Dying for Coal: The Struggle for Health and Safety Conditions in American Coal Mining, 1930-82

Dying for Coal: The Struggle for Health and Safety Conditions in American Coal Mining,1930-82Author(s): Michael WallaceSource: Social Forces, Vol. 66, No. 2 (Dec., 1987), pp. 336-364Published by: Oxford University PressStable URL: http://www.jstor.org/stable/2578744 .

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Dying for Coal: The Struggle for Health and Safety Conditions in American Coal MXinig, 1930-82*

MICHAEL WALLACE, Ohio State University

Abstract

T1his paper examines the determinants of fatal and nonfatal coal mining injuries in the U.S. from 1930-82. Three theoretical orientations are considered as expla- nations for the long-term secular decline in both fatal and nonfatal injury rates during this period: state regulation, industrial business climate, and resource mobilization theory. Previous research has pointed to the importance of state regulatory and enforcement activity as the key determinant in lower injury rates and has neglected features of the industrial business climate and the collective capacities of miners to organize effectively against unsafe conditions. The results of multivariate time series analyses suggest that these neglected factors are equally or more important than state regulatory efforts for the improved health and safety conditions in American coal mining. Several of the statistical results are illus- trated by reference to the events surrounding the 1984 accident in the Wilberg mine in Utah which killed 27 persons. It is suggested that state regulation and enforcement of safety standards should be encompassed under the resource mobilization perspective.

On December 19, 1984 an explosion and fire ripped through the Wilberg Mine in Orangeville, Utah killing 27 persons. About 90 others escaped through one of two open exits in the mine. The fire probably started when a bearing on a conveyer belt overheated about 5,000 feet into the mine and created sparks which, combined with coal dust or spillage, caused the

*Earlier drafts of this paper were presented in 1985, at the ASTON/UMIST Conference on Control of Labour Process, and in 1986, at the meetings of the Society for the Study of Social Problems. I thank Jong Soo Do for his assistance in gathering much of the data for this analysis. I also thank several people for their generous comments on earlier drafts: Daniel Cornfield, Wllliam Form, Larry Griffin, Robert Kaufman, Laurie Krivo, Toby Parcel, Charles Perrow, Beth Rubin, Verta Taylor, Charles Tilly, and two anonymous referees. I, of course, remain responsible for all errors of omission and commission. Address correspondence to the author, Sociology Department, Ohio State University, Columbus, OH 43210 ? 1987 The University of North Carolina Press 336



Dying for Coal / 337

explosion (see United Mine Workers Journal 1985b, p. 4).1 Ventilation fans helped spread the fire and smoke throughout the mine, impeding both the escape of miners and efforts of rescue teams. Eventually, rescue efforts were halted altogether until the fire could subside. Several months passed before rescue teams could reenter the mine to evacuate the bodies of the dead miners.

The accident at the unionized Wilberg mine quickly angered United Mine Workers' Association (UMWA) president Richard Trumka who claimed that accelerated productivity goals had pushed the workers and machines beyond their limits at the expense of safety and health con- siderations. Trumka asserted, "Production contests without concern for safety and health are an unacceptable race toward death" (Perl 1984). He further noted that the mine had only two exits, rather than the three or four which are the standard for a mine of Wilberg's size.

A spokesperson for the Emery Mining Company, which operated the Wilberg Mine, conceded that the company pays bonuses to miners who set production records and acknowledged that the company had been trying to set a single-day productivity record for longwall mining on the day .of the accident. However, he denied that this caused the explosion. Defending the practice of paying bonuses for increased productivity, he claimed:

They were trying to mine as much coal as they could on that shift. Breaking a record is a form of incentive and motivation for our men (sic; one of the 27 miners killed was a woman). Miners are very, very competitive people and when they have a chance to mine more coal than the day before, that's a measure of progress for them (Peterson 1984).

Despite management's protestations, Wilberg's recent record in nonfatal injury rates exceeded the national average considerably. In 1982, the Wil- berg rate was 37.23 per 1,000 workers compared to 12.21 nationwide; in 1983, 17.01 compared to 10.44; in 1984 before the December 19 accident, 11.48 compared to 10.06 (New York Times 1984). In 1984, the Mine Safety and Health Administration (MSHA) had cited the mine for 114 safety violations, over half of which were fire-related (United Mine Workers Journal 1985b, p. 4).

The Wilberg accident is a single episode in a century-long struggle over health and safety conditions in American coal mining. For decades, the UMWA and coal operators have fought bitterly over health and safety issues, even overshadowing the bread and butter issues that typify U.S. labor-management confrontations. UMWA officials readily acknowledge the grim trade-off between productivity criteria and safety standards; that higher tonnage is frequently purchased at the cost of disabling injuries or deaths to the miners. Still, in its struggle for stronger legislation governing safety conditions and for stricter enforcement criteria, the union has met



338 / Social Forces Volume 66:2, December 1987

P1.r9 Min Inpection Ac Federa Cod Min Safety At Federa Coal Mie Heal and 1.9 8 Peod of 1941 passed of 1952 passed Sat A of 1969 passed

