates for employ- ment size class 500 through 999 in order to protect the confidentiality of the mines as well as the workers. The combined size class is labeled as 500 + . Present Job, Present Company, and Total Mining Experience The data for all three of these characteristics were coded only as the number of years. It was felt that data were not reliable enough to be accurate to the month. The groupings were formed to be as compatible as possible to the groupings used by MSHA for its injury statistics. 4 Italic numbers in parentheses refer to items in the list of references preceding the appendixes at the end of this report. Job-Related Training During the Last 2 Years The grouping for this characteristic was formed to reflect the definite and logical intervals that various mine operators employ and that meets the need of the mine safety personnel. The most frequently reported number was 16 h for training during last 2 yr; this is because MSHA requires a minimum training of 8 h/yr. Also, MSHA and safety personnel are interested in knowing the percent of workers who receive no training. Hence, both and 16 h were categorized separately. Age The groupings for age were formed to be about the same as what MSHA uses for their injury statistics. RELIABILITY OF ESTIMATES As stated in reference 2: All estimates derived from a sample survey are subject to sampling and nonsampling errors. Sampling errors occur because observations are made on a sample, not on the entire population. Estimates based on the different possible samples of the same size and sample design could differ. Nonsampling errors in the estimates can be attributed to many sources, e.g., inability to obtain information about all cases in the sample, mis- takes in recording or coding the data, definitional difficulties, etc. Nonsampling errors occur in a census as well as in a sample survey. As mentioned earlier, the completed forms underwent a very comprehensive review and edit process. This was primarily done to minimize the nonsampling errors. In a probability sample the coefficients of variation (CV's), which are a measure of the sampling errors in the estimates, can be estimated from the survey data. CV's were calculated for the basic characteristics as part of the survey estimation process; the CV's as well as the corresponding estimates for number of workers are given in tables E-49 through E-56. The CV's for other estimates can also be derived if requested. The methodology used to compute the estimated CV's is given below. By definition, the CV of any sample estimate is equal to the standard error of the estimate divided by the value of the estimate (3). In other words, it is a measure of relative variation. Because the survey data will be used by numerous researchers to measure different statistics (e.g., totals, means, medians, percentages) by various cross-classification catego- ries, it was not feasible to use the exact formula for the standard error estimates. Hence, a generalized formula that approximated the exact formula and that was easy to imple- ment for computing all the standard error estimates was developed. It should be noted that since the survey uses a complex sampling design, the usual variance, standard devia- tion, and standard error estimates computed by the software packages are no longer valid because they are based on simple random sample design. The reliability measures for this survey were computed by employing a random group variance tech- nique. A brief description of it is given in appendix D and a detailed discussion is given in reference 4. The purpose of producing a reliability measure for this report is to define the confidence interval or range that would include the comparable complete coverage value. For example, the total number of estimated truck drivers for the 1986 coal industry was 7,297 (table E-2 and E-50) with a CV of 4.6 pet (table E-50). Based on this information, the standard error on the total number of truck drivers is 336 (estimate X CV = 7,297 x 0.046) and the 95-pct confidence interval is 6,625 to 7,969 (7,297 ± 2 x 336). This means that with 95 pet confidence it can be said that the interval 6,625 to 7,969 includes the total number of coal truck drivers that would have been obtained from a census of the frame. It should be noted that normally the variance (square of the standard error) of a total pertaining to the combined two industries would be equal to the sum of the variances for each industry because the two industries were sampled indepen- dently. That is, the variance for the total number of truck drivers for the entire coal mining industry would be equal to the sum of the variances for the truck drivers in anthracite and bituminous coal mining industries. However, this methodol- ogy was not employed to compute the variance estimates for the combined two industries, instead, even for this estimate, the random group variance technique as described in appendix D was employed. This was primarily done, as mentioned previously, because the survey data will be used by numerous researchers to measure different statistics (other than totals) such as means, medians, percentages, etc., and for these statistics the variance for the combined two industries will not be the simple sum of the variances for each industry. Hence, for reasons of consistency and simplicity the random group variance estimator was used to compute all variances and thus CV estimates. In general, the smaller the subpopulation size, the larger the variability in the estimates. Additionally, the larger the nonresponse, the less reliable the estimate may be. As men- tioned earlier, nonresponse error is considered a nonsampling error. This error occurred more frequently for estimates of job-related training during the last 2 yr and total mine experience than for other variables because conceptually these variables are harder to report. Moreover, it is possible that the training estimates might be somewhat biased because many respondents filled in 16 h, the minimum number of hours required by MSHA over a 2-yr period. VALIDATION OF ESTIMATES Once the estimates were produced, they were validated for accuracy and reasonableness by several mining industry spe- cialists. Additionally, the total employment for each industry was compared to an independent census conducted by MSHA, the results of which are reported in references 5 through 9. The injury experience report tabulates