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Where o’ where did my baseball cards go?
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The Social Science Journal 44 (2007) 742–750
Where o’ where did my baseball cards go? Race, performance, and placement in the Topps ERA, 1956–1980 Robert M. Regoli a,∗ , Eric Primm b , John D. Hewitt c a
b
Department of Sociology, University of Colorado, Boulder, CO 80309, USA Division of Social Sciences, Pikeville College, 147 Sycamore Street, Pikeville, KY 41501, USA c School of Criminal Justice, Grand Valley State University, Grand Rapids, MI 49546, USA
Abstract On the surface, baseball cards appear to be little more than uninteresting object of child’s play; yet they provide invaluable data for assessing unique aspects of the social order. They reveal much about the state of society when they were produced and the people who collected them. This paper examines the unique numbering system the Topps company developed to differentiate among the “royalty of the diamond” from 1956 to 1980. Their system assigned to each card in a set a number that explicitly designated its placement, while implicitly establishing a hierarchical ordering among the players, ostensibly based on performance. It is arguable whether the numbering system Topps developed was based on performance or the ascribed characteristic of race. The results of our work suggest that player performance, not race, was the primary factor in the assignment of “prestigious” card numbers in Topps’ system. © 2007 Elsevier Inc. All rights reserved.
1. Introduction Baseball card collecting had a rather modest beginning. During the late 19th century tobacco tycoon James Buchanan “Buck” Duke (who founded Duke University) began inserting small pieces of cardboard into the backs of cigarette packages to stiffen them to prevent damage during shipping. Each cardboard piece had advertising on one side and the picture of a popular actor on the reverse. Two of Duke’s competitors, Allen & Ginter and Goodwin & Company, responded by putting pictures of baseball players on “cards” they inserted into their cigarette packages (Williams, 1995). ∗
Corresponding author. Tel.: +1 303 492 7088. E-mail address: [email protected] (R.M. Regoli).
0362-3319/$ – see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.soscij.2007.10.009
R.M. Regoli et al. / The Social Science Journal 44 (2007) 742–750
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The production of baseball cards, and thus the public’s interest in them, declined in the early 1900s and sports cards may have faded unceremoniously into history if not for competing chewing gum companies. The Topps Chewing Gum Company emerged as the winner of this battle in 1956 when they bought their chief competitor: the Bowman Gum Company of Philadelphia. Topps’ most popular product, “Bazooka” bubble gum, was packaged with two baseball cards and sold for a penny (Williams, 1995). For the next 25 years (1956–1980) Topps was in complete control of the baseball card industry; however, their monopoly ended in 1981 as a result of losing an antitrust suit filed by the Fleer Corporation (Williams, 1995). The focus of this study is on the period 1956–1980, known in the hobby as the “Topps Era.”
2. The research question Critical race theorists contend that racism permeates every nook and cranny of American society. One spokesperson for this perspective is Feagin (2000), who has charged that racism in the United States is structured into the very rhythms of everyday life. He believes racism pervades all social institutions and impacts all social interactions. If Feagin and his supporters are correct (e.g., Bonilla-Silva, 2003; Hunter, 2005), racism should also be pervasive in the seemingly benign hobby of baseball card collecting. Several studies have examined the role of race in sport card collecting and the findings from them are mixed. Nearly all of the studies have explored the influence of race on the value of players’ cards. Some research has found a bias in the card values of black baseball players (Andersen & LaCroix, 1991; Fort & Gill, 2000; Gabriel, Johnson, & Stanton, 1999; Nardinelli & Simon, 1990; Regoli, 2000). Other research appears to find minimal or no racial bias, or report mixed results (Hewitt, Mu˜noz, Oliver, & Regoli, 2005; Messitte & Powell, 1995; Primm, Regoli, & Hewitt, 2006; Regoli, 1991). Some of these discrepancies can be accounted for by varying samples and methodologies. Gabriel et al. (1999) examined rookie cards of baseball players produced by Topps between 1974 and 1982, Nardinelli and Simon (1990) investigated all cards of baseball players produced by Topps in 1970, and Hewitt et al. (2005) examined a sub-sample of rookie cards of members of the baseball Hall of Fame (HOF). In addition, there are differences in terms of the independent variables included in the studies. Some researchers used measures of performance while others did not. Moreover, identifying the race of a player is no easy task. No player’s card specifically identifies his race. To solve the problem, some researchers, such as Fort and Gill (2000, p. 25), developed a continuous, market participant measure of race reflecting “an average race/ethnicity score (between 0 and 1) for each player.” Other researchers used a more traditional approach of measuring race as discrete variables using photo identification from player cards (Brown & Bear, 1999; Hewitt et al., 2005; Primm et al., 2006; Regoli, 1991; Regoli, Hewitt, Mu˜noz, & Regoli, 2004). Despite their varied methodologies, generally all studies have used card value as their dependent variable. In this paper we extend these works and add to the recent research of Regoli et al. (2004). A key difference in this work as compared to other research on racial bias in card collecting is their use of card location, not card value, as the dependent variable.