1.7 -e-oFatal Injuries 50

1.6 --.Nonfatal Injuries 80.00

1.5 -075.00

1.4 ~~~~~~~~~~~~~~~~~~~~70.00 1.3 - 65.00

55.00 C-I

5 ~~~~~150.00

~~~~0.9 1 ~~~~~~~~~~~~~~~~~45.00 0.8 ~~~~~~~~~~~~~~~~~~~~40.00

0.7 -35.00

0.6 1 ~~~~~~~~~~~~~~~~~~~~30.00 0.5 -25.00

0.4 1 ~~~~~~~~~~~~~~~~~~~~20.00 0.3 15.00

1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985

YEAR, 1930-1982

Figure 1.

with occasional, but significant, success. Though mine operators acknowledge that safety standards can always be improved, they note that the danger and uncertainty inherent in coal mining constitute major obstacles to significant improvements. They further contend that many injuries result from operator error, unsanctioned shortcuts in work operations, or other human foibles-factors that cannot be eliminated easily by legislative mandate.2 And since the owners regard regulation as a bane to further productivity, they have resisted further legislation to reduce coal mining accidents.

At stake in this controversy are the lives and welfare of workers who mine coal above and below ground. Since 1900, over 103,000 workers have perished in American coal mines; another 1,750,000 have suffered disabling injuries in accidents since 1930 (when tabulation of nonfatal injuries by federal agencies began; figures do not include black lung victims). Fortunately, both fatal and nonfatal injury rates have declined secularly in this century, suggesting some progress in making mines a safe place to work. In 1907, the most disastrous year in American coal mining history, 3,242 miners were killed in accidents-a rate of 4.81 deaths per 1,000 workers in the industry. Since 1971, the annual average has been about




140 or .71 deaths per 1,000 workers. A similar-but less dramatic-pattern exists for nonfatal injuries (see Figure 1).3 The fatal injury rate is more volatile because of greater year-to-year fluctuations in the number of deaths relative to disabling injuries. The gradual but steady progress against coal mining accidents is a major (and unheralded) achievement of the American labor movement.4 Still, the causes for the decline, while frequently debated, have not been studied systematically.

This paper analyzes the determinants of fatal and nonfatal coal mining injuries from 1930-82. The analysis begins in 1930 for both theoretical and pragmatic reasons. Theoretically, this date is generally re- garded as the end of the "handloading era" and the beginning of large- scale mechanization of the cutting and loading operations of the mines (Dix 1979; Yarrow 1979). Pragmatically, several variables needed in the analysis are not available prior to 1930, limiting the utility of analyses before that date. The paper focuses on three theoretical approaches for understanding the determinants of fatal and nonfatal injuries since the 1930s: state regulation, the industrial business climate, and resource mobilization. The determinants of fatal and nonfatal injury rates are then exam- ined using data which relates to each of these three perspectives.

Conceptual Framework: Explaining the Long-Term Decline in Coal Mining Injuries

THE STATE REGULATORY MODEL

While state regulation of health and safety of most jobs under the Occu- pational Health and Safety Act of 1970 is a relatively recent phenomenon (Berman 1978; McCaffrey 1982; Mendeloff 1979; Nichols & Zeckhouser 1977), the state has been actively involved in regulating coal mine safety for over 45 years. Several previous analyses of the determinants of coal mine safety by political scientists have focused almost exclusively on the role of Congressional legislation in reducing the incidence and severity of coal mining accidents (Christenson and Andrews 1973; Lewis-Beck & Al- ford 1980; Perry 1982). Some of these studies analyze fatality rates and ignore nonfatal injury rates. This paper analyzes both fatal and nonfatal injury rates. While the expected patterns may be most prominent in the case of fatal injury rates, many of the same mechanisms should affect nonfatal injury rates.

Prior to 1941, the safety of coal miners was left largely to the discre- tion of individual mine operators. Although the Bureau of Mines was created in 1910 to address the hazards of coal mining, few, if any, federal guidelines were established to regulate mine conditions. The patchwork of state laws and regulations that existed were generally weak and ineffec-




tual. In some cases, adherence to piecemeal standards was secured by the UMWA in their collective bargaining agreements with individual operators or enforced by the collective capacities of the miners through work stoppages or slowdowns. Mine inspections were rare or nonexistent and the coal operators usurped ultimate control over decisions about safety procedures. This "preregulatory period" was characterized by frequent and large accidents with a high rate of injuries.

In subsequent years, three major pieces of coal mine legislation were passed to improve conditions. The first, the Mine Inspection Act of 1941, gave federal inspectors the right to inspect the mines and make recommendations which were nonbinding on the owners. Coal operators bitterly opposed this law, branding it "sheer communism" (Bethell 1972, p. 78). Despite their resistance and the fact that the law gave federal inspectors very little authority to enforce compliance with regulations, the law seemed to have a perceptible effect on improving safety conditions (see Figure 1). Lewis-Beck and Alford attribute most of the law's apparent impact to its "birth order":

The law appears to have been effective because it was the first law introduced into a lawless situation. At the national level, the rules for mining safety were suddenly changed from none to some.... Workplace safety had been so neglected that a number of improvements could be made cheaply and simply. Surely, in response to or in preparation for the federal inspector's visit, some operators would be moved to narrow the spacing of roof bolts, replace a fallen support, remove piles of explosive dust, check the machinery wiring, or put a protective canopy over the mine entrance.

The Mine Inspection Act of 1941 apparently exerted downward pressure on coal fatalities for about a decade, after which its effects seemed to diminish.

In response to continued pressure for progress in mine safety, Con- gress passed the Federal Coal Mine Safety Act of 1952. This law, which effectively superseded the 1941 law, focused primarily on large mines and had little impact on mines employing 15 miners or less (which, by then, accounted for about 80 percent of all mine workers). As a result, the 1952 law is generally perceived as doing little to improve overall safety (An- drews & Christenson 1970; Lewis-Beck & Alford 1980; Perry 1982). This was also a period in which the attention of the UMWA and the coal operators centered on problems of declining productivity and increased mechanization of the coal mines (Navarro 1983). As a result, the 1952 law was not strenuously enforced by the union, management, or the state (Lewis- Beck & Alford 1980; McAteer 1973). Lewis-Beck & Alford (1980, p. 751) refer to the 1952 legislation as a "symbolic law" for, while it relieved public concern that nothing was being done, it produced no tangible improvement in coal mining safety.




By the late 1960s, the shortcomings of the two previous laws were apparent. Existing regulations largely ignored smaller mines and the enforcement capacity of regulatory agencies was weak. With the dramatic increases in productivity in the 1950s and 1960s, progress in safety standards levelled off and public concern about safety resurfaced. In 1969, Congress passed the Federal Coal Mine Health and Safety Act with the goal of providing a comprehensive approach to coal health and safety issues (induding efforts to reduce black lung disease; see Judkins 1979; B. Smith 1981). This law supplanted the 1952 law. An extensive array of regulations was imposed on mines of all sizes, and government inspectors were given broader enforcement powers through fines and other penal- ties. Consequently, after 1969, coal mining fatalities again decined notice- ably, prompting optimism among adherents of the regulatory model: "The 1969 legislation seems to offer a long-term solution to the coal mine safety problem, i.e., under its continued enforcement, safety should eventually reach an acceptable level" (Lewis-Beck & Alford 1980, p. 752).

Empirical studies of the effect of legislative context on coal mining safety have been fairly consistent in their findings: The 1941 law repre- sented a marked improvement over the preregulatory period because it encouraged mine operators to clean up sloppy practices. The 1952 "symbolic" law, limited in scope and not rigorously enforced, did not measur- ably improve conditions beyond the level achieved by the 1941 legislation. The 1969 law extended the scope of regulation to smaller mines and strengthened enforcement capacity, thus leading to a renewed decline in fatal and nonfatal injuries.

Some advocates of the state regulatory model differentiate between the impact of passing stricter legislation and the enforcement capacity of federal agencies such as the MSHA and its predecessors. The MSHA has primary responsibility for implementing safety standards, mine inspections, levying fines for violations, and other enforcement activities. Perry (1982) has argued that enforcement capacity of federal agencies, as reflected in their annual budgetary expenditures for safety enforcement, is perhaps more important than legislation. Supporting his argument, Perry shows that such expenditures are correlated at -.90 with fatality rates for the period 1930-79. State regulatory activity thus has two dimensions- legislation and enforcement-which may have a bearing on injury rates.

INDUSTRIAL BUSINESS CLIMATE

Though not a coherently articulated "model" for explaining injuries, a set of variables indexing industry-specific conditions in coal mining that have been partly or wholly neglected in previous research should be considered. These variables comprise the industrial business climate. One char- acteristic of the industrial business climate in the past 50 years is the shift