the injury-illness-fatality data reported to MSHA on form 7000-1 and employment data reported on form 7000-2. While the data base used to compile the statistics for this report contains detailed information for the injured victims, it does not contain similar information for the entire workforce. The breakdown of total employment is available only by type of coal mined, employment size class, and work location. Hence, the MIPS was conducted so that MSHA injury data could be analyzed in greater detail. The data show that the overall employment figures from the two sources differed about 13 pet for coal industry, with the MSHA figures being higher than those of the demograph- ics survey. The differences in the estimates are caused in part by differences in reporting, coverage period, definitions, and methodology, as explained below, for data comparison by employment size class and by work location. When comparing distribution of workers by employment size class, the differences between the numbers in table E-l of this report and MSHA data as stated in tables 4, 4A, and 4B of reference 9, are substantial. This is mainly due to the differences in definitions and methodology. The MIPS classi- fication is based on total employment of an establishment as it existed when the respondents filled out the questionnaires. MSHA collects employment on an quarterly basis and for each quarter it is possible for the employment to be broken into a maximum of four different work locations; hence each estab- lishment may have up to 16 different employment figures. Per MSHA methodology, the size groups are classified according to the lowest numbered (primary) subunit's average employment of four quarters and not on the total employment of an establishment, as is the case with the MIPS. For example, if an establishment's annual average employment is 60, but the employment for the primary subunit, say under- ground, is 15, then the establishment per MSHA's methodol- ogy is in size class 1 through 19, whereas according to the MIPS procedure it is in size class 50 through 99. It is for this reason the average employment per operation as stated in table 4 of reference 9 is 4.6 for size class 1-4. It should be noted that the MSHA classification overestimates the employment in smaller size classes. In view of the above, the injury data as published in references 5 through 9 by size class should not be analyzed against the MIPS employment size class data. Instead, the analyst needs to retabulate the MSHA injury data from the original data tapes so that the size class definition corresponds to the MIPS. Also, a large difference existed between MIPS and MSHA figures for employment distribution by work location. This is primarily due to differences in reporting. The employment reported to MSHA every quarter is in aggregate numbers for each work location (maximum of four). Generally, this type of reporting results in gross approximations in the breakdown of variables like employment. For the MIPS data, the work location was reported for each worker in the sample, in the same manner as it is reported to MSHA on form 7000-1 for each injured worker. It should be noted that the data on work location for individual worker is known with more specificity than for the whole population. Hence, it is appropriate to analyze the survey work location data with MSHA injury statistics. Additionally, a small portion of the difference in the two estimates is due to the job title category of office workers. The MIPS underestimated the number of employees in this cate- gory because many respondents assumed that these workers very seldom incur injuries and therefore were not to be reported. For the purposes of accident analysis, the office workers are to be excluded because of the obvious difference in the injury risk. Hence, the difference in counts of office workers does not make any difference. SUMMARY OF MAJOR FINDINGS The findings of the survey by various cross classifications are given in tables E-l through E-48; tables E-49 through E-56 give reliability estimates for the basic characteristics and a detailed discussion of their use is given in the "Reliability of Estimates" section. If desired, the estimates by some other classification criteria including more detailed estimates (e.g., distribution of workers by age and experience at present company in the bituminous coal industry working at the underground location) can be derived from the original data base. The following findings are based on the data for the entire 1986 coal mining workforce. • The total estimated workforce for the anthracite coal industry was approximately 2,600 while that of bitumi- nous coal was 149,200 (table E-l). The data also indicate that 39 pet of the anthracite coal workforce was employed in establishments with 19 or less employees as compared with 1 1 pet for the bituminous coal industry. • The total estimated workforce for the coal industry was approximately 151,800, of which 15 pet were employed as laborers-miners-utility-service persons, another 15 pet as mechanics-welders-oilers-machinists, and 7 pet as dozer-heavy-mobile equipment operators (table E-2). Each of the remaining occupation groupings had fewer than 7 pet of the employees. • The distribution of the coal workforce was under- ground mine, 46 pet; surface at underground mine, 6 pet; surface mine, 34 pet; plant or mill, 9 pet; and office, 5 pet (table E-4). Also, the distribution for work locations underground mine, surface mine, and plant or mill for anthracite coal industry was vastly different from that of bituminous coal. • The median experience at the present company ranged from 5 yr for truck drivers to 11 yr for longwall operators and working foremen (table E-l 9). • Mean hours of training during the last 2 yr ranged from 23 for scoop tractor operators to 63 for working foremen (table E-21). • Of the female employees, 46 pet had the job title category of office worker, compared with 2 pet of the males (table E-23). • Median experience at present job was 5 yr for surface mine and plant or mill workers compared with 3 yr for underground mine workers and 4 yr for surface at underground mine workers (table E-32). Surface mine workers had lower median present company experience and total mining experience than the workers at the other three nonoffice work locations. The following findings are based on data that exclude the job title category of office