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2.1. The Topps numbering system In the 1950s Topps developed a rather clever numbering system for assigning placement of players in baseball card sets. Only recently has the system been revealed to academics, who are typically “outsiders” to card collecting hobbyists (Becker, 1963; Regoli et al., 2004). On the back of every baseball card is a number with different numbers having varying “prestige” levels. In theory, the “best” players receive the most prestigious card numbers or placement in the card set. In other words, the numbering system aided collectors in identifying the top players in the game or those players who were the “royalty of the diamond in any given year” (O’Connell, 1993, p. 160). This system, however, did take a few years to fully develop. For example, in 1954, one of the “prestigious” numbers was assigned to Bob Keegan because he was a college friend of Topps executive, Sy Berger; but by 1956 the numbering system was well established as a “merit” based system (O’Connell, 1993, p. 160). Interestingly, the status of numbers did not follow a simple linear progression beginning with “1” and ending with “500” or whatever the largest number happened to be for that set. Instead, the Topps Numbering System (TNS) was more subtle and involved the development of a pattern that used particular sets of numbers in descending order of prestige: 1. 2. 3. 4. 5. 6.
Card #1 was reserved for the player with the top status in the game. Card #500. All even 100 numbers (e.g., 100, 200, 300, etc.). Card #50. All numbers ending with 50 (e.g., 150, 250, 350, etc.). All numbers that ended in zero, with preference placed within the first nine such units, leading up to #100. 7. Numbers that ended with 5, with substantial preference given to numbers that are multiples of 25 (O’Connell, 1993, p. 160). Placement for all other players in a card set was a random process. In the first study of its kind, Regoli et al. (2004) compared players’ on-the-field performance, measured with a statistic called Total Baseball Ranking (TBR), to their cards’ location the following year for 25 years of Topps baseball cards (1956–1980) (Thorn, Palmer, & Gershman, 2001). Theoretically, in a world free of bias, the most prestigious card location numbers would be assigned to the best performers from the previous season. The researchers identified the top ten black and white performers from the preceding season based on their TBR, calculated the percentage of TBR points earned by blacks and whites, and compared that to points earned by blacks and whites for the top 10 placements in each year’s card set. They found a strong bias against black players from 1956 to 1965: black players systematically received less prestigious card numbers than their on-field performance from the prior season would have dictated. Interestingly, they also found this arrangement reversed from 1966 to 1980 (with the exception of the 1970 and 1977 sets). For these years, black players compared to white players received more prominent card numbers than their performance the previous year would predict. The goal of the present research is to reexamine the work of Regoli et al. (2004), while addressing specific shortcomings in their research. A serious flaw of the Regoli et al. (2004) study is of a statistical nature. The researchers only reported the difference between the
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percentage of TBR points earned and percentage of location points earned. There was no reporting as to the significance or importance of these differences. While a double-digit percentage disparity sounds like a sizable margin; how “big” is “big?” Another point of concern is that Regoli et al. (2004) limited their study to the top ten performers and the top ten card locations for each year studied. This relatively small number of data points for each year increases the potential for error entering the research (Levin & Fox, 2005). Perhaps a more important issue is that Regoli et al. made the assumption that a player’s performance from 1 year could be separated from other factors, aside from racial bias, that may contribute to card placement. One obvious factor is the reputation a player builds over the course of his career. For example, some star players had “off” seasons, but in the subsequent years had high card placements (e.g., Mickey Mantle in 1964). Another issue, unrelated to performance, that could account for disproportionately high or low card placement could be the team the player was on. “Big market” teams, such as the New York Yankees or Los Angeles Dodgers, may confer star-level status, and favorable card numbers, to players whose statistics would suggest otherwise (Pee Wee Reese in 1955 and Whitey Ford in 1957). Conversely, players who were on “Small market” teams often failed to receive their “just deserts”: Detroit’s Al Kaline and Twins’ slugger Harmon Killebrew were often overlooked by Topps. Similarly, the on-the-field accomplishments of baseball’s long-time home run king—Hammerin’ Hank Aaron of the Milwaukee Braves—regularly went unnoticed by Topps in their card sets. Furthermore, a player could be a “fan favorite” for reasons not entirely related to their performance, and receive consistently high card placements (e.g., Reggie Jackson and Pete Rose). In essence, by examining performance and card location on a year-to-year basis, the research of Regoli et al. (2004), becomes susceptible to volatile variations in individual performances in any given year, as well as other “intangible” factors such as those described above. Due to these limitations, the validity of the findings reported by Regoli et al. (2004) is suspect. The present study addresses the problems of their research in several ways. First, we perform a regression analysis on the data as opposed to simply reporting the percentage of difference between performance and location points. Our technique allows us to make more meaningful comparisons and interpretations regarding the results. Second, and most importantly, we examine the performance and location statistics of players spanning their entire careers, rather than on a year-to-year basis. This attends to two of the previously discussed weaknesses in Regoli et al.’s (2004) work. By studying career statistics we avoid the problem of having a relatively small number of data points for each year. In addition, this strategy helps to moderate the effects of the “intangible” factors that can influence card placement in any given year, such as: a player’s reputation, his popularity among fans, and market size of his team. Restated, a player might not receive his “fair dues” by being assigned a prestigious card number following an outstanding season on the field, however, consistently high performance is more likely to be recognized and rewarded (with favorable card locations) over the course of his career. 2.2. The data Data were derived from three secondary sources: (1) Berger and Slocum (1985), The Complete Picture Collection of Topps Baseball Cards, 1951–1985, (2) James and Henzler