from underground to surface mining. During this period, the percentage of coal mined underground has dropped steadily from 96 to 40 percent. Two developments account for this trend: the increased sophistication of above-ground technology, in particular, large earthmoving equipment, has made surface mining more economically feasible; and, while safety regulations are directed toward both underground and surface mining, the fi- nancial burden of stricter regulation falls most heavily on underground mines. Thus, especially since the 1969 law, there has been a strong finan- cial incentive to shift to surface mining. Surface mining (or strip mining), though dangerous in its own right, results in only one-third as many (fatal and nonfatal) injuries per million personhours worked as underground mining (King 1983; Perry 1984; but see Weeks & Fox 1983, for evidence that the gap is narrowing). These observations suggest a positive relation between underground coal mining and both the fatal and nonfatal injury rates; hence, part of the decline in injury rates in Figure 1 may be due to the long-term shift from underground to surface mining. If so, the puta- tive impact of state regulatory factors might be artifactual.

Another factor related to coal mining injuries is the average number of employees per mine, but its effect is difficult to discern. Large mines, of course, mean that more miners are exposed to risk of death or injury from a single accident. Historically, the worst mining disasters have occurred in large mines, reinforcing the belief that they are inherently more dangerous. However, a presumed thrust of federal regulatory efforts-even the weaker 1952 law-has been to reduce the hazards in large mines. One simple regulation that helped reduce the human toll of accidents is the maintenance of multiple exits in larger mines. Thus, if a fire or roof fall blocks one exit, alternative exits are available. (However, as the Wilberg accident attests, enforcement of this rule is not guaranteed.) Prior to federal regulations governing the number of entrances to the mine, a single explosion could spread fire or deadly methane gas throughout the mine, killing hundreds of workers in a matter of minutes. Other regulations govern the installation of ventilation fans to keep the air free of combusti- ble coal dust or methane gas.5

Because large mines are more visible to the regulators, legislative enactments may have altered the impact of mine size on safety. Industry experts today seem more concerned about the safety hazards of small mines which are less subject to rigorous mine inspections and less likely to be unionized (National Research Council 1982). One recent statistical report by the UMWA claimed that chances of being killed on the job are four times greater in mines with under 50 employees than at larger mines (United Mine Workers Journal 1985a, p. 9).

Christenson and Andrews (1973) found conflicting results of mine size in their analysis of injury rates in underground bituminous coal mining. They found average mine size to be inversely related to fatal coal min-




ing injuries, but positively related to nonfatal injuries (see also Andrews & Christenson 1970). Their results, however, covered only the 1940-65 period. When the analysis is extended over a longer period (1930-82), a positive relation between mine size and both fatal and nonfatal injury rates is expected. Though there is conflicting evidence as to what this effect should be, especially for fatal injuries, large mines are likely to be more dangerous once other dimensions of industrial business climate are controlled.

Managers' productivity demands were central in the controversy surrounding the Wilberg accident of 1984, as they are in virtually every large accident involving loss of life. Similar concern has been expressed by persons studying the connection between safety and health in other work settings (Grunberg 1983; Oi 1974). Productivity norms have a com- plicated role in the labor process frequently binding workers and owners together in a strategy which undermines adequate safety precautions.6 Productivity is generally linked to higher profits, giving owners sufficient reason for demanding higher output. And, especially in unionized settings, higher wages and benefits are often pegged to productivity, giving workers incentive to maintain high levels of output even at risk to their own health. Caudill thus argues that miners are unwitting accomplices in their own demise because they are "hooked on high wages and resent any action that might cost them a shift" (1977, p. 496). While the -two-edged relationship between productivity and safety is present in many work settings, it takes on potentially disasterous consequences in jobs as inherently dangerous as coal mining. At a given state of technological develop- ment and enforcement effort, stepped up productivity is likely to lead to shortcuts and violations of safety standards.7 Or, conversely, closer adherence to safety regulations (not taking shortcuts) means that a larger portion of the working day is devoted to "nonproductive" activities. This reasoning suggests that productivity will be positively related to injury rates.

Because of its primacy as an energy source for industry, coal mining activity tends to be closely linked to the rhythms of the business cycle. In prosperous times, demand for coal is high; during recessionary periods, industrial activity slacks off and coal production declines accordingly (Navarro 1983). How should the business cycle affect coal mining safety? When demand for coal increases, two things happen which could have negative effects for conditions in the mines. First, extraction of coal is increased through an intensification of the labor process. As suggested above, speedup of production frequently leads to hazardous shortcuts or outright disregard for ordinary safety precautions. Second, increased demand for coal may bring smaller, unproductive mines back into operation. These marginal mines, which have typically exhausted the major portions of their coal reserves, are more dangerous because they require greater




human effort and risk to extract additional coal. While out of business during bad times, the lure of higher prices brings these otherwise non- profitable (and unsafe) mines back into operation. This reasoning suggests the rhythms of the business cycle may affect trends in coal mining injury rates, even independently of productivity. Upswings in the general economic climate should exacerbate injury rates, and recessionary periods should decrease injury rates in subsequent periods (for a similar argument regarding the effect of the business cycle on injuries in manufacturing industries, see Cooke & Gautschi 1981).

RESOURCE MOBILIZATION THEORY

Resource mobilization theory has been applied fruitfully to the study of protest by welfare recipients (Jackson & Johnson 1974), farm workers (Jen- kins & Perrow 1977), ethnic/cultural minority groups (Ragin 1979), civil rights protesters (Morris 1984; Piven & Cloward 1977), and revolutionary challengers (Tilly 1978). Several studies using this perspective have focused on the organization and militancy of industrial workers (Piven & Coward 1977; Ragin, Coverman & Hayward 1982; Shorter & Tilly 1974; D. Snyder 1975, 1977), the counter-organization of employers against worker movements (Griffin, Wallace & Rubin 1986), and the coal miners' black lung movement of the 1960s (Judkins 1979).

Resource mobilization theory attempts to explain how disadvantaged or exduded groups gain political or social leverage by utilizing organizational resources (e.g., people, money, etc.). In contrast to other theo- ries of collective action, resource mobilization theorists assume a more or less constant stock of grievances of excluded groups and, also, that conflicts of interests emanate from institutionalized power relations among competing groups. Mobilization is seen essentially as a consequence of two processes. First, the challenging group must accumulate sufficient organizational resources to threaten the privileged position of the domi- nant group, to affect policy decisions impacting the positions of the two groups, or otherwise upset the status quo. Often, such mobilization is demonstrated by the withholding of some critical resource which is controlled by the challenging group. Second, mobilization is frequently an outgrowth of opportunities created by the shifting structure of power relations between the two groups or even fortuitous events which sway public opinion in favor of the challengers. Such changes in the "political opportunity structure" are instrumental in at last two respects: (a) they can lead to internal fragmentation of elite interests, and (b) they can draw important outside actors into the struggle on the side of challenging groups (what resource mobilization theorists call the "enlistment of conscience constituencies").

A number of other debates within the resource mobilization school




are peripheral to this analysis: the bureaucratization/professionalization of social movement organizations, the role of violent versus nonviolent forms of collective action, the counterproductive functions of organization, etc. (for a complete review, see Jenkins 1983). Here, the general framework of the theory is applied to the movement for coal mining safety. The risk of serious injury or death in coal mining accidents poses an omnipresent threat for workers, thus a "constant stock of grievances." While in a structurally disadvantaged position in capitalist social relations, coal miners' success in achieving lower injury rates can be understood in part as the result of developing sufficient resources to resist unsafe conditions. In addition, sudden alterations in the political opportunity structure draw outside actors into the controversy over safer conditions. In the following discussion, this perspective is applied to explain the declining injury rates of the past 50 years.