worker. • The single largest category of equipment operated was handtools (powered and nonpowered) (table E-3). • The median experience at present job, present com- pany, and total mining were 4, 8, and 1 1 yr, respectively (table E-5). • Mean job-related training during the last 2 yr was about 21 h for anthracite workers and about 35 h for bitumi- nous workers (table E-6). • Mean age of anthracite workers was 42 yr compared with 39 yr for bituminous workers (table E-7). Also, the percentage of workers 50 yr and over in the anthracite coal industry was much greater than in bituminous coal. • Males made up 98 pet of the coal workforce (table E-8). Note that the 98-pct figure excludes the unspeci- fied category. • Whites, blacks, and Hispanics made up 94, 2, and 1 pet, respectively, of the workforce (table E-8). The remaining 3 pet workers belonged either to another race or were unspecified. • Of those workers whose education was specified, 78 pet had a high school or better education (table E-8). Note that this figure is obtained by (1) summing the workers in the categories high school diploma, vocational di- ploma, some college, and college degree, and (2) divid- ing this sum by the total number of workers minus the workers in unspecified category. In this case, it is 96,650 divided by 124,501. • Median experience with present company for establish- ments with less than 50 employees was 5 yr compared with about 9 yr for those with 50 or more employees (table E-12). • Mean job-related training during the last 2 yr was about 30 h for establishments with less than 250 employees, compared with about 42 h for establishments with 250 or more employees (table E-l 3). • Mean age was about 39 yr across all size classes (table E-14). • Those workers that operated no equipment received the most training, an average of 49 h during the last 2 yr (table E-27). At first this result seemed quite surprising, then a close examination of the data by cross referenc- ing to column "None" of table E-16 revealed that most of these workers are in managerial positions. In effect, it is the managers who are receiving the most training (table E-21). • Education and median experience at the present com- pany were inversely related (table E-45); that is, on the average, the less educated the person was, the longer he or she was employed with the company. • There were a higher percentage of employees with at least a high school education under the age of 35 yr than there were of age 35 yr and over (table E-46 and figure 1); proportionately more females had high school or higher education than males (table E-47 and figure 2); education by race (table E-48) is shown in figure 3. 82 pet 85 pet 85 pet 87 P ct 73 pct 73 pct 56 pct 15-23 24-26 27-29 30-34 35-39 40-49 50+ AGE, yr FIGURE 1 .—Percentage of coal mining 1986 workforce with at least a high school diploma, by age (excluding job title category of office worker, as well as workers whose education was unspecified). 87 pet 77 pet 82 pet 84 pet 78 pet MALE FEMALE WHITE BLACK HISPANIC FIGURE 2.— Percentage of coal mining 1986 workforce with at least a high school diploma, by sex (excluding job title category of office worker, as well as workers whose education was unspecified). FIGURE 3.— Percentage of coal mining 1986 workforce with at least a high school diploma, by race (excluding job title cate- gory of office worker, as well as workers whose education was unspecified). APPLICATION OF DATA FOR INJURY ANALYSES The ultimate objective of this study is to provide a basis for- 1. Analyzing the 1986 MSHA coal injury statistics and identifying those subpopulations exhibiting higher or lower than average injury rates. 2. Producing some selected estimates by geographic loca- tion such as regions (east, central, west), MSHA districts, or States and performing injury analyses. 3. Developing an easy to use computerized data base that would be available to the researchers to do their own analyses, especially in the area of targeting injury prevention and training efforts. The results from these analyses, which encompass all facets of mining operations, can help identify areas where research efforts should be devoted to achieve the greatest safety improvements, thus preventing creation of unnecessary regu- lations or crash research programs that tend to waste funds. RECOMMENDATIONS FOR FUTURE WORK 1. After the injury analyses are performed, and the hazardous areas or subpopulations have been identified, it would be desirable to further investigate their problems and needs. This can be accomplished by conducting some special surveys such as an equipment use survey, maintenance-related work survey, small mines survey, etc. 2. Repeat the MIPS and perform the injury analyses periodically, say every 3 to 5 yr, in order to study the changing mining environment and its impact on mining safety and productivity. When the survey is repeated, it is recommended that modifications be made to the questionnaire to reflect new needs. It is also recommended that the collection of total mine experience and job-related training data be eliminated, since these variables are conceptually very hard to measure. Also, the variables experience on the job and experience with the company should be measured in years only. REFERENCES 1. Cochran, W. G. Sampling Techniques. Wiley, 3d ed., 1977, 428 PP. 2. U.S. Bureau of Labor Statistics. Occupational Injuries and Illnesses in the United States by Industry, 1985. May 1987, 81 pp. 3. Hansen, M. H., W. N., Hurwitz, and W. G. Madow. Sample Survey Methods and Theory. Wiley, v. 1, 1953, 638 pp. 4. Wolter, K. M. Introduction to Variance Estimation. Springer- Verlag, 1985, 440 pp. 5. U.S. Mine Safety and Health Administration. Injury Experience in Metallic Mining, 1986. Inf. Rep. 1158, 1987, 276 pp. 6. . Injury Experience in Stone Mining, 1986. Inf. Rep. 1 160, 1987, 450 pp. 7. . Injury Experience in Sand and Gravel Mining, 1986. Inf. Rep. 1161, 1987, 111 pp. 8. . Injury Experience in Nonmetallic Mining, 1986. Inf. Rep. 1159, 1987, 291 pp. 9. . Injury Experience in Coal Mining, 1986. Inf. Rep. 1157, 1987, 390 pp. APPENDIX A.