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(2002) Win Shares, and (3) Thorn et al.’s Total Baseball (2004). The data on a player’s placement in a card set (location) and his race were taken from Berger and Slocum’s book, which shows a photo of every card produced by Topps, with its number and year, for 35 years. The measure of on-the-field performance (performance) was taken from James and Henzler (2002), who constructed a statistic called Win Shares (WS), a composite measure that makes it possible to compare the yearly and career on-the-field performances of players. 2.3. The sample Our sample consisted of all black and white players who received one or more votes for induction into the National Baseball Hall of Fame (HOF) between 1956 and 1980.1 These twoand-one-half decades define the parameters of our sampling time frame because it covers what is known as the Topps Era. This is the period when Topps had a monopoly on the production of baseball cards, and therefore, a monopoly on all information transmitted to collectors of those cards. This information included which cards were to be most coveted, and by extension, which players were truly the diamond’s elite. To have comparable samples of black and white HOF-eligible players, every player in the study had to have played in the integrated major baseball league that started in 1947 with Jackie Robinson. Furthermore, a player had to have been eligible for inclusion to the HOF and to have received at least one vote for induction prior to the end of the Topps Era in 1980.2 2.4. The variables Three variables were examined in the analysis: 1. Card point ratio: The dependent variable was constructed based upon the player’s location or placement in the card set. Rather than simply totaling a player’s card points, we standardized this measure to account for the number of appearances in Topps card sets. Therefore, after totaling the points for all players’ cards according to the TNS (i.e., card #1 = 9 points, #500 = 8, etc.) we divided that number by the total number of card sets in which the players appeared. The resultant ratio-level variable ranged in values from 0 to 5.13 and had a mean of 1.45. 2. Race: A visual inspection of each player’s photograph as it appears in The Complete Picture Collection of Topps Baseball Cards, 1951–1985 (Berger & Slocum, 1985) was used to determine each player’s race. With the assistance of colleagues, friends, family members, and acquaintances, the authors used visual cues such as skin tone and facial features to assign players to each category. In the few situations where the authors still were not certain of the race of a player, they consulted with experienced collectors at local, regional, and national collectors’ conventions. The players were subsequently divided into black (n = 30) and white (n = 108) subcategories.3 3. Performance:Win Shares (WS) measure the number of wins a player contributes to his team. This measure was created with the intention of making meaningful comparisons between individual players across positions, eras, teams, and even the “home park” in
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Table 1 Effects of race and performance on card location
Constant Racea Win Shares
Unstandardized coefficients
S.E.
t value
Significance t
.091 .084 .003
.061 .070 .000
1.493 1.195 12.178
.138 .234 .000
R2 = .550. Adjusted R2 = .544. a Whites are reference group.
which a player played. Essentially, Win Shares are wins created by individual players. Once a team’s Win Shares are calculated (three times the number of wins the team had in any given year) there is a six-stage process to assign Win Shares to individual players. (For a more detailed discussion of the win shares measure see James & Henzler, 2002).
3. Analysis The variable card point ratio was log-transformed (natural logarithm) in our analysis because of its skewed distribution. A value of 1 was added before transformation to avoid values of 0. The dependent variable, logged point ratio was regressed on race, and WS. The regression coefficients for this model are presented in Table 1. The multiple R2 for the analysis is .55. As expected, the measure of performance, WS, had a significant positive effect on card location points (t = 12.178; p < .001). As a player’s WS increased their logged point ratio also increased. The coefficient for race was not significant (t = 1.195; p = .234). It should be noted, however, the direction of race on logged point ratio was somewhat unexpected. The analysis suggests black players may have received an advantage over white players when on-the-field performance was taken into account over the duration of their careers. Nevertheless, as stated previously the coefficients for this variable were not significant. Several other models were tested including those using variations of the dependent variable. Although the parameter estimates changed across the models, these changes did not affect our substantive conclusions: the relative explanatory power and direction of each covariate remained unchanged.
4. Discussion Our findings of no racial preferences in the Topps Numbering System (TNS) are not inconsistent with those of Regoli et al. (2004). As they reported, white players received preferential placement in Topps’ card sets from 1956 to 1965, then from 1966 to 1980 (excepting 1970 and 1977) blacks were assigned the more prestigious card locations than their performance would have indicated. Regoli et al. (2004) speculated this dramatic reversal was a result of the increased awareness of racism in its many forms and the mounting societal desire to end such
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practices. The Civil Rights Movement brought sweeping changes to many facets of American culture; it is not unreasonable to conclude this wave of change was also felt and acted upon by the Topps baseball card empire. We have a long standing interest in the nature of the hobby of baseball card collecting, particularly its social hierarchies and mechanisms of social control. The origins of this curiosity can be traced to early observations of one of the authors who started collecting baseball cards in the mid-1950s. He and his peers had become very aware of their being “something” significant about the numbers on the backs of Topps’ cards. They identified a strong association between the status of certain players and the numbers they received in the card deck. The awareness of this difference led him and his friends to first look at the card numbers when opening a new pack of cards and then to look at the players who were pictured on them. For years not much was made of this practice; the frivolous pursuits of children. Then, we read Feagin’s Racist America (2000), where he contends that America is a total racist society. For some, Feagin’s assertion raised eyebrows; for us it raised some intriguing questions: Was something more significant than the “objective” ranking of our sports heroes going on with the TNS? Was the TNS one more piece in the much larger societal picture engaged in the transmission of a racist ideology? We approached these questions with a bit of skepticism because of a growing body of literature indicating a decline in racism (e.g., Butler, 1991; Farley, 1984; Farley & Allen, 1987; Moskos & Butler, 1996; Wilson, 1981). We decided to put Feagin’s idea of America being a total racist society to a test in one of the more inconsequential areas of American culture: baseball card collecting. We believed that if racism had permeated baseball card collecting, then, it probably also was true that racism had infected much of the “heart and soul” of American society as Feagin suggested. This possibility was tested by examining decisions Topps made regarding where to locate players in card sets it issued when Topps had an iron grip on the sport card industry. Of particular interest to us was whether during the “Topps Era,” the decisions made about where to locate players in sets were based primarily on achievement (WS) or ascription (race). Our results suggest that during the Topps Era, taken as a whole, decisions about player location were based upon on-the-field performance and were not racially motivated. These findings, however, do not necessarily contradict Feagin’s (2000) assertion regarding the pervasiveness of racism in American society. There is little doubt that racism is extensive. But does it permeate all spheres of social structure and process? Our findings suggest it does not. There are clearly arenas in which notions of ability, competence, and performance, rather than race, defines the value placed on outcomes—in this case, the status location of the cards of baseball players. Other research supports the idea that sensitivity to race is present in the hobby of baseball card collecting (e.g., Bloom, 1997; Regoli, 2000). Our results of no racial preference in the TNS might be a byproduct of the two opposing eras of preference, reported by Regoli et al. (2004), simply “canceling one another out.” This prospect suggests a topic for future study for other researchers. Although the present work addresses several of the shortcomings of Regoli et al. (2004), like Regoli et al. it fails to examine the trends that have occurred. This work, in part, was intended to mitigate some of the volatility that could occur from year to year in placing players in the Topps card sets, but in doing so; we lose sight of the “little picture,” the shifts in practices that may have occurred over time in player placement in the Topps sets.