Historically, the debate surrounding the enactment of stricter safety legislation has been politically charged within the coal mining community, but the debate only sporadically attracts the attention of a broader public audience. During periods of relative tranquility in the mines, the day-today struggle over working conditions between miners and individual operators goes virtually unnoticed by the general public. But periodically the occurrence of a major mining disaster rivets public attention on the problem and generates more vigorous public debate over mine safety conditions. The heightened public concem often provides the opportunity for a new legislative thrust to improve safety regulations, sometimes tipping the balance in passage of stronger legislation. The linkage between major mining disasters and new safety legislation has long been suspected. After passage of the Mine Inspection Act of 1941, Wieck wrote: "Dead miners have always been the most powerful influence in securing passage of mining legislation" (1942, p. 131). Indeed, each of the three major laws cited above was preceded by a major disaster in the year before passage which mobilized public support for the legislation. Three disasters killing over 50 miners each in 1940 led to the passage of the Mine Inspection Act of 1941. An accident in West Frankfort, Illinois in 1951, killing 119 miners preceded the passage of theFederal Coal Mine Safety Act of 1952. And the death of 78 miners in a Farmington, West Virginia mine in 1968, preciptated passage of the Federal Coal Mine Health and Safety Act of 1969.8

Major coal mining disasters should have a profound influence on the political opportunity structure of the coal mining safety controversy. If these disasters have such a powerful role in the passage of stricter legislation, they should also exert downward pressure on fatal and nonfatal injury rates regardless of legislative action. How might such disasters actually lower injury rates? Obviously, injury rates in a year in which a major disaster occurred would tend to be higher ceteris paribus. But, by drawing public attention to coal mining safety, such events might improve safety




conditions in the subsequent year. In other words, the occurrence of a major mining disaster in one year might lead to lower death and injury rates in the following year due to public awareness of the problem, the operators' fears of impending regulatory action, and a heightened effort to abide by existing standards. Consequently, in the analyses below, the annual number of major mining disasters, lagged one year, should have a negative impact on fatal and nonfatal injury rates.

In capitalist society, ultimate control of the conditions of employment, induding working conditions, rests with employers. But judicious utilization of worker-controlled resources can countervail employer power. Through their collective capacities to organize into labor unions and to withhold their labor power from the production process by striking, workers have two important resources for reacting to the practices of employers. In this century, then, American coal miners have used both "institutionalized" (the union) and "noninstitutionalized" (strikes) resources (Isaac & Kelly 1981) with remarkable success to improve the working conditions in their industry.

The UMWA has organized a large portion of the industry's work force since 1890 and has almost exdusive jurisdiction over the underground sector of the industry. During the 40-year reign of John L. Lewis as UMWA president, the union consolidated its power in the coal fields and became a force to be reckoned with in bargaining with coal operators (Perry 1984). Though any union exists to provide better economic benefits for its members, the UMWA-by virtue of the hazardous conditions faced by its membership-has pressed vigorously for safer working conditions. First, the union has argued consistently for stronger state and federal legislation to regulate safety standards in the mines. Second, on a day-today basis the union .presence at individual mines has given the miners a voice in implementing and enforcing existing standards. Establishment of health and safety committees by UMWA locals and a standing depart ent at the national headquarters concerned with safety issues strengthen the miners' resources for this cause. Third, and perhaps most important, the union gives miners the collective strength to resist unsafe conditions at the point of production without fear of reprisal by the operators.

The second resource by which miners (in particular, but not exclusively, unionized miners) demonstrate their collective strength is the use of the strike weapon, the ultimate means of resisting unsafe conditions. By withholding their labor power from the production process, miners can protest unsafe conditions or secure additional safety concessions from operators. Coal miners are the most strike-prone of industrial workers in most countries (Cronin 1979; Kerr & Siegel 1954). And, contrary to the pattern in other industries, about 90 percent of the strikes in coal mining involve working conditions, most of them safety-related (Wallace 1987). Further, a majority of these are wildcat strikes in which rank-and-file




members strike in violation of an existing contract (Brett & Goldberg 1979; Wallace 1987). Hence, the strike serves as a safety valve for the rank-and- file, allowing them to respond quickly to dangerous conditions and to circumvent union officialdom when necessary. Together, organization and militancy provide complementary, but strategically distinct, resources to empower miners to resist unsafe working conditions. Through both institutionalized and noninstitutionalized strategies, then, workers can re- shape the conditions of employment and improve the quality of working life. If this reasoning is correct, unionization and militancy should both exert negative effects on coal mining injury rates.

It is important to acknowledge that one important theoretical issue is perhaps impossible to adjudicate definitively with the statistical analyses described below. If the expected impact of the state regulatory variables are nullified by the inclusion of resource mobilization variables in the regression model, two conclusions are possible. First, such a condition might imply that resource mobilization theory is a "superior" explanation of injury rates and that the original association between state regulation and declining injury rates was spurious. Second, resource mobilization theory may be said to 'explain' the original association between state regulatory efforts and declining injury rates. Clearly, the first conclusion seems a bit strong, given the obvious pattern of decline displayed in Fig- ure 1. The second conclusion seems more plausible since resource mobilization variables are likely to be important not only in securing stronger legislation (the direct association between major mining disasters and stronger legislation has already been cited), but also in reshaping the enforcement environment once such legislation is in place. The second conclusion, then, would suggest a more encompassing theory that explains the decline in injury rates both as a direct and indirect consequence of resource mobilization variables.

Data and Methods

All variables in this analysis are taken from an annual time series data file for the American coal mining industry which was constructed from published and unpublished sources. The analysis is conducted for the years 1930-82, the period since the end of the "handloading era" and the wide- spread mechanization of most mining processes. It also represents the period for which all data needed for the analysis were available. Multivari- ate time series regression analysis is used to estimate models assessing the determinants of injury rates. This technique is the most appropriate method for estimating dynamic, historically contingent models such as those suggested in the above discussion (Ostrom 1978).




DEPENDENT VARIABLES

The two dependent variables in this analysis-fatal and nonfatal injury rates-can be measured in a variety of ways. Naturally, absolute injury levels uncorrected by any measure of the "population at risk" were re- jected. The remaining possibilities include injury rates (a) per 1,000 workers, (b) per 1,000 "person-years" of 300 days each, and (c) per 1,000,000 personhours worked. The last is most appropriate since it provides the most stringent control for changing manpower levels during the period of the analysis. Thus, fatal and nonfatal injuries per 1,000,000 personhours worked are the dependent variables in this analysis. These measures com- bine injury rates in both bituminous and anthracite sectors of the industry.9

INDEPENDENT VARIABLES

Two aspects of state regulatory activity were discussed above: the legislative context created by new safety legislation and the enforcement capacity of federal regulatory agencies. The legislative context of coal mrining safety centers around the three laws discussed above: the Mine Inspection Act of 1941, the Federal Coal Mine Safety Act of 1952, and the Federal Coal Mine Health and Safety Act of 1969. Three dummy variables are utilized to tap the legal context of these three laws (1941-51; 1952-68; 1969-82) with the preregulatory period (1930-40) as the excluded category. Since each successive law completely superseded the one pnor to it, these dummies measure directly the impact of the three different laws. Federal enforcement capacity is indicated by the logged safety expenditures spent by federal agen- aes to enforce existing laws. Logging this variable is justified by the skew- ness in the distribution and is consistent with Perry's (1982) analysis. This provides a uniform, continuous measure of federal regulatory effort that spans different legislative eras and enforcement agencies.