— COAL MINING INDUSTRY JOB TITLE GROUPING Description Job title code Backhoe-crane-dragline-shovel operator 367, 378, 340 Beltman-belt cleaner-belt repairman 601, 154, 1012, 996 Blaster 807 Continuous miner and related machine operator 35, 36, 37, 38, 43, 116 Deckhand-barge and dredge operator 372 Dozer-heavy and mobile equipment operator 368, 985 Driller-auger operator 833, 834, 370, 371 Electrician-wireman-lampman 402, 602, 603, 611, 385 Front-end loader operator 382 Grader-scraper operator 375, 957 Laborer-miner-utility man 616, 53, 316, 10, 16, 32, 39, 45, 157, 216, 224, 386, 395, 397, 609, 624, 706, 708, 710, 874, 997, 1013 Longwall operator 40, 41, 44 Manager-foreman-supervisor: general 430, 449, 481, 489, 494 maintenance 418 working 749 Mechanic-welder-oiler-machinist 404, 604, 605, 1019, 1018, 1060, 394, 608 Mine technical support 393, 396, 414, 423, 456, 462, 464, 495, 592, 593, 594, 921, 965, 998, 1014, 1017, 1023 Office worker 497 Plant operator-warehouseman 374, 379, 380, 388, 392, 1022 Roof bolter-rock driller 46, 47, 1056 Scoop tractor operator-motorman 128, 269, 969, 262, 276, 373, 962 Shuttle car operator 850 Thick driver 376 Code Description 10 Jacksetter, on face underground 16 Faceman , on section underground 32 Brattice man 35 Continuous miner helper 36 Continuous miner operator 37 Cutting machine helper 38 Cutting machine operator 39 Hand loader operator 40 Headgate operator 41 Longwall helper Longwall operator 43 Loading machine operator Gathering arm loader operator 44 Shear operator Longwall operator 45 Rockman 46 Pinner Roof trimmer Scaler operator Truss bolter Roof bolter 47 Roof bolter helper Pinner helper 53 Utility man , underground 116 Mucking machine operator, underground 128 Scoop operator, underground 154 Belt cleaner Code Description 157 Pumper off section, underground 216 Track workers Trackman, underground 224 Transportation trainee, underground 262 Brakeman 269 Locomotive operator Motorman, underground 276 Jeep driver Tractor operator, underground 316 Service truck operator Pumper, surface Utility man, surface Track gang, surface 340 Boom operator 367 Pitman Backhoe operator Shovel operator 368 Tractor operator, surface Dozer operator 370 Auger operator 371 Auger helper 372 Boat operator Deckhand Barge loader Barge attendant Dredge operator 373 Car dropper Code Description 374 Sandbox operator Crusher operator Reagent operator Preparation plant operator Cleaning plant operator Shipping Bagger-baler Blunger operator Warehouseman Bulk loader Storekeeper Mill operator Car loader 375 Grader operator, surface 376 Truck driver, surface 378 Crane operator, surface Dragline operator 379 Kiln operator Calciner Dryer operator 380 Fine coal plant operator 382 Front-end loader operator, surface Loader operator Highlift operator Payloader operator 385 Lampman 386 Refuse truck driver 388 Shaker operator Separator operator Screen operator 392 Washery operator Binman Tipple operator 393 Scaleperson Weighmaster 394 Carpenter 395 Water truck operator 396 Watchman Security guard 397 Fireman 402 Master electrician 404 Master mechanic 414 Laboratory assistant Technicians Quality control Laboratory technician Laboratory supervisor 418 Maintenance supervisor Maintenance foreman 423 Surveyor Draftsman 430 Assistant foreman- vice president Assistant manager 449 President Owner Mine manager Mine foreman 456 Engineer Chemist Geologist Metallurgist Code Description 462 Mine examiner Examiner Preshift examiner Fireboss 464 Inspector 481 Assistant supervisor-superintendent Superintendents Supervisors 489 Outside foreman 494 Mill foreman Plant foreman Plant manager Mill manager 495 Safety director Safety manager Environmental coordinator Safety coordinator Safety engineer 497 Clerk Office help Accountant Computer operator Secretary Timekeeper Controller 592 Safety instructor 593 Nurse 594 Training specialist 601 Belt mover Conveyor man Beltman Belt installer Tailpiece man 602 Lineman Electrician 603 Electrician helper 604 Millwright Plumber Boilermaker Mechanic Fueler Pipe man Repairman Pipefitter Boiler operator Boiler trainee 605 Mechanic helper 608 Mason 609 Material man Supplyman 611 Wireman 616 Roustabout Miner Groundman Laborer Parts Runner 624 Trainees Apprentice 706 Rock duster 708 Ventilation man 10 Code Description 710 Timberman Propman 749 Leadman Production supervisor-superintendent Section boss Section foreman Labor foreman Shift boss Working foreman Production foreman 807 Blaster Shot firer Powder man Chargeman Hole loader 833 Driller helper 834 Stoper operator Driller 850 Buggy operator Ramcar operator Shuttle car operator 874 Stationery mine equipment operator Mine equipment operator 921 Hoist engineer Hoist operator Hoistman 957 Scraper operator Pan operator 962 Trip rider Flagman Car runner surface Code Description 965 Dispatcher Expeditor 969 Locomotive engineer Motorman 985 Heavy equipment operator Mobile equipment operator 996 Feeder operator 997 General or many equipment operator 998 Janitor 1012 Belt repairman Belt vulcanizer 1013 Cleanup man 1014 Coal sampler Coal tester Sampler 1017 Rodman 1018 Greaser Oiler Lube man 1019 Welder 1022 Dump operator Dump man 1023 Transit man 1056 Rock driller 1060 Shopman Shop foreman Bit sharpener Machinist 11 APPENDIX B.— COAL MINING INDUSTRY EQUIPMENT OPERATED GROUPING Description Equipment code Backhoe-crane-dragline-shovel 60, 14 Belt 13, 96 Continuous miner and related machinery 12, 16, 25, 43 Dozer-heavy and mobile equipment 8, 85 Explosives 47 Front-end loader-forklift 24, 23 Grader-scraper 52, 57 Handtools (powered and nonpowered) 28 Hoist 30 Locomotive-mine car 34, 41, 42, 56, 64, 65 Longwalls and parts 35, 36 Many equipment 97 Miscellaneous utility equipment 95 Plant equipment 40, 7, 11, 15, 18, 22, 26, 51, 58, 69, 83 Rock dusting machine-pump 48, 55 Roof bolting machine-underground drill 54, 20, 53 Scale-lab equipment-controls 92, 80, 91 Scoop 33 Shuttle car 61 Surface drill-auger 9, 4 Truck (haulage) 44, 45 Truck (utility)-personnel carrier 67, 37, 66 Welding machine-lathe 70, 5 None Unspecified-not elsewhere classified 99, 98, 3, 71 Code Description Code Description None 3 Helicopters 4 Auger Auger machine 5 Lathe 7 Boats Barges Water transportation 8 Bulldozer Dozer Crawler tractor 9 Carriage-mounted drill Jumbo drill Churn drill Rotary drill Jet piercing drill Airtrack compressor drill 11 Classifier Cyclones 12 Continuous miner Dosco miner 13 Conveyor All types belts Belt feeder Mobile bridge carrier 14 Crane Derrick Cherry picker Basket scaler Scaling machine Rock or dropball Boom hoist Gantry 15 Crusher Breaker 16 Undercutter Cutting machines Chain cutter 18 Dredge 20 Electric drills Hydraulic drills Coal drills 22 Precipitator heavy media bath Filters Flotation machines