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Notes 1. Latinos were excluded from this sample because too few (five players) met the criteria for inclusion for any meaningful statistical analysis to be performed. 2. The sample was limited to players who received votes for HOF induction since in a world free of bias; these are the very same players who would receive the vast majority of the favorable card positions in the TNS. The elite card positions are (theoretically) reserved for the elite players and this is precisely the relationship being tested. While some research has indicated racial bias in election to the HOF (for example Desser, Monks, & Robinson, 1999; Findlay & Reid, 1997), our sample includes not only those elected to the HOF but also those simply receiving votes and this inclusion should aid in mitigating bias if it indeed exists. 3. Players’ race was generally determined in a manner similar to that used by Brown and Bear (1999) in their analysis of disparities in field position of minorities in major league baseball between 1952 and 1987. Players were initially classified as black or white based on facial features on their cards. If a player’s facial features suggested he was black, but he had a Latino surname, The Baseball Encyclopedia (Prebenna, 1990) was used to determine whether the player was born in a Latin American country. Black players with Latino surnames born in the United States were classified as black, while those born in Latin American countries were counted as Latino. This photo identification method was chosen because this is the method collectors use to determine a player’s race. We have (collectively) studied sport card collecting for more than 20 years; attended over 100 local, regional, and national conventions; presented research at the National Sports Collectors Convention; and discussed the topic of race and sport cards with countless collectors. Invariably, when we ask a collector how they determine a player’s race they respond: “By looking at the picture on the card.”
Acknowledgments The Council on Research and Creative Work at the University of Colorado provided partial funding for the study. We thank our colleague, Jason Boardman, for his assistance, guidance, and patience. We also appreciate the support of our colleagues, particularly Michael Radelet whose comments helped us to improve the paper. References Andersen, T., & LaCroix, S. J. (1991). Customer racial discrimination in Major League Baseball. Economic Inquiry, 29, 665–677. Becker, H. (1963). Outsiders: Studies in the sociology of deviance. New York: Free Press. Berger, S., & Slocum, F. (1985). The complete picture collection of Topps baseball cards, 1951–1985. New York: Warner Books. Bloom, J. (1997). House of cards. Minneapolis: University of Minnesota Press. Bonilla-Silva, E. (2003). Racism without racists: Color-blind racism and the persistence of racial inequality in the United States. Oxford: Rowman and Littlefield Publishers.
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Brown, J., & Bear, G. (1999). Minorities in Major League Baseball 1952–1987. International Review for the Sociology of Sport, 34, 411–422. Butler, J. S. (1991). Entrepreneurship and self-help among black Americans. Albany, New York: State University of New York. Desser, A., Monks, J., & Robinson, M. (1999). Baseball Hall of Fame voting: A test of the customer discrimination hypothesis. Social Science Quarterly, 80, 591–603. Farley, R. (1984). Blacks and whites. Cambridge: Harvard University Press. Farley, R., & Allen, W. (1987). The color line and the quality of life in America. New York: Russell Sage Foundation. Feagin, J. (2000). Racist America: Roots, current realities, and future reparations. New York: Routledge. Findlay, D. W., & Reid, C. E. (1997). Voting behavior, discrimination and the National Baseball Hall of Fame. Economic Inquiry, 35, 562–578. Fort, R., & Gill, A. (2000). Race and ethnicity assessment in baseball card markets. Journal of Sports Economics, 1, 21–38. Gabriel, P. E., Johnson, C. D., & Stanton, T. J. (1999). Customer racial discrimination for baseball memorabilia. Applied Economics, 31, 1331–1335. Hewitt, J. D., Mu˜noz, R., Jr., Oliver, W. L., & Regoli, R. M. (2005). Race, performance, and baseball card values. Journal of Sport & Social Issues, 29, 411–429. Hunter, M. (2005). Race, gender, and the politics of skin tone. Routledge: New York. James, B., & Henzler, J. (2002). Win shares. Morton Grove, IL: STATS, Inc. Levin, J., & Fox, J. A. (2005). Elementary statistics in social research (10th ed.). Boston: Allyn and