Several dimensions of the industrial business climate described above are included in the analysis. First, the percentage of coal mined underground is used to index the large-scale shift from underground to surface mining that has occurred in the past 50 years. Second, average mine size, the ratio of total employees per mine, is included to test the hypothe- sis that large mines are more dangerous.10 Third, the coal production index, standardized by 1967 production levels, measures fluctuations in productivity. Fourth, in order to assess the impact of the business cycle, the aggregate unemployment rate is included. This variable is lagged one year to reflect the approximate time that it takes for changes in the general business climate to affect the demand for coal.

The previous discussion revealed that three dimensions of resource mobilization theory may be relevant to the analysis. Miners' opportunities for advancing safety issues and the potential success of legislative reform




Table 1. VARIABLES, SOURCES, LAG STRUCTURES, AND HYPOTHESIZED RELATIONSHIPS

Lag Hypothesized Variables Operationalization Source* Structure Relationship

Dependent

Fatal Injury Fatal injuries/1,000,000 1930-70, HS; rate personhours 1971-82, SA NA NA

Nonfatal injury Nonfatal inJuries/ 1930-70, HS; rate 1,000,000 personhours 1971-82, SA NA NA

I ndependent 1941 safety law Dummy variable (1942-52-1) NA t 1952 safety law Dummy variable (1953-69-1) NA t 1969 safety law Dummy variable (1970-82o1) NA t Ln safety expend Natural logarithm, safety

expendigtures by federal regulatory agencnes 1930-82, BUSG t

Pct underground Percent of coal tonnage 1930-70, HS; mined underground 1971-82, KHng t +

Pct unemployment Aggregate unemployment 1930-70, HS; rate 1971-82, SA t-l

Avg mine size Number of employees/ 1930-70, HS; number of mines 1971-82, SA t +

Coal product on P 1roducton index, 1930-70, HS; index 1967=100 1971-82, SA t + iasor minong Mining accipdents wllth 50 Unpublished tabu- disasters or more persons k Tlled lations, Ud W t-l

Ln UteW Natural logarithm. Troy and membershIp UMW membershIp Shef1In t

Strike Strikes/l1,000 ,000 frequency mining employees 1930-82, AWS t i

HS: U.S. Bureau of the Census (1975, Historical Statistics of the United States). SA: U.S. Bureau of the Census (Annual, Statistical Abstracts of the United States). BUSG: Office of Management and Budget (Annual, Budget of the U.S. Government).

King: King (1983). Troy and Sheflin: Troy & Sheflin (1985). AWS: Bureau of Labor Statistics (Annual, Analysis of Work Stoppages).

is indexed by the number of major mining disasters, that is, the number of accidents killing 50 or more persons. This variable also is lagged one year to approximate the time required for these accidents to arouse public indignation against mining conditions. The collective capacities of coal miners to resist hazardous conditions takes both institutionalized and noninstitutionalized forms. The capacity for institutionalized resistance is measured by the logged number of UMWA members." Noninstitutionalized resistance is indexed by the strike frequency rate, that is, the number of strikes per 1,000 workers in the industry. The Bureau of Labor Statistics strike statistics, from which this measure is constructed, include both sanctioned and unsanctioned (i.e., 'wildcat") strikes. The strike frequency rate is lagged one year to avoid possible simultaneity conflicts with the dependent variable'2 and to reflect the approximate time it takes for labor protest to influence injury rates.

The key variables used in the analysis, lag structures, variable sources, and hypothesized relationships to fatal and nonfatal injury rates are summarized in Table 1.




Table 2. DETERMINANTS OF FATAL AND NONFATAL INJURIES IN COAL MINING, 1930-82 (PER 1,000,000 PERSONHOURS)

(a) (b) (c) (d) Fatal Nonfatal Fatal Nonfatal

a Dummy (1942-52) _.397***a 16.05*** -.056 -6.44**

(t) (-.393) (-.439) (-.055) (-.176) Dummy (1953-69) -.504*** -30.54*** .119 -14.42***

(t) (~-574) (.-.961) (.135) (-.454) Dummy (1970-82) -1.066*** -35.28*** .183 -6.11

(t) (-1.119) (-1.023) (.192) (-.178) Ln safety expend -- -.262*** -6.17***

(t) (-1.122) (.-.729) Pct underground -- -- --

(t) Pct unemployment -- t-

(t-l) Avg mine size --

(t) Coal production index -- --

(t) Major mining disasters -- -

(t-1) Ln UMW members-hip

(t) Strike frequency --

(t-1)

Constant 1.542 74.66 3.248 114.13 Adjusted R2 .849 .930 .890 .948 Durbin-Watson 2.02 1.52 1.92 1.33 Rho -.059 .086 -.030 .121 Estimation technique GLS GLS/AR2 GLS GLS/AR2

a Unstandardized regression coefficients (standard coefficients in parentheses).

p<.10, one-tailed test.

*** P?-.05, one-tailed test, p<.01, one-tailed test.

The Present Analysis

INITIAL MODELS

The analysis of fatal and nonfatal coal mining injuries using multiple time series regression analysis is presented in Table 2. Inspection of Durbin- Watson statistics revealed that the original models estimated by ordina7 least squares (OLS) contained unacceptable levels of serial correlation." This problem was corrected for the fatal injury models (columns a, c, and




Table 2. (continued)

(e) (f) Fatal Nonfatal

-.143 -4.12 (-.142) (-.113) -.141 -8.36*

(-.161) (-.263) .121 -5.08

(.127) (-.147) -.267*** -2.65

(-1.143) (-.314) 1.227* 20.88 (.524) (.246) -.012** -.205

(-.178) (-.082) -2.48 299.66** (-.163) (.544)

.270** 47.91 (.125) (.061) -.075** -1.141**

(--O 98) (-.042) -.308*** -6.77***

(-.425) (-.257) -.022* -.746*

(-.096) (-.090) 4.27 86.83

.938 .972 2.02 1.69 -.018 .123

GLS GLS/AR2

e) by reestimation with generalized least squares (GLS). The models for nonfatal injuries (columns b, d, and f) required reestimation with GLS using a second-order autoregressive correction (GLS/AR2). Even so, some lingering serial correlation is present in columns (b) and (d). Because the direction of relationships is predicted, one-tailed tests of hypotheses are used.

Columns (a) and (b) show results when only the three legislative dummy variables are included as regressors (the exduded category, re- member, is the preregulatory period). All three dummies exert a significant, negative impact on both fatal and nonfatal injury rates, strong evidence for the role of regulation. (However, the significance of these variables in the nonfatal model may be inflated by undesirable levels of serial correlation-Durbin-Watson = 1.52.) Tests of significance for the difference between adjacent pairs of dummy variable coefficients were conducted (not shown) to determine if later laws exerted a significant improvement




over directly preceding laws. In accordance with Lewis-Beck and Alford's (1980) analysis, the 1952 law did not significantly improve upon the 1941 law in reducing fatal injury rates; however, it did cause a significant further reduction in nonfatal injury rates. The 1969 law, by contrast, seems to have caused a significant reduction over the 1952 law in both fatal and nonfatal rates, though the reduction in the latter is small. In sum, there is strong prima facie evidence that federal regulatory legislation has the presumed impact of lowering fatal and nonfatal injuries.

In columns (c) and (d), the safety expenditures variable is added to fill out the state regulatory model. For fatal injuries, the legislative dummies lose their significance and safety expenditures alone is significant. This indicates that legislative enactments may be secondary to enforcement effort in curbing fatal rates, as suggested by Perry (1982). The pattern for nonfatal injuries is mixed. Here also the safety expenditures variable is significant, but so are the dummy variables for the 1941 and 1952 laws. Ironically, only the 1969 law, which is presumed to be the strictest of the three, fails to achieve significance. (Again, the significance of coefficients in the nonfatal model may be an artifact of serial correlation- Durbin-Watson = 1.33.)

Estimates for the full model in columns (e) and (f) include indica- tors of all three perspectives: state regulatory, industrial business cimate, and resource mobilization. For fatal injuries, the safety expenditures variable remains statistically significant, but none of the legislative dummies approach significance. However, all the remaining variables in the model excepting average mine size are in the expected direction and statistically significant. Supporting the industrial business cimate approach, coal fatalities are positively associated with increases in coal mined underground and in productivity levels and inversely associated with (lagged) aggregate unemployment rates, the index of general economic conditions. The average mine size coefficient is in the negative direction contrary to expecta- tion, but is not significant. As suggested above, one by-product of the safety legislation may have been to improve conditions in large mines while having little impact in smaller mines.14

Of primary importance here are the variables indexing aspects of resource mobilization theory. As expected, major mining disasters (lagged one year) have a negative impact on fatality rates, indicating that mine operators are responsive to the public outcry that generally follows such events. Hence, such accidents not only serve as a catalyst in passing stricter legislation, as Wieck (1942) observed over 40 years ago, but also they lead to closer adherence to existing regulations. The variables indicating the collective capacities of coal miners also operate as expected. The strength in numbers of the UMWA reduces the fatality rate, attesting to the collective strength of organized labor in improving mine conditions through their presence in the coal fields and the legislative chambers. The




withholding of labor power, as indexed by the (lagged) strike frequency rate, also has the expected effect of reducing mining fatalities. The strike effect exists net of other variables in the model including the union organization effect, supporting the argument that both institutionalized and noninstitutionalized resistance is effective in lowering injury rates.