Filte- 23 Forklift 24 Loader Front-end loader Highlift Payloader Bobcat 25 Gathering arm loader Coal loading machine 15BU joy 26 Grizzlies 28 Handtools (powered and nonpowered) Ram jack 30 Car dropper Hydraulic jack Hoist 33 S&S battery Unitrac Load-haul-dump Scoop tram Teletram car 12 Code Description 34 Trammer Lorry car Locomotive Rail-mounted locomotive Tow-motor 35 Longwall machine Plow shearer 36 Longwall shield Jacks or chocks Longwall subparts 37 Golf cart Mancar Inspector's friend Jeep Mantrip Personnel carrier Porta bus Boss buggy Rail runner Rail rover 39 Grinding mills Rod or ball mills 40 Milling machinery General plant equipment Sandboxes Block press 41 Underground flatcar Timber truck, underground Nipper truck, underground Mine car, underground 42 Boxcar, surface Hopper car, surface Mine car, surface Ore-coal car, surface 43 Overshot loader Mucking machine 44 Ore haulage trucks, offhighway 45 Pay loader ore haulage, onhighway 47 Driller loader Powder buggy Pneumatic blast agent loader Explosives Prill loader Pop shooter 48 Pump 51 Dump bins Raw coal storage Tipple 52 Motor grader Motor patrol Road grader 53 Track drill Jackleg Airleg Drifter drill Stoper drill Diamond drill Jackhammer Hydraulic drill Rock drill Buzzy drill Jumbo drill Code Description 54 Pinner Scaler Roof bolting machine Rock bolting machine Trussbolter 55 Rock dusting machine 56 Rump rail Rotary dump 57 Scoop, surface Self-loading scraper Scraper loader Pan scraper Tractor scraper 58 Vibrator Shaker Screen 60 Dragline Power shovel Dragline bucket Big muskie Stripping shovel Gradall Backhoe Clamshell 61 Buggy Shuttle car Ram car 64 Tamping machine Railroad tie packer 65 Track maintenance Track repair equipment 66 Elkhorn Tractor, underground Supply car 67 Service truck Pickup truck Water truck Dump truck Trash truck Utility truck 69 Washers 70 Welding machine Torch 71 Drilling rigs Machines, not elsewhere classified Wheelbarrows Rock rake Hydroseeder Impact roller 80 Lab equipment 83 Calciners Kilns Furnaces Dryers 85 Heavy equipment Mobile equipment 91 Controls Consoles 92 Scales 95 Miscellaneous utility equipment 96 ....._. Feeder 97 General or many equipment 98 Not elsewhere classified 99 Not specified 13 APPENDIX C— ESTIMATION PROCEDURES Establishment weight. — Suppose one out of every five mine establishments in a sampling stratum (industry-mine type-employment size class-status) was selected. Then, the sampling ratio is 1/5, and the establishment weight (EWT) is 5.00, the inverse of the sampling ratio. Nonresponse adjustment factor. — Also suppose in a given sampling stratum, 80 pet of the establishments that were within the scope of the survey responded. Then, the nonre- sponse adjustment factor (NRAF) is 1.25 (i.e., 100/80). Worker weight. — Additionally, there was the sampling ratio with which the workers in the establishment were sam- pled; the worker weight (WWT) ranged from 1 .00 to 30.00 (see the first page of MIPS questionnaire in appendix F). Theoret- ically, all the workers in a sampling stratum should have had the same weight. Hence, there would have been no need to assign weight at the worker level as the worker weight could have been incorporated into the establishment weight. In practice, however, this is seldom the case because for a few establishments the employment level changes from what it was on the sampling frame to the time of the survey data collec- tion. Since all the establishments did not report in the same employment size class that they were sampled in, it was necessary to also assign each worker a weight. Final weight. — For the purpose of computing the esti- mates, each worker was assigned a final weight (FWT), which was the product of establishment weight (EWT), nonresponse adjustment factor (NRAF), and the worker weight (WWT). That is, FWT = EWT X NRAF X WWT. Estimates of number of workers. — The estimates of the total number of workers were computed by (1) summing the final weights over the appropriate domain, and (2) rounding the sum to the nearest integer. Example: To estimate the total number of truck drivers in the anthracite coal industry: 1. Compute x = £ FWTj, where, the domain D was the set of all records (workers) that had an industry code of anthracite and occupation code of truck driver. 2. Compute y = round (x). Estimates of mean. — The estimates of mean age (training) were computed by summing over the appropriate domain (1) the product of age (training) and final weight, (2) the final weights, and then, (3) dividing the sum of the products by the sum of the weights and rounding the result to the nearest whole number. It should be noted that for each domain only these entries where age (training) was specified were included in the computation: Example: The mean age of the blasters in the coal industry was estimated as follows. 1. Compute x = £ (Age , * FWT;). 2. Compute y = £ FWT ; , where, domain D is the set of all records on the coal file (anthracite as well as bituminous industry) that had an occu- pation code of blasters with age being specified. 3. Compute z = round (x/y). Estimates of median. — The estimates of median job, company, and mining experience were derived by (1) sorting the records within the domain in ascending order of the experience for which the median statistic was desired, (2) computing the total number of workers (NW) in the domain by summing the final weights, and (3) selecting the experience corresponding to the middle worker (s) in the ordering. That is, if NW is an odd number, then the median experience is the experience corresponding to the (NW/2 + l)th worker in the ordering; if NW is an even number, then the median experience is the midpoint (rounded to the nearest integer) of the experi- ence corresponding to the (NW/2)th and (NW/2 + l)th worker in the ordering. As with the mean estimates, the median estimates also excluded those entries in the domain with unspecified experience. 14 APPENDIX D.