Bacon. Messitte, J., & Powell, I. (1995). Customer race discrimination in the market for baseball cards. Paper Presented at Department of Economics, Grinnell College. Moskos, C., & Butler, J. S. (1996). All that we can be. New York: Basic Books. Nardinelli, C., & Simon, C. (1990). Customer racial discrimination in the market for memorabilia: The case of baseball. Quarterly Journal of Economics, 105, 575–595. O’Connell, T. S. (1993). Topps numbering system, a subtle record of player status. Sports Collectors Digest, 160. Prebenna, D. (1990). The baseball encyclopedia. New York: Macmillan. Primm, E., Regoli, R. M., & Hewitt, J. D. (2006). Does membership have its rewards? The effects of race and hall of fame membership on football card values. Sociological Spectrum, 26, 369–385. Regoli, R. M. (1991). Racism in baseball card collecting: Fact or fiction? Human Relations, 44, 255–264. Regoli, R. M. (2000). Racism, racism everywhere: Looking inside the hobby of baseball card collecting. Race & Society, 3, 183–192. Regoli, R. M., Hewitt, J. D., Mu˜noz, R., Jr., & Regoli, A. M. (2004). Location, location, location: The transmission of racist ideology in baseball cards. The Negro Educational Review, 55, 75–90. Thorn, J., Birnbaum, P., & Deane, B. (2004). Total baseball (8th ed.). Toronto: SPORTClassic Books. Thorn, J., Palmer, P., & Gershman, M. (2001). Total baseball (7th ed.). Kingston, NY: Total Sports Publishing. Wilson, W. J. (1981). The declining significance of race. Chicago: University of Chicago Press. Williams, P. (1995). Card sharks. New York: Macmillan.
The Social Science Journal 44 (2007) 742–750
Where o’ where did my baseball cards go? Race, performance, and placement in the Topps ERA, 1956–1980 Robert M. Regoli a,∗ , Eric Primm b , John D. Hewitt c a
b
Department of Sociology, University of Colorado, Boulder, CO 80309, USA Division of Social Sciences, Pikeville College, 147 Sycamore Street, Pikeville, KY 41501, USA c School of Criminal Justice, Grand Valley State University, Grand Rapids, MI 49546, USA
Abstract On the surface, baseball cards appear to be little more than uninteresting object of child’s play; yet they provide invaluable data for assessing unique aspects of the social order. They reveal much about the state of society when they were produced and the people who collected them. This paper examines the unique numbering system the Topps company developed to differentiate among the “royalty of the diamond” from 1956 to 1980. Their system assigned to each card in a set a number that explicitly designated its placement, while implicitly establishing a hierarchical ordering among the players, ostensibly based on performance. It is arguable whether the numbering system Topps developed was based on performance or the ascribed characteristic of race. The results of our work suggest that player performance, not race, was the primary factor in the assignment of “prestigious” card numbers in Topps’ system. © 2007 Elsevier Inc. All rights reserved.
1. Introduction Baseball card collecting had a rather modest beginning. During the late 19th century tobacco tycoon James Buchanan “Buck” Duke (who founded Duke University) began inserting small pieces of cardboard into the backs of cigarette packages to stiffen them to prevent damage during shipping. Each cardboard piece had advertising on one side and the picture of a popular actor on the reverse. Two of Duke’s competitors, Allen & Ginter and Goodwin & Company, responded by putting pictures of baseball players on “cards” they inserted into their cigarette packages (Williams, 1995). ∗
Corresponding author. Tel.: +1 303 492 7088. E-mail address: [email protected] (R.M. Regoli).
0362-3319/$ – see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.soscij.2007.10.009
R.M. Regoli et al. / The Social Science Journal 44 (2007) 742–750
743
The production of baseball cards, and thus the public’s interest in them, declined in the early 1900s and sports cards may have faded unceremoniously into history if not for competing chewing gum companies. The Topps Chewing Gum Company emerged as the winner of this battle in 1956 when they bought their chief competitor: the Bowman Gum Company of Philadelphia. Topps’ most popular product, “Bazooka” bubble gum, was packaged with two baseball cards and sold for a penny (Williams, 1995). For the next 25 years (1956–1980) Topps was in complete control of the baseball card industry; however, their monopoly ended in 1981 as a result of losing an antitrust suit filed by the Fleer Corporation (Williams, 1995). The focus of this study is on the period 1956–1980, known in the hobby as the “Topps Era.”