The model for nonfatal injuries in column (f) has been sufficiently purged of serial correlation to warrant confidence in the estimates (Dur- bin-Watson= 1.69). The pattern here is similar to that of the fatal injury model in column (e), but there are notable differences. Among the variables in the state regulatory model, only the dummy variable for the 1952 law is significant. That this variable alone should be significant is quite surprising since others have demonstrated that this law had little impact in lowering fatal injury rates. Conceivably, since the thrust of the 1952 law was directed toward larger mines, major improvements in nonfatal injuries in that sector helped to lower the overall rate. Otherwise, this result should be viewed with a bit of skepticism.

Of the variables indexing industrial business climate, only the average mine size effect is significant (and positive). Though this corresponds with original expectations, it is a departure from the fatal injury models where this variable was negative and not significant. It coincides, however, with the findings of Christenson and Andrews (1973) mentioned above. Also contrary to the fatal injury model, none of the other three industrial business climate variables achieve statistical significance although all are in the expected directions.

Finally, as with fatal injuries, all three of .the resource mobilization variables are statistically significant determinants of nonfatal injuries. De- clines in the nonfatal injury rate are associated with (lagged) major mining disasters, membership in the UMWA, and (lagged) strike frequency rates. Overall, the model performs less satisfactorily for nonfatal injuries than for fatal injuries (the higher adjusted R square in the nonfatal model is attributable to the trending factor in the nonfatal series and not a particularly good indication of explanatory power). But standardized regression coefficients for significant variables indicate that UMWA membership is a very important determinant, behind average mine size and the 1952 law dummy.

Exandnation of residuals revealed that only one out of 53 observations in the fatal model (1968) and one out of 53 in the nonfatal model (1974) exceeded two times the standard errors of the estimate for the re- spective models.15 Together, the results for both fatal and nonfatal injury rates support the primary argument made in this paper that resource mobilization theory contributes importantly to the explanation for improving mine safety since the 1930s. The three resource mobilization variables are the only variables to be statistically significant in the full models for both fatal and nonfatal injuries.




Table 3. THREE-STAGE LEAST SQUARES ESTIMATES OF FATAL INJURY RATES AND COAL PRODUCTiON INDEX, 1930-82

(a) (b) Fatal Coal

Injuries Index

Fatal Injury rate -- -1.213 (t) (-2 .615)

Coal production index .361* (t) (.167)

Dummy (1942-52=1) -.176 -.161 (t) (-.175) (-.344)

Dummy (1953-69=1) -.170 J .359 (t) (-. 193) (-.882)

Dummy (1970-82=1) .070 .195 (t) (.074) (.442)

Ln safety expend -.254*** -.332 (t) (-1.086) (-3.064)

Pct underground 1.425** -.118 (t) (.609) (-.109)

Pct unemployment -.013** --

(t-l) (-.182) Pct unemployment -- - .042*

(t) (-1.31) Avg mine size -2.911 4.009

(t) (-.191) (.567) Major mining disasters -.091*** -.083

(t-l) (-.119) (-.233) Ln UMW membership -. 308*** - .379

(t) (-.425) (-1.126) Strike frequency -.017 -.082*

(t-1) (-.077) (-.775)

Constant 3.97 7.74 System R2 -- 0976 --

Adjusted R2 .940 .258 Durbin-Watson 2.11 1.83 Rho - .069 .087

aUnstandardized regression coefficients (standardized coefficients in parentheses). *

p<.l0, one-tailed test (a); p<.10, two-tailed test (b).

p<.05, one-tai led test (a); p<.l10, N:o-tai led test (b) .

p<.01, one-tailed test (a); p<.01, two-tailed test (b).




ALTERNATIVE MODELS

In general, the estimates provided in Table 3 appear stable and robust in the face of a series of alternative model specifications, lag structures, and variable operationalizations. A subset of these alternative procedures is summarized here.

First, a time trend variable was added to the full model for both fatal and nonfatal injury rates as a global control for a variety of unmea- sured variables which may have been excluded from the model. This variable was not significant in the fatal injury model and significantly negative in the nonfatal injury model. More importantly, the substantive implications of the full models shown in columns (e) and (f) of Table 3 are hardly affected. Only the coal production index effect in the nonfatal model is altered, turning positive and significant (as had been predicted). The in- sertion of a more stringent global control-the lagged endogenous variable-had similarly marginal impact. In the fatal injury model, only the (lagged) strike frequency effect turns nonsignificant (not predicted). In the nonfatal model, the percent underground and coal production index effects turn positive and significant (predicted). Overall, then, the general implications of the model in Table 3 remain virtually unaffected after con- sideration of these alternatives.

Arguably, the most serious omission from the model is the lack of any indicator of technological trends in the industry. Aside from the tran- sition from underground to surface mining, the major change in mining procedures over the past 50 years has been the increasing mechanization of all phases of coal production. While mechanization has undeniably re- duced the absolute level of injuries by displacing human labor, its effect on injury rates is difficult to predict.'6 An extensive search of published statistics failed to turn up a completely satisfactory indicator of technological trends. The best measures found were three that indicated the number of tons of coal mechanically (a) cut, (b) loaded, and (c) cleaned. Even so, these particular series ended in 1975.17 The full model was thus reestimated for the truncated series (1930-75) three times, adding one at a time the logged tons of coal mechanically processed in each of these phases.

In the reestimates of the fatal model, none of the technology variables achieved statistical significance and none of the other estimates in the model were altered. In the reestimates of the nonfatal model, two of the technology variables (loading and cleaning) showed significant negative impacts on injury rates. The inclusion of these variables caused the (lagged) unemployment variable to turn significantly negative (predicted), but there were no other changes. Hence, after including the best available control for technological trends, the substantive conclusions indicated above remain unaltered.

The estimates produced in Table 2 may be artifacts of the way in




which the dependent variables are operationalized. The models were thus reestimated substituting the absolute injury levels (fatal and nonfatal) for the injury rates. As suggested above, this operationalization differs significantly from the one used in Table 2 by not controlling for the "population at risk." The reestimation of the fatal model produced two significant departures from the previous model. The (lagged) strike frequency rate turned nonsignificant (not predicted), and the mine size effect turned positive and significant (predicted). The reestimation of the nonfatal model produced three departures. The major mining disasters effect and the strike frequency effect turned nonsignificant (not predicted), but the underground effect became significantly positive (predicted). These reestimates thus result in more substantial modifications of the original findings, particularly for the resource mobilization variables, but modifications which must be tempered by the qualifications noted above about the use of absolute injury levels instead of rates. On balance, the procedures discussed here (and others conducted, but not discussed) do not seriously damage the key substantive findings reported in the previous section. At many points, expected relations which had not been found in the original estimates materialize; only the strike frequency effect appears somewhat unstable under these alternate specifications.

Finally, the models shown in Table 2 possibly contain one nonrecursive relation-that between injury rates and productivity. In short, taking the steps necessary to reduce injury rates may simultaneously reduce productivity (but see Sider's 1983 analysis for contrary evidence). Such a relation can yield biased and inconsistent estimates of parameter values if left untreated (Johnston 1972). First, the significantly positive effect of the productivity variable in the fatal injury model may be spurious. Second, other parameter estimates in this model may be affected by the presence of such a nonrecursive relationship. (This is not a problem in the infer- ences drawn from the nonfatal model since the productivity variable is not significant.) Johnston (1972) suggests that the appropriate procedure for assessing the extent of such nonrecursive relations is 3-stage least squares which estimates a system of equations in which models are jointly estimated for each of the endogenous variables in question.

Table 3 shows results of a 3-stage least squares analysis with fatal injury rates and the coal production index as joint endogenous variables. The main concern here is with the estimation of the fatal injury side of the model. As a result, the predictor variables in the productivity side are identical with those in the fatal injury side, with one exception. Instead of lagging the aggregate unemployment variable, it is modeled contemporaneously in the productivity side. This specification (a) conforms with speculation about the likely effect of this variable on productivity, and (b) is necessary to identify the model.

The results indicate that the relation between productivity and fatal