— RELIABILITY OF ESTIMATES: RANDOM GROUP VARIANCE TECHNIQUE The random group method of variance estimation em- ployed in this study consisted of selecting eight samples using the same sampling scheme for each sample as the parent sample. The primary sampling units (establishments) were divided into two sets. The first set consisted of noncertainty (probability of selection less than 1 .00) primary sampling units sorted by their original industry-mine type-employment size class-status. A random integer, say j, between 1 and 8 was generated. The first primary unit in the ordering was assigned to the random group j , the second to the random group j + 1 , and so forth in a modulo 8 fashion. Then, the secondary sampling units (workers) were assigned the same random group number as the primary unit to which they belonged. The second set consisted of all secondary sampling units belonging to the certainty (probability of selection equal to 1.00) primary sampling units. The secondary sampling units were sorted by the same scheme as above, and a random integer, say k, between 1 and 8 was generated. Then, the first secondary unit in the ordering was assigned to the random group k, the second to the random group k + 1, and so forth in a modulo 8 fashion. Hence, each worker belonged to a random group. For a more detailed discussion of the random group technique, the reader is referred to reference 4 of the main text. The following procedure was followed in computing the estimated variance (var), standard error (s), and the coefficient of variation (CV) for the estimated number of workers belong- ing to a particular category. 1. The domain (i.e., category) was defined. 2. A separate estimate for total number of workers, 9;, for each of the eight random groups was computed. If any random group was empty, then a zero was assigned to that random group. 3. Total number of workers, 0, for all eight groups was computed as e = e, + e 2 + ... + e 8 . 4. The mean number of workers per group was computed as e = e/8. 5. The variance fore was computed as ri (0= -I) 2 var (0) = 8 JJ ' • i=l ' 6. The standard error of was computed as s(0) = V var (e). 7. The CV forG was computed as CV (9) = M£* X 100.0. e 15 APPENDIX E.— COAL MINING 1986 WORKFORCE ESTIMATES TABLE E-1.— Coal mining 1986 workforce estimates: employment size class, by type of coal mined Anthracite Bituminous Total Employment size class 1 Workers pet Workers pet Workers pet 1-19 1,016 39 16,999 11 18,016 12 20-49 882 34 21,495 14 22,377 15 50-99 300 12 14,473 10 14,773 10 100-249 380 15 34,248 23 34,628 23 250-499 41,935 28 41,935 28 500+ 20,009 13 20,009 13 Total 2,578 100 149,158 100 151,737 100 1 MSHA size groups are based on the annual average employment of the primary subunit and not on the total employment; hence, MSHA published injury statistics by size groups should not be analyzed against these data. NOTE.— Owing to independent rounding, data may not add to totals shown. TABLE E-2.— Coal mining 1986 workforce estimates: job title, by type of coal mined Anthracite Job title grouping 1 Workers pet Backhoe-crane-dragline-shovel operator 188 7 Beltman-belt cleaner-belt repairman 7 Blaster 9 Continuous miner and related machine operator 4 Deckhand-barge and dredge operator 3 Dozer-heavy and mobile equipment operator 101 4 Driller-auger operator 110 4 Electrician-wireman-lampman 50 2 Front-end loader operator 132 5 Grader-scraper operator 12 Laborer-miner-utility man 620 24 Longwall operator Manager-foreman-supervisor: General 187 7 Maintenance 2 Working 6 Mechanic-welder-oiler-machinist 503 19 Mine technical support 90 4 Office worker 81 3 Plant operator-warehouseman 160 6 Roof bolter-rock driller Scoop tractor operator-motorman 15 1 Shuttle car operator Truck driver 301 12 Total 2,578 100 'As defined by MSHA; see appendix A for detailed explanation of job title grouping. NOTE.— Owing to independent rounding, data may not add to totals shown. Bituminous Total Workers pet Workers pet 2,825 2 3,013 2 5,214 3 5,221 3 1,209 1 1,218 1 6,433 4 6,437 4 232 235 10,480 7 10,580 7 2,762 2 2,872 2 6,155 4 6,205 4 4,192 3 4,324 3 2,446 2 2,459 2 22,647 15 23,267 15 1,036 1 1,036 1 9,214 6 9,400 6 2,250 2 2,252 1 5,515 4 5,521 4 22,735 15 23,237 15 6,707 4 6,797 4 5,261 4 5,342 4 5,735 4 5,895 4 8,206 6 8,206 5 5,261 4 5,277 3 5,646 4 5,646 4 6,997 5 7,297 5 149,158 100 151,737 100 16 TABLE E-3.— Coal mining 1986 workforce estimates: 1 principal equipment operated, by type of coal mined Anthracite Equipment operated grouping 2 Workers Backhoe-crane-dragline-shovel 181 Belt 10 Continuous miner and related machinery 4 Dozer-heavy and mobile equipment 103 Explosives 9 Front-end loader-forklift 167 Grader-scraper 12 Handtools (powered and nonpowered) 390 Hoist 41 Locomotive-mine car 19 Longwalls and parts Many equipment 29 Miscellaneous utility equipment 490 Plant equipment 136 Rock dusting machine-pump 2 Roof bolting machine-underground drill 23 Scale-lab equipment-controls 26 Scoop Shuttle car Surface drill-auger 92 Truck (haulage) • 310 Truck (utility)-personnel carrier 6 Welding machine-lathe 225 None 207 Unspecified-not elsewhere classified 14 Total 2,498 'Excluding job title category of office workers. 2 See appendix B for detailed explanation of equipment operated grouping. NOTE.— Owing to independent rounding, data may not add to totals shown. pet Bituminous Workers pet 2,887 2 5,299 4 6,222 4 9,638 7 1,209 1 5,216 4 2,868 2 25,633 18 443 3,997 3 945 1 2,859 2 12,810 9 4,108 3 1,132 1 8,844 6 2,182 2 3,853 3 5,703 4 2,055 1 7,311 5 2,487 2 4,284 3 21,735 15 178 Total Workers pet 2 4 4 7 1 4 2 18 3 1 2 9 3 1 6 2 3 4 1 5 2 3 15 7 4 7 16 2 1 1 20 5 1 1 4 12 9 8 1 100 143,897 100 3,067 5,308 6,226 9,741 1,218 5,383 2,881 26,023 484 4,016 945 2,888 13,300 4,245 1,134 8,868 2,208 3,853 5,703 2,147 7,621 2,494 4,509 21,942 192 146,395 100 TABLE E-4.— Coal mining 1986 workforce estimates: work location at mine, by type of coal mined Work location Anthracite Bituminous Total Workers pet Workers pet Workers pet 392 15 69,471 47 69,863 46 121 5 8,757 6 8,878 6 1,229 48 51,061 34 52,291 34 730 28 12,222 8 12,952 9 107 4 7,647 5 7,753 5 2,578 100 149,158 100 151,737 100 Underground mine Surface at underground mine. Surface mine Plant or mill Office Total NOTE— Owing to independent rounding, data may not add to totals shown. TABLE E-5.— Coal mining 1986 workforce estimates: 1 experience at job, company, and mining, by type of coal mined 17 Anthracite Experience, yr Workers At present job: 0< to £1 219 1< to £2 243 2< to <3 117 3< to <5 218 5< to £10 439 10< to £20 345 20< 136 Unspecified 781 Total 2,498 Median yr.... 6 At present company: 0< to £1 311 1< to <5 725 5< to £10 488 10< to £15 630 15< to £20 177 20< to £25 93 25< to £30 28 30< 35 Unspecified 9 Total 2,498 Median yr.... 7 Total mining: 0< to <1 89 1< to £5 299 5< to <10 291 10< to £15 287 15< to £20 114 20< to £25 85 25< to <30 88 30< 66 Unspecified 1,179 Total 2,498 Median yr.... 10 NAp Not applicable. 