2. The research question Critical race theorists contend that racism permeates every nook and cranny of American society. One spokesperson for this perspective is Feagin (2000), who has charged that racism in the United States is structured into the very rhythms of everyday life. He believes racism pervades all social institutions and impacts all social interactions. If Feagin and his supporters are correct (e.g., Bonilla-Silva, 2003; Hunter, 2005), racism should also be pervasive in the seemingly benign hobby of baseball card collecting. Several studies have examined the role of race in sport card collecting and the findings from them are mixed. Nearly all of the studies have explored the influence of race on the value of players’ cards. Some research has found a bias in the card values of black baseball players (Andersen & LaCroix, 1991; Fort & Gill, 2000; Gabriel, Johnson, & Stanton, 1999; Nardinelli & Simon, 1990; Regoli, 2000). Other research appears to find minimal or no racial bias, or report mixed results (Hewitt, Mu˜noz, Oliver, & Regoli, 2005; Messitte & Powell, 1995; Primm, Regoli, & Hewitt, 2006; Regoli, 1991). Some of these discrepancies can be accounted for by varying samples and methodologies. Gabriel et al. (1999) examined rookie cards of baseball players produced by Topps between 1974 and 1982, Nardinelli and Simon (1990) investigated all cards of baseball players produced by Topps in 1970, and Hewitt et al. (2005) examined a sub-sample of rookie cards of members of the baseball Hall of Fame (HOF). In addition, there are differences in terms of the independent variables included in the studies. Some researchers used measures of performance while others did not. Moreover, identifying the race of a player is no easy task. No player’s card specifically identifies his race. To solve the problem, some researchers, such as Fort and Gill (2000, p. 25), developed a continuous, market participant measure of race reflecting “an average race/ethnicity score (between 0 and 1) for each player.” Other researchers used a more traditional approach of measuring race as discrete variables using photo identification from player cards (Brown & Bear, 1999; Hewitt et al., 2005; Primm et al., 2006; Regoli, 1991; Regoli, Hewitt, Mu˜noz, & Regoli, 2004). Despite their varied methodologies, generally all studies have used card value as their dependent variable. In this paper we extend these works and add to the recent research of Regoli et al. (2004). A key difference in this work as compared to other research on racial bias in card collecting is their use of card location, not card value, as the dependent variable.
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2.1. The Topps numbering system In the 1950s Topps developed a rather clever numbering system for assigning placement of players in baseball card sets. Only recently has the system been revealed to academics, who are typically “outsiders” to card collecting hobbyists (Becker, 1963; Regoli et al., 2004). On the back of every baseball card is a number with different numbers having varying “prestige” levels. In theory, the “best” players receive the most prestigious card numbers or placement in the card set. In other words, the numbering system aided collectors in identifying the top players in the game or those players who were the “royalty of the diamond in any given year” (O’Connell, 1993, p. 160). This system, however, did take a few years to fully develop. For example, in 1954, one of the “prestigious” numbers was assigned to Bob Keegan because he was a college friend of Topps executive, Sy Berger; but by 1956 the numbering system was well established as a “merit” based system (O’Connell, 1993, p. 160). Interestingly, the status of numbers did not follow a simple linear progression beginning with “1” and ending with “500” or whatever the largest number happened to be for that set. Instead, the Topps Numbering System (TNS) was more subtle and involved the development of a pattern that used particular sets of numbers in descending order of prestige: 1. 2. 3. 4. 5. 6.
Card #1 was reserved for the player with the top status in the game. Card #500. All even 100 numbers (e.g., 100, 200, 300, etc.). Card #50. All numbers ending with 50 (e.g., 150, 250, 350, etc.). All numbers that ended in zero, with preference placed within the first nine such units, leading up to #100. 7. Numbers that ended with 5, with substantial preference given to numbers that are multiples of 25 (O’Connell, 1993, p. 160). Placement for all other players in a card set was a random process. In the first study of its kind, Regoli et al. (2004) compared players’ on-the-field performance, measured with a statistic called Total Baseball Ranking (TBR), to their cards’ location the following year for 25 years of Topps baseball cards (1956–1980) (Thorn, Palmer, & Gershman, 2001). Theoretically, in a world free of bias, the most prestigious card location numbers would be assigned to the best performers from the previous season. The researchers identified the top ten black and white performers from the preceding season based on their TBR, calculated the percentage of TBR points earned by blacks and whites, and compared that to points earned by blacks and whites for the top 10 placements in each year’s card set. They found a strong bias against black players from 1956 to 1965: black players systematically received less prestigious card numbers than their on-field performance from the prior season would have dictated. Interestingly, they also found this arrangement reversed from 1966 to 1980 (with the exception of the 1970 and 1977 sets). For these years, black players compared to white players received more prominent card numbers than their performance the previous year would predict. The goal of the present research is to reexamine the work of Regoli et al. (2004), while addressing specific shortcomings in their research. A serious flaw of the Regoli et al. (2004) study is of a statistical nature. The researchers only reported the difference between the
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percentage of TBR points earned and percentage of location points earned. There was no reporting as to the significance or importance of these differences. While a double-digit percentage disparity sounds like a sizable margin; how “big” is “big?” Another point of concern is that Regoli et al. (2004) limited their study to the top ten performers and the top ten card locations for each year studied. This relatively small number of data points for each year increases the potential for error entering the research (Levin & Fox, 2005). Perhaps a more important issue is that Regoli et al. made the assumption that a player’s performance from 1 year could be separated from other factors, aside from racial bias, that may contribute to card placement. One obvious factor is the reputation a player builds over the course of his career. For example, some star players had “off” seasons, but in the subsequent years had high card placements (e.g., Mickey Mantle in 1964). Another issue, unrelated to performance, that could account for disproportionately high or low card placement could be the team the player was on. “Big market” teams, such as the New York Yankees or Los Angeles Dodgers, may confer star-level status, and favorable card numbers, to players whose statistics would suggest otherwise (Pee Wee Reese in 