injury rates is recursive, as assumed in the earlier single-equation model. The positive effect of the coal production index on fatal injury rates is genuine (though the level of significance is diminished), and the fatal injury rate is not a significant predictor of productivity. Further, none of the substantive interpretations yielded by the single-equation model in Table 3 is altered, except one. The (lagged) strike frequency variable, which was shown to be somewhat unstable above, turns nonsignificant. Fortu- itously, the 3-stage least squares specification sheds light on the sources of this instability. The (lagged) strike frequency effect turns up as a significant, negative predictor of productivity. This suggests that labor militancy affects injury rates indirectly through its impact on productivity rather than directly. In other words, militancy, the noninstitutionalized vehicle for protesting hazardous conditions, appears to curb management's productivity demands, thereby reducing the possibility of injuries. This un- derscores the conceptual distinction between the two separate resources- the union and rank-and-file strike actions-by which miners can influence safety conditions in the workplace.

RETURN TO WILBERG

The Wilberg accident, though it killed 27 persons, is small by comparison to the "major" mining disasters referred to in this analysis (i.e., 50 or more persons killed). Yet, even a "minor" disaster such as Wilberg is instrumental in politicizing the issue of coal mine safety. Though no legislative initiative for stricter safety standards will be forthcoming from the U.S. Congress, Wilberg seems to have had an impact within the coal mining industry com- parable to that of the larger disasters. Table 4 presents quarterly data for 1984-85 for three key variables in this analysis: fatal injury rates, nonfatal injury rates, and productivity. Since the Wilberg accident occurred in the third week of December in 1984, the 1984-85 breakdown essentially re- veals trends in the year leading up to, and directly following, the accident. Changes from 1984 to 1985, then, may be attributed to the impact of the Wilberg disaster.

These data permit two observations relevant to the above discussion and analysis. First, consistent with the argument above, the Wilberg accident appears to have had an immediate and year-long impact in reducing both fatal and nonfatal injury rates throughout the industry. This is reflected in both the quarterly comparisons and the comparisons of the annual average for these two variables. Second, these data speak to the issue of how productivity demands are altered by highly publicized accidents. This question was not explicitly addressed in the earlier analysis. But the logic of the argument suggests that since major disasters cause mine operators to attend to safety concerns more conscientiously, they might well experience a fall-off in productivity. The data in Table 4 support



358 / Sodal Forces Volume 66:2, December 1987

Table 4. IMPACT OF THE WILBERG ACCIDENT ON INJURY RATES AND PRODUCTIVIT

Fatal Injury Nonfatal Injury Productivity Rates* Rates* Index**

1984 1985 1984 1985 1984 1985

lst quarter .335 .208 26.10 23.40 111.2 109.9 2nd quarter .278 .171 24.95 25.13 111.9 109.3 3rd quarter .179 .207 28.78 25.83 115.1 109.8 4th quarter .583 .187 25.32 22.32 106.3 113.0

Annual avg .334 .193 26.35 24.20 111.2 110.5

*Fatal/nonfatal injury rates: Mine Safety and Health Asso- ciation, Mine Injuries and Worktime Quarterly .

Productivity index: Derived from coal producttion data published by, the Department of Energy, Monthly Energy Review; and employment and hours data published by the De- partment of Labor, Employment, Hours, and Earnings.

this hunch, though the decline in productivity is not large and seems to last only three quarters after the accident. Still, the depressant effect was sufficient to reduce coal productivity in 1985 over 1984 levels. Ironically, the fourth quarter of 1984, in which the Wilberg accident occurred, had the lowest productivity rate of all eight quarters. These data thus reinforce the argument that publicly visible coal mine disasters serve as a catalyst in creating safer conditions in the mines.

Summary and Discussion

This study has introduced previously neglected factors which have con- tributed to the long-term decline in fatal and nonfatal injuries in American coal mining. The empirical results suggest that exclusive reliance on the state regulatory model-the legislative and enforcement capacity of the state-is insufficient for explaining these trends. Instead, the ebb and flow of the industrial business climate, the collective capacities of coal miners, and the opportunity structure for mounting protest are key factors in creating safer conditions. As suggested above, the issue of whether the relation between state regulatory variables and declining injury rates is spurious or merely "explained" by the inclusion of other relevant variables is ultimately theoretical, not statistical. All indications, however, point to the conclusion that the state regulatory variables should be encompassed under the resource mobilization perspective also since safety legislation




and enforcement capacity are by-products of the ongoing struggle between miners and mine operators.

In this light, one should not interpret the results of this analysis as dismissing the significance of state regulatory and enforcement activity. Each of the three laws discussed above was passed over substantial resistance by the coal operators' lobbies, attesting to the threat that stricter regulations and enforcement posed to their interests. Moreover, each successive law legitimated and reaffirmed, at least symbolically, the miners' central demands for safer working conditions. The enforcement agencies that were created and funded by these acts represent an institutional ap- paratus that can be pressured by the UMWA to create and enforce safer operating procedures. Federal legislation strengthened the watchdog role of the UMWA, giving it a stronger voice in identifying and correcting violations as they arise in the workplace. In short, regulatory legislation and federal enforcement efforts should be viewed as both products of the continuing struggle between coal miners and mine operators and as con- tributing factors to the altering stock of resources and strategies available to both parties.

While exclusive focus on the regulatory determinants of health and safety improvements is, then, misleading, further analysis is required to pass judgment on how safety legislation affects the interplay among other key variables. How might such laws restructure the terrain of conflict between workers and employers over health and safety issues? By crown- ing worker demands with an aura of legitimacy, by providing the public mandate and organizational infrastructure to conduct inspections and levy fines, and by availing unions institutional access to the enforcement process, legislation empowers workers with symbolic and material resources for improving their work environment. For instance, one unintended consequence of safety legislation, it appears, has been to legitimate more aggressive strategies by miners to improve conditions. This is demonstrated by increases in strike frequency rates in the four legislative periods: .14 in 1930-41, 1.10 in 1942-52, 1.14 in 1953-69, and 3.77 in 1970-82. The estimation of models using interaction terms might further illuminate the means by which legislative enactments alter the effects of this and other variables (see also note 14).

Even though some have cited the half-century regulatory experience in coal mining as an indicator of the potential effectiveness of broader regulatory efforts, it is probably ill-advised to extrapolate safety regulation efforts in coal mining to the experience of other workers under the Occu- pational Safety and Health Act of 1970. Empirical studies of the OSH Act remain incondusive with regard to its effectiveness in curbing injuries in other industries (e.g., compare Smith 1976 and Viscusi 1979 to Cooke & Gautschi 1981). Still, the conclusions presented here imply that future studies of regulatory effectiveness should encompass a broader set of organizational and contextual variables than have previously been included.




Specifically, since resources of both employers and workers are critical for understanding the interplay of forces structuring the safety of work envi- ronments, they should be explicitly considered in future studies.

Notes

1. At this writing, 20 months after the Wilberg explosion, the fire continues to smolder. As a result, federal investigators have been unable to pinpoint the precise cause of the explosion. 2. Perrow (1984) suggests there is some merit to the operators' claims. There is no doubt an irreducible element of risk in mining that stems from uncertainty of the environment and the complexity of tasks. However, Perrow also notes that what passes for "operator errors" may actually be "forced errors" brought about by production schedule demands, extended shifts, conflicting job pressures, and careless management. He cites several examples from mine accident reports in which the designation "operator error" was, at least, questionable, and, arguably, a ruse for management irresponsibility. He concludes: "'Operator error' is an easy classification to make. What really is at stake is an inherently dangerous working situation where production must be kept moving and risk taking is the price of continued employment" (p. 249). 3. Since the scales for fatal and nonfatal injuries are so different, the graphs in Figure 1 are standardized by the average annual rate of decline of fatal injury rates. In other words, the two series are scaled so that one cah compare directly the rate of decline in fatal and nonfatal injuries. Had the rate of reduction in nonfatal injuries exceeded the rate of reduction in fatal injuries (which it did not), the nonfatal series would have fallen below the fatal series by the end of the period. 4. In comparative perspective, however, U.S. fatality rates in coal mining are far above those of most advanced industrial countries who mine coal (Braithwaite 1985; Caudill 1977). Shortly after the passage of the Federal Coal Mine Health and Safety Act in 1969, U.S. mines reached a level of safety that was achieved in British coal mines over 50 years before (see Hair's 1968, p. 545, analysis of British fatality figures). Recent American fatality rates are four times Holland's enviable rate of .15 deaths per 1,000 workers. 