1 Excluding job title category of office workers. NOTE.— Owing to independent rounding, data may not add to totals shown. Bituminous Total pet Workers pet Workers pet 9 26,01 1 18 26,230 18 10 20,877 15 21,120 14 5 13,707 10 13,824 9 9 21,911 15 22,129 15 18 34,212 24 34,651 24 14 14,047 10 14,392 10 5 1,587 1 1,723 1 31 11,545 8 12,325 8 100 NAp 100 NAp 143,897 4 143,897 8 100 NAp 100 NAp 146,395 4 146,395 8 100 NAp 12 10,647 7 10,958 7 29 35,467 25 36,193 25 20 43,556 30 44,044 30 25 33,153 23 33,783 23 7 12,129 8 12,307 8 4 2,525 2 2,618 2 1 1,074 1 1,102 1 1 2,760 2 2,795 2 2,586 2 2,595 2 100 NAp 4 3,341 2 3,430 2 12 16,591 12 16,890 12 12 38,623 27 38,914 27 11 33,668 23 33,955 23 5 14,152 10 14,266 10 3 4,524 3 4,610 3 4 2,168 2 2,257 2 3 4,335 3 4,401 3 47 26,494 18 27,673 19 100 143,897 100 146,395 100 NAp 11 NAp 11 NAp TABLE E-6.— Coal mining 1986 workforce estimates: 1 training received, by type of coal mined Job training for last Anthracite 2 y r ' h Mean Workers pet 167 7 1-8 8 104 4 9-15 12 12 16 16 963 39 17-40 35 117 5 41-80 71 114 5 81-160 125 17 1 161+ 240 6 Unspecified NAp 997 40 Total or mean 21 2,498 100 35 NAp Not applicable. 1 Excluding job title category of office workers. NOTE— Owing to independent rounding, data may not add to totals shown. Bituminous Total Mean Workers pet Mean Workers pet 4,157 3 4,324 3 7 6,328 4 7 6,432 4 11 2,080 1 11 2,092 1 16 46,775 33 16 47,738 33 29 31,186 22 29 31 ,303 21 58 14,102 10 58 14,216 10 111 5,645 4 111 5,662 4 306 2,667 2 306 2,673 2 NAp 30,956 22 NAp 31,953 22 143,897 100 35 146,395 100 18 TABLE E-7.— Coal mining 1986 workforce estimates: 1 age distribution, by type of coal mined Anthracite Age, yr Mean Workers pet 15-20 19 30 1 21-23 22 94 4 24-26 25 130 5 27-29 28 184 7 30-34 32 378 15 35-39 37 332 13 40-49 44 471 19 50+ 58 777 31 Unspecified NAp 103 4 Total or mean 42 2,498 100 39 Excluding job title category of office workers. NAp Not applicable. NOTE.— Owing to independent rounding, data may not add to totals shown. Bituminous Total Mean Workers pet Mean Workers pet 19 735 1 19 765 1 22 2,946 2 22 3,040 2 25 7,750 5 25 7,879 5 28 14,541 10 28 14,725 10 32 31,287 22 32 31 ,665 22 37 28,222 20 37 28,554 20 44 33,971 24 44 34,441 24 56 22,682 16 56 23,459 16 NAp 1,763 1 NAp 1,866 1 143,897 100 39 146,395 100 TABLE E-8.— Coal mining 1986 workforce estimates: 1 sex, race, and education, by type of coal mined Anthracite Workers Sex: Male 2,487 Female 10 Unspecified Total 2,498 Race: White 2,480 Black 6 Hispanic 5 Other 5 Unspecified 1 Total 2,498 Education level: Some elementary 61 Some high school 173 High school diploma 1,148 Vocational diploma 151 Some college 35 College degree 52 Unspecified 877 Total 2,498 Excluding job title category of office workers. NOTE.— Owing to independent rounding, data may not add to totals shown. Bituminous pet Workers pet Total Workers pet 100 100 100 100 139,876 3,317 704 143,897 143,897 143,897 97 2 100 100 100 142,363 3,328 704 146,395 146,395 146,395 97 2 100 99 134,640 94 137,120 94 3,606 3 3,612 2 912 1 917 1 2,927 2 2,932 2 1,812 1 1,814 1 100 2 8,409 6 8,470 6 7 19,207 13 19,380 13 46 66,266 46 67,413 46 6 10,221 7 10,372 7 1 12,411 9 12,446 9 2 6,367 4 6,419 4 35 21,017 15 21 ,894 15 100 TABLE E-9.— Coal mining 1986 workforce estimates: job title, by employment size class 1 19 1-19 20-49 50-99 100-249 250-499 Job title grouping 2 Workers pet Workers pet Workers pet Workers pet Workers pet Backhoe-crane-dragline-shovel operator 525 3 487 2 361 2 766 2 673 2 Beltman-belt cleaner-belt repairman 355 2 643 3 331 2 1,281 4 1,682 4 Blaster 217 1 241 1 184 1 207 1 295 1 Continuous miner and related machine operator 711 4 853 4 379 3 1,668 5 2,156 5 Deckhand-barge and dredge operator 136 1 26 15 42 15 Dozer-heavy and mobile equipment operator 1,902 11 2,265 10 1,266 9 1,888 5 1,859 4 Driller-auger operator 640 4 557 2 362 2 486 1 539 1 Electrician-wireman-lampman 381 2 773 3 806 5 1,428 4 2,057 5 Front-end loader operator 1,616 9 1,264 6 555 4 699 2 166 Grader-scraper operator 268 1 366 2 243 2 653 2 688 2 Laborer-miner-utility man 1,750 10 2,326 10 1,636 11 5,945 17 8,431 20 Longwall operator 231 1 486 1 Manager-foreman-supervisor: General 2,109 12 2,077 9 909 6 1,629 5 1,948 5 Maintenance 80 135 1 210 1 510 1 809 2 Working 232 1 523 2 358 2 1,370 4 2,161 5 Mechanic-welder-oiler-machinist 1,442 8 2,765 12 2,488 17 5,250 15 6,752 16 Mine technical support 727 4 871 4 674 5 1,715 5 1,832 4 Office worker 902 5 809 4 581 4 1,251 4 1,210 3 Plant operator-warehouseman 653 4 1,092 5 855 6 1,344 4 1,248 3 Roof bolter-rock driller 903 5 1,311 6 565 4 2,036 6 2,312 6 Scoop tractor operator-motorman 861 5 788 4 392 3 1,130 3 1,418 3 Shuttle car operator 307 2 687 3 483 3 1,762 5 1,865 4 Truck driver 1,299 7 1,518 7 1,118 8 1,335 4 1,333 3 Total 18,016 100 22,377 100 14,773 100 34,628 100 41,935 100 1 MSHA size groups are based on the annual average employment of the primary subunit and not on the total employment; statistics by size groups should not be analyzed against these data. 2 As defined by MSHA; see appendix A for detailed explanation of job title grouping. NOTE.— Owing to independent rounding, data may not add to totals shown. 500 + Total Workers pet Workers pet 200 1 3,013 2 928 5 5,221 3 75 1,218 1 669 3 6,437 4 235 1,400 7 10,580 7 287 1 2,872 2 760 4 6,205 4 25 4,324 3 240 1 2,459 2 3,178 16 23,267 15 319 2 1,036 1 729 4 9,400 6 507 3 2,252 1 878 4 5,521 4 4,540 23 23,237 15 979 5 6,797 4 589 3 5,342 4 702 4 5,895 4 1,079 5 8,206 5 689 3 5,277 3 541 3 5,646 4 695 3 7,297 5 20,009 100 151,737 100 hence, MSHA published injury 20 TABLE E-10.