1955 and Whitey Ford in 1957). Conversely, players who were on “Small market” teams often failed to receive their “just deserts”: Detroit’s Al Kaline and Twins’ slugger Harmon Killebrew were often overlooked by Topps. Similarly, the on-the-field accomplishments of baseball’s long-time home run king—Hammerin’ Hank Aaron of the Milwaukee Braves—regularly went unnoticed by Topps in their card sets. Furthermore, a player could be a “fan favorite” for reasons not entirely related to their performance, and receive consistently high card placements (e.g., Reggie Jackson and Pete Rose). In essence, by examining performance and card location on a year-to-year basis, the research of Regoli et al. (2004), becomes susceptible to volatile variations in individual performances in any given year, as well as other “intangible” factors such as those described above. Due to these limitations, the validity of the findings reported by Regoli et al. (2004) is suspect. The present study addresses the problems of their research in several ways. First, we perform a regression analysis on the data as opposed to simply reporting the percentage of difference between performance and location points. Our technique allows us to make more meaningful comparisons and interpretations regarding the results. Second, and most importantly, we examine the performance and location statistics of players spanning their entire careers, rather than on a year-to-year basis. This attends to two of the previously discussed weaknesses in Regoli et al.’s (2004) work. By studying career statistics we avoid the problem of having a relatively small number of data points for each year. In addition, this strategy helps to moderate the effects of the “intangible” factors that can influence card placement in any given year, such as: a player’s reputation, his popularity among fans, and market size of his team. Restated, a player might not receive his “fair dues” by being assigned a prestigious card number following an outstanding season on the field, however, consistently high performance is more likely to be recognized and rewarded (with favorable card locations) over the course of his career. 2.2. The data Data were derived from three secondary sources: (1) Berger and Slocum (1985), The Complete Picture Collection of Topps Baseball Cards, 1951–1985, (2) James and Henzler
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(2002) Win Shares, and (3) Thorn et al.’s Total Baseball (2004). The data on a player’s placement in a card set (location) and his race were taken from Berger and Slocum’s book, which shows a photo of every card produced by Topps, with its number and year, for 35 years. The measure of on-the-field performance (performance) was taken from James and Henzler (2002), who constructed a statistic called Win Shares (WS), a composite measure that makes it possible to compare the yearly and career on-the-field performances of players. 2.3. The sample Our sample consisted of all black and white players who received one or more votes for induction into the National Baseball Hall of Fame (HOF) between 1956 and 1980.1 These twoand-one-half decades define the parameters of our sampling time frame because it covers what is known as the Topps Era. This is the period when Topps had a monopoly on the production of baseball cards, and therefore, a monopoly on all information transmitted to collectors of those cards. This information included which cards were to be most coveted, and by extension, which players were truly the diamond’s elite. To have comparable samples of black and white HOF-eligible players, every player in the study had to have played in the integrated major baseball league that started in 1947 with Jackie Robinson. Furthermore, a player had to have been eligible for inclusion to the HOF and to have received at least one vote for induction prior to the end of the Topps Era in 1980.2 2.4. The variables Three variables were examined in the analysis: 1. Card point ratio: The dependent variable was constructed based upon the player’s location or placement in the card set. Rather than simply totaling a player’s card points, we standardized this measure to account for the number of appearances in Topps card sets. Therefore, after totaling the points for all players’ cards according to the TNS (i.e., card #1 = 9 points, #500 = 8, etc.) we divided that number by the total number of card sets in which the players appeared. The resultant ratio-level variable ranged in values from 0 to 5.13 and had a mean of 1.45. 2. Race: A visual inspection of each player’s photograph as it appears in The Complete Picture Collection of Topps Baseball Cards, 1951–1985 (Berger & Slocum, 1985) was used to determine each player’s race. With the assistance of colleagues, friends, family members, and acquaintances, the authors used visual cues such as skin tone and facial features to assign players to each category. In the few situations where the authors still were not certain of the race of a player, they consulted with experienced collectors at local, regional, and national collectors’ conventions. The players were subsequently divided into black (n = 30) and white (n = 108) subcategories.3 3. Performance:Win Shares (WS) measure the number of wins a player contributes to his team. This measure was created with the intention of making meaningful comparisons between individual players across positions, eras, teams, and even the “home park” in
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Table 1 Effects of race and performance on card location
Constant Racea Win Shares
Unstandardized coefficients
S.E.
t value
Significance t
.091 .084 .003
.061 .070 .000
1.493 1.195 12.178
.138 .234 .000
R2 = .550. Adjusted R2 = .544. a Whites are reference group.
which a player played. Essentially, Win Shares are wins created by individual players. Once a team’s Win Shares are calculated (three times the number of wins the team had in any given year) there is a six-stage process to assign Win Shares to individual players. (For a more detailed discussion of the win shares measure see James & Henzler, 2002).
3. Analysis The variable card point ratio was log-transformed (natural logarithm) in our analysis because of its skewed distribution. A value of 1 was added before transformation to avoid values of 0. The dependent variable, logged point ratio was regressed on race, and WS. The regression coefficients for this model are presented in Table 1. The multiple R2 for the analysis is .55. As expected, the measure of performance, WS, had a significant positive effect on card location points (t = 12.178; p < .001). As a player’s WS increased their logged point ratio also increased. The coefficient for race was not significant (t = 1.195; p = .234). It should be noted, however, the direction of race on logged point ratio was somewhat unexpected. The analysis suggests black players may have received an advantage over white players when on-the-field performance was taken into account over the duration of their careers. Nevertheless, as stated previously the coefficients for this variable were not significant. Several other models were tested including those using variations of the dependent variable. Although the parameter estimates changed across the models, these changes did not affect our substantive conclusions: the relative explanatory power and direction of each covariate remained unchanged.