5. Late nineteenth-century accounts of mine operations indicate that when the installation of ventilation systems was left to the mine operators, the key factor in their decision was the value of the capital equipment, not human lives, that would be lost in a large explosion. Hence, ventilation systems were typically installed voluntarily in large, gassy mines and not in smaller, nongassy mines. Ironically, it was in the latter mines that miners were most exposed to a sudden death from explosion or to the dreaded black lung disease which "killed the men by inches" (Sheafer 1879, p. 244). 6. Qualitative research on work organization in underground mines has demonstrated that miners establish an informal, but well-defined, hierarchy of mine dangers which stems from "interaction within the miners' own ranks and (is) relatively independent of formal action taken by or through the mining company, miners' union, or mine regulatory agencies" (Fitzpatrick 1980, p. 138). This shared cognitive scheme is essentially an indigenously created survival technique which facilitates maximum output under conditions of duress. The team- work and solidarity displayed by miners, then, may be functional up to a point for maintain- ing high levels of productivity under dangerous and stressful conditions. But beyond that point, it may engender a callous disregard for externally created safety regulations that im- pede realization of day-to-day production quotas (see Caudill 1977). 7. Two operators in the Wilberg mine reported several occasions when such practices were encouraged. One miner reported, "We were under strict orders never to shut our belts off, no matter what the reason. Even if we had a roller bearing burning up, they'd tell us to cool it down with a water hose and change it out between shifts." Another miner added, "They would even bypass safety devices on our equipment if it kept them in the coal. I've seen them jumper out methane monitors on the transformer, and even remote switches on the belt. One time I really complained that they jumpered out the start alarm for the pan on our




longwall and the superintendent told me, 'We're responsible for this mine, and when we tell you to do something, you'll do it or you'll be looking for another job"' (United Mine Workers Journal 1985b, p. 8).

Perrow's insightful analysis of mine accident reports corroborates this anecdotal evidence: "looking at the accident reports, one is struck by the frequency with which reports are littered with failed clutches, broken drills, broken warning devices, electrical or power fail- ures, and so on. It seems that machinery is simply prone to failure, or, more likely, is poorly maintained and forced to its limits in this environment" (1984, p. 246). 8. Some have disputed the impact of such disasters on the passage of safety legislation noting correctly that numerous other large accidents have occurred without ensuing legislative action (Curran 1984). But this argument must be qualified by an understanding of the specific historical conditions in which this conflict has evolved. Most of the 65 major mining disasters since 1867 (complete list available from author) occurred prior to the New Deal era (and prior to the starting point of this analysis), when labor's influence in the political arena was relatively weak and the weight of public opinion paled in comparison with the power of the mine operators. Since the New Deal (excepting the World War II years), virtually every major disaster has been followed closely by the passage of new safety legislation. Thus, the role of these events in galvanizing public indignation against hazardous mining conditions since the beginning of the New Deal is difficult to ignore. 9. This analysis combines injury rates for both underground and surface mines, a practice used by some, but not all researchers in this area. The shifting composition of coal production (from underground to surface) is controlled by including a measure of the percentage of coal mined underground in the regression analyses. The ratio of injuries per million personhours worked is the most common measure used by researchers in this field (e.g., Lewis- Beck & Alford 1980; Perry 1982). 10. Arguably, one could better operationalize the average mine size variable by including only production workers in the numerator since they are most likely to be endangered. However, nonproduction personnel are frequently involved in day-to-day mine operations and are thus exposed to considerable danger. In fact, between 1978 and 1982, 96 out of 658 (14.6%) coal mining fatalities involved supervisors and foremen (K. Snyder 1984). Also, among the 27 persons killed in the Wilberg accident, 8 were management personnel (United Mine Workers Journal 1986). Hence, the more inclusive measure using "number of employees" as the numerator is most appropriate. 11. Several readers of an earlier version of this paper suggested substituting a measure of union density (percent of industry labor force unionized) for the UMWA variable. Construct- ing such a measure at the industry level is easier said than done in quantitative, historical analyses. First, no reliable union density measure for this (or any) industry is available as far back as 1930. One cannot simply divide the UMWA membership by total employees in coal mining to derive this measure because many UMWA members work in mining industries other than coal. In fact, for some years in the analysis, the number of UMWA members exceeds the number of employees in coal mining. Second, the UMWA is a more desirable measure than union density in this case because it represents organizational resources of coal miners. Even though members and dues are drawn from outside the coal mining sector, UMWA membership serves as an adequate proxy for resources that can be funnelled as needed to combat unsafe conditions in coal. 12. Simultaneity problems could arise if the strike variable is specified contemporaneously because, arguably, an increase in strike activity in a given year might reduce the injury rate in the same year because striking miners are not exposed to injury. Actually, the operationalization of the dependent variable (injuries per million personhours worked) virtually precludes this possibility, but lagging the strike frequency variable one year eliminates it altogether. 13. Serial correlation in multiple time series regression analysis can reduce artificially the standard errors of the estimates and lead to inflated and biased t-statistics; thus, a tendency to identify falsely regression coefficients as significant (Ostrom 1978). 14. Examination of zero-order correlations between mine size and injury rates by legislative




period supports this conjecture. The correlations between fatal injury rates and mine size are .70 in 1930-41, .83 in 1942-52, -.27 in 1953-69, and -.93 in 1970-82. The correlations between nonfatal injury rates and mine size are .92 in 1930-41, .80 in 1942-52, .60 in 1953- 69, and -.18 in 1970-82. Thus, in both cases, but especially for fatal injury rates, there is evidence that successive legislative enactments have transformed the average mine size effect on injury rates. This pattern is masked by the indusion of only main effects in the models. 15. TWo other diagnostic exercises were conducted in an attempt to uncover potentially "influential cases" in the analysis. First, a series of partial regression plots-one for each exoge- nous variable in the model with the exception of the law dummies-was performed for both the fatal and nonfatal injury models. This procedure permits the researcher to detect outliers which are not readily apparent from the original scattergram or from the standard plot of residuals (see Belsley, Kuh & Welsch 1980, or Bollen & Jackman 1985, for a fuller treatment). Second, the final regression model for both fatal and nonfatal injuries was rerun 53 times, each time dropping a different case from the analysis. Parameter estimates from each of these models were scanned to detect significant departures from the estimates in the final models. To summarize, neither of these exercises turned up serious evidence of additional outliers or influential cases, underscoring the robustness of the models presented in Table 2. 16. The mechanization of cutting processes in underground mining, in particular, has probably had mixed effects on injury rates. While freeing human labor from some of the more hazardous operations, mechanization has introduced previously unknown hazards. For instance, the noise and vibration of many heavy machines can create deafness and internal injuries to the operators and can also make it difficult "to hear the life-saving signal that the roof was 'working' and a slate fall was imminent" (Dix 1979, p. 166). Automated cutting process also accelerates the output of fine coal dust and methane gas (which is liberated from the coal seam during cutting) which can lead to explosions. Recent innovations in cutting processes include cutting under a fine spray of water to hold down the coal dust and methane sensors which shut down the machines when concentrations of gas reach dangerous levels (Marovelli & Karhnak 1983). Still, sensors have been known to fail or be shut down by operators intent on speeding up production (see note 7). 17. Though perhaps a serviceable quantitative indicator of technological change, none of these measures capture the types of qualitative changes taking place in underground and surface mining. In underground mining, for instance, the changing composition among different automated techniques (conventional, continuous, and longwall) is impossible to determine.

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Dying for Coal: The Struggle for Health and Safety Conditions in American Coal Mining, 1930-82

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