— Coal mining 1986 workforce estimates: 1 principal equipment operated, by employment size class 2 1-1 9 20-49 50-99 100-249 250-499 Equipment operated grouping 3 Workers pet Workers pet Workers pet Workers pet Workers pet Backhoe-crane-dragline-shovel 593 3 494 2 358 3 682 2 691 2 Belt , 432 3 646 3 331 2 1,288 4 1,682 4 Continuous miner and related machinery 699 4 814 4 347 2 1,650 5 2,140 5 Dozer-heavy and mobile equipment 1,850 11 2,191 10 1,104 8 1,767 5 1,528 4 Explosives 217 1 241 1 184 1 207 1 295 1 Front-end loader-forklift 1,925 11 1,343 6 639 5 810 2 492 1 Grader-scraper 316 2 383 2 281 2 746 2 915 2 Handtools (powered and nonpowered) 1,820 11 3,173 15 2,734 19 5,864 18 7,943 20 Hoist 55 9 7 146 193 Locomotive-mine car 110 1 259 1 348 2 930 3 1,757 4 Longwalls and parts 286 1 417 1 Many equipment 151 1 208 1 174 1 780 2 1,206 3 Miscellaneous utility equipment 1,057 6 1,522 7 888 6 3,366 10 4,446 11 Plant equipment 768 4 953 4 649 5 772 2 710 2 Rock dusting machine-pump 11 19 72 1 309 1 500 1 Roof bolting machine-underground drill 1,165 7 1,442 7 618 4 2,100 6 2,483 6 Scale-lab equipment-controls 295 2 459 2 292 2 631 2 456 1 Scoop 777 5 531 2 228 2 725 2 1,051 3 Shuttle car 307 2 687 3 487 3 1,799 5 1,882 5 Surface drill-auger 413 2 418 2 352 2 436 1 353 1 Truck (haulage) 1,331 8 1,574 7 1,206 8 1,375 4 1,439 4 Truck (utility)-personnel carrier 127 1 410 2 234 2 599 2 688 2 Welding machine-lathe 261 2 503 2 585 4 1,071 3 1,142 3 None 2,427 14 3,279 15 2,041 14 4,969 15 6,279 15 Unspecified-not elsewhere classified 8 12 30 70 35 Total 17,114 100 21,568 100 14,191 100 33,377 100 40,725 100 1 Excluding job title category office workers. 2 MSHA size groups are based on the annual average employment of the primary subunit and not on the total employment; statistics by size groups should not be analyzed against these data. 3 See appendix B for detailed explanation of equipment operated grouping. NOTE. — Owing to independent rounding, data may not add to totals shown. 500 + Total Workers pet Workers pet 250 928 575 1,301 75 174 240 4,489 74 612 242 370 2,021 393 223 1,059 75 541 541 175 695 436 947 2,947 37 1 5 3 7 1 1 23 3 1 2 10 2 1 5 3 3 1 4 2 5 15 3,067 5,308 6,226 9,741 1,218 5,383 2,881 26,023 484 4,016 945 2,888 13,300 4,245 1,134 8,868 2,208 3,853 5,703 2,147 7,621 2,494 4,509 21,942 192 2 4 4 7 1 4 2 18 3 1 2 9 3 1 6 2 3 4 1 5 2 3 15 19,420 100 146,395 100 hence, MSHA published injury TABLE E-11.— Coal mining 1986 workforce estimates: work location at mine, by employment size class 1 1-19 20-49 50-99 100-249 250-499 500 + Total Work location Workers pet Workers pet Workers pet Workers pet Workers pet Workers pet Workers pet Underground mine 5,545 31 7,556 34 4,179 28 17,370 50 25,083 60 10,129 51 69,863 46 Surface at underground mine 907 5 1,107 5 359 2 2,145 6 2,871 7 1,489 7 8,878 6 Surface mine 7,478 42 8,755 39 7,192 49 11,091 32 10,954 26 6,820 34 52,291 34 Plant or mill 2,885 16 3,725 17 2,160 15 2,038 6 1,336 3 808 4 12,952 9 Office 1,200 7 1,233 6 883 6 1,983 6 1,691 4 763 4 7,753 5 Total 18,016 100 22,377 100 14,773 100 34,628 100 41,935 100 20,009 100 151,737 100 1 MSHA size groups are based on the annual average employment of the primary subunit and not on the total employment; hence, MSHA published injury statistics by size groups should not be analyzed against these data. NOTE —Owing to independent rounding, data may not add to totals shown. 21 TABLE E-12.— Coal mining 1986 workforce estimates: 1 experience at job, company, and mining, by employment size class 2 1-19 20-49 50-99 100-249 250-499 500+ Total Experience, yr Workers pet Workers pet Workers pet Workers pet Workers pet Workers pet Workers pet At present job: 0< to <1 3,799 22 3,579 17 1,626 11 5,929 18 9,063 22 2,214 11 26,230 18 1< to <2 2,137 12 2,457 11 1,609 11 5,414 16 6,371 16 3,132 16 21,120 14 2< to £3 1,787 10 2,385 11 914 6 2,720 8 4,252 10 1,766 9 13,824 9 3< to <5 2,201 13 3,611 17 2,609 18 4,712 14 6,148 15 2,848 15 22,129 15 5< to <10 3,288 19 4,120 19 3,906 28 7,447 22 9,742 24 6,148 32 34,651 24 10< to <20 1,813 11 2,087 10 1,481 10 3,499 10 4,178 10 1,334 7 14,392 10 20< 417 2 279 1 222 2 351 1 405 1 50 1,723 1 Unspecified 1,672 10 3,050 14 1,824 13 3,305 10 547 1 1,928 10 12,325 8 Total 17,114 100 21,568 100 14,191 100 33,377 100 40,725 100 19,420 100 146,395 100 Median yr.... 3 NAp 4 NAp 5 NAp 4 NAp 4 NAp 5 NAp 4 NAp At present company: 0< to <1 3,173 19 3,120 14 696 5 2,197 7 1,306 3 467 2 10,958 7 1< to <5 5,619 33 9,181 43 3,530 25 7,747 23 7,389 18 2,726 14 36,193 25 5< to £10 3,630 21 4,286 20 5,283 37 9,836 29 12,685 31 8,323 43 44,044 30 10 143,897 1.1 'Excluding job title category of office workers. NOTE. — Owing to independent rounding, the data for individual entries on number of workers may not equal total shown. All Workers CV, pet 142,363 3,328 704 146,395 146,395 146,395 1.0 8.0 17.8 1.0 137,120 1.2 3,612 4.5 917 15.0 2,932 10.6 1,814 25.2 1.0 8,470 5.7 19,380 3.2 67,413 .9 10,372 5.3 12,446 3.2 6,419 5.3 21,894 6.2 1.0 57 APPENDIX R— MINING INDUSTRY POPULATION SURVEY LETTERS AND QUESTIONNAIRE United States Department of the Interior BUREAU OF MINES 2401 E STREET, NW. WASHINGTON, D.C. 20241 Dear Mine Manager: The Bureau of Mines, U.S. Department of the Interior, is requesting your help in conducting a survey of the mining industry. The survey is designed to char- acterize the nation's mine-worker population by occupation, job experience, training, age, and other factors. These data are necessary to accurately ana- lyze the nation's mine accidents. At this time, the information sought "by this survey cannot be obtained from any other source. Your firm was randomly selected to represent firms of a similar size in your industry. Although your response to this survey is voluntary, the validity of the results depends upon a very high response rate. We urge you, therefore, to respond as completely and accurately as possible based upon information from your personnel files, management records, or direct response from indi- vidual workers at your mine. Under no circumstances will the information you provide be identified by individual mine, company, or worker. The data will be used for statistical purposes only and the results of the survey when analyzed with accident statis- tics will be made available to the public in the form of official publications. Instructions for completing the survey questionnaire are on the enclosed survey form. Questions regarding the survey should be directed to: Ms. Shail Butani Bureau of Mines 5629 Minnehaha Avenue South Minneapolis, MN 55417 Telephone: (612) 725-4500 Thank you for your time and effort. (Note: Collect calls regarding this survey will be accepted during regular business hours, 8:00 a.m. to 4:00 p.m., Central Time.) Sincerely, If) !5< lo JO CO CO to X: V CO z S 1- o cc •= z, © .2 l±l -1 .2 c o a -1 o OS CO CO o £S c c 2 to < I- w 5 o to co co 0) 0) t— o "* — o o CO co 5— CD CM a X O LU Z To CO > o U- 2 a Q. o< >- >• LU DC > | z - o i * s o Q. 3 »- O to| w UJ § zui £ ir "■ « « o £2 3 © ra < CC I.? c CO -^ «M _■ 5 co ID I— m lO lO z 5 o o (0 ID o in a CM CO |-~- CO c c CM 3 CO (0 z o c i_ 3 t- T3 C CO -O CO co o Q. 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