4. Discussion Our findings of no racial preferences in the Topps Numbering System (TNS) are not inconsistent with those of Regoli et al. (2004). As they reported, white players received preferential placement in Topps’ card sets from 1956 to 1965, then from 1966 to 1980 (excepting 1970 and 1977) blacks were assigned the more prestigious card locations than their performance would have indicated. Regoli et al. (2004) speculated this dramatic reversal was a result of the increased awareness of racism in its many forms and the mounting societal desire to end such
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practices. The Civil Rights Movement brought sweeping changes to many facets of American culture; it is not unreasonable to conclude this wave of change was also felt and acted upon by the Topps baseball card empire. We have a long standing interest in the nature of the hobby of baseball card collecting, particularly its social hierarchies and mechanisms of social control. The origins of this curiosity can be traced to early observations of one of the authors who started collecting baseball cards in the mid-1950s. He and his peers had become very aware of their being “something” significant about the numbers on the backs of Topps’ cards. They identified a strong association between the status of certain players and the numbers they received in the card deck. The awareness of this difference led him and his friends to first look at the card numbers when opening a new pack of cards and then to look at the players who were pictured on them. For years not much was made of this practice; the frivolous pursuits of children. Then, we read Feagin’s Racist America (2000), where he contends that America is a total racist society. For some, Feagin’s assertion raised eyebrows; for us it raised some intriguing questions: Was something more significant than the “objective” ranking of our sports heroes going on with the TNS? Was the TNS one more piece in the much larger societal picture engaged in the transmission of a racist ideology? We approached these questions with a bit of skepticism because of a growing body of literature indicating a decline in racism (e.g., Butler, 1991; Farley, 1984; Farley & Allen, 1987; Moskos & Butler, 1996; Wilson, 1981). We decided to put Feagin’s idea of America being a total racist society to a test in one of the more inconsequential areas of American culture: baseball card collecting. We believed that if racism had permeated baseball card collecting, then, it probably also was true that racism had infected much of the “heart and soul” of American society as Feagin suggested. This possibility was tested by examining decisions Topps made regarding where to locate players in card sets it issued when Topps had an iron grip on the sport card industry. Of particular interest to us was whether during the “Topps Era,” the decisions made about where to locate players in sets were based primarily on achievement (WS) or ascription (race). Our results suggest that during the Topps Era, taken as a whole, decisions about player location were based upon on-the-field performance and were not racially motivated. These findings, however, do not necessarily contradict Feagin’s (2000) assertion regarding the pervasiveness of racism in American society. There is little doubt that racism is extensive. But does it permeate all spheres of social structure and process? Our findings suggest it does not. There are clearly arenas in which notions of ability, competence, and performance, rather than race, defines the value placed on outcomes—in this case, the status location of the cards of baseball players. Other research supports the idea that sensitivity to race is present in the hobby of baseball card collecting (e.g., Bloom, 1997; Regoli, 2000). Our results of no racial preference in the TNS might be a byproduct of the two opposing eras of preference, reported by Regoli et al. (2004), simply “canceling one another out.” This prospect suggests a topic for future study for other researchers. Although the present work addresses several of the shortcomings of Regoli et al. (2004), like Regoli et al. it fails to examine the trends that have occurred. This work, in part, was intended to mitigate some of the volatility that could occur from year to year in placing players in the Topps card sets, but in doing so; we lose sight of the “little picture,” the shifts in practices that may have occurred over time in player placement in the Topps sets.
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Notes 1. Latinos were excluded from this sample because too few (five players) met the criteria for inclusion for any meaningful statistical analysis to be performed. 2. The sample was limited to players who received votes for HOF induction since in a world free of bias; these are the very same players who would receive the vast majority of the favorable card positions in the TNS. The elite card positions are (theoretically) reserved for the elite players and this is precisely the relationship being tested. While some research has indicated racial bias in election to the HOF (for example Desser, Monks, & Robinson, 1999; Findlay & Reid, 1997), our sample includes not only those elected to the HOF but also those simply receiving votes and this inclusion should aid in mitigating bias if it indeed exists. 3. Players’ race was generally determined in a manner similar to that used by Brown and Bear (1999) in their analysis of disparities in field position of minorities in major league baseball between 1952 and 1987. Players were initially classified as black or white based on facial features on their cards. If a player’s facial features suggested he was black, but he had a Latino surname, The Baseball Encyclopedia (Prebenna, 1990) was used to determine whether the player was born in a Latin American country. Black players with Latino surnames born in the United States were classified as black, while those born in Latin American countries were counted as Latino. This photo identification method was chosen because this is the method collectors use to determine a player’s race. We have (collectively) studied sport card collecting for more than 20 years; attended over 100 local, regional, and national conventions; presented research at the National Sports Collectors Convention; and discussed the topic of race and sport cards with countless collectors. Invariably, when we ask a collector how they determine a player’s race they respond: “By looking at the picture on the card.”
Acknowledgments The Council on Research and Creative Work at the University of Colorado provided partial funding for the study. We thank our colleague, Jason Boardman, for his assistance, guidance, and patience. We also appreciate the support of our colleagues, particularly Michael Radelet whose comments helped us to improve the paper. References Andersen, T., & LaCroix, S. J. (1991). Customer racial discrimination in Major League Baseball. Economic Inquiry, 29, 665–677. Becker, H. (1963). Outsiders: Studies in the sociology of deviance. New York: Free Press. Berger, S., & Slocum, F. (1985). The complete picture collection of Topps baseball cards, 1951–1985. New York: Warner Books. Bloom, J. (1997). House of cards. Minneapolis: University of Minnesota Press. Bonilla-Silva, E. (2003). Racism without racists: Color-blind racism and the persistence of racial inequality in the United States. Oxford: Rowman and Littlefield Publishers.
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