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And the Award Goes too… External Status as a Driver of Cumulative Advantage by Molly Contini A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Arts in Psychology Guelph, Ontario, Canada © Molly Contini, August, 2020
ABSTRACT AND THE AWARD GOES TOO… EXTERNAL STATUS AS A DRIVER OF CUMULATIVE ADVANTAGE Molly Contini Advisor: University of Guelph, 2020 Dr. Jeff Spence Awards are prevalent in almost every area of society and yield a number of material and immaterial benefits. This research aims to extend our understanding of the effect of immaterial benefits associated with receiving an award on long-term future employee career outcomes. Drawing upon the Mathew Effect, I examine if status gain as a result of winning an award is associated with career outcomes (i.e., opportunities and productivity) irrespective of productivity levels prior to receiving the designation. This work used professional sports data to address potential confounds that may account for career differences (e.g., talent, ability) between award winners and non-winners. Overall, my results indicated some evidence for the Mathew Effect hypothesis. Specifically, award winners were found to receive more opportunities than non- winners, however, winners were not found to be more productive than non-winners.
iii DEDICATION This thesis is dedicated to Mathew Wuest, the founder of hockey salary site GapGeek, who passed away following a two-and-a-half-year battle with colon cancer in 2015. Mathew was a pioneer in NHL media and this thesis could not have been completed without his vision and hard work.
iv ACKNOWLEDGMENTS First and foremost, I’d like to express my gratitude to my advisor, Dr. Spence. You have been a constant source of guidance and support and I am very much grateful for your thoughts, feedback, and insights throughout this process. I’d also like to thank my committee members, Dr. Powell and Dr. Stanley. I learned a great deal from you both and I so appreciate your time and input on this project. A thank you must also be extended to Dr. Giguère and Dr. Gill for their willingness to help with my thesis defense in their roles as external and chair, respectively. I feel quite fortunate to have had you both as a part of my defense day. It’s been a true blessing to be a part of the University of Guelph I-O Psychology program and a special thank you goes out to my cohort for their kindness, encouragement, and support. Lastly, I’d like to thank the best fans in the game – my family. In no way do I deserve such a loving and loyal contingent, but I’m so thankful to have it anyways.
v TABLE OF CONTENTS Abstract ......................................................................................................................................... ii Dedication ………........................................................................................................................ iii Acknowledgements ...................................................................................................................... iv Table of Contents .......................................................................................................................... v List of Tables .............................................................................................................................. viii List of Figures ................................................................................................................................ x And the Award Goes too… External Status as a Driver of Cumulative Advantage ..................... 1 Awards and Status .............................................................................................................. 3 Cumulative Advantage and the Mathew Effect ................................................................. 5 Awards and Career Outcomes: Cause or false cause? ..................................................... 10 Are there other mechanisms that are critical in the cumulative advantage process? ....... 12 Can we examine the effect of awards on career outcomes independent of recipient’s endogenous characteristics? ............................................................................................. 13 The Current Study ............................................................................................................ 15 Study 1………………….............................................................................................................. 16 Methods ............................................................................................................................ 16 About the dataset .................................................................................................. 16 Measures .............................................................................................................. 19 Team Award ......................................................................................................... 19
vi Productivity .......................................................................................................... 20 Opportunity .......................................................................................................... 21 Results .............................................................................................................................. 21 Stanley Cup as a Marker of Affiliation-Based External Status ........................... 21 Winners Against Non-Winners and Finalists ...................................................... 22 But don’t teams with the best players win? ......................................................... 25 Do differences in outcomes arise after the win? .................................................. 27 But what role does opportunity play in the cumulative advantage process?........ 32 Study 1 Discussion ……................................................................................................... 34 Study 2 ......................................................................................................................................... 36 How do differences in career outcomes arise? ................................................................ 36 Methods ........................................................................................................................... 36 About the dataset ……………............................................................................. 36 Measures .............................................................................................................. 38 Length .................................................................................................................. 38 Total Salary .......................................................................................................... 38 Average Annual Value ......................................................................................... 21 Results .............................................................................................................................. 39 Study 2 Discussion ........................................................................................................... 40
vii General Discussion ..................................................................................................................... 40 Limitations and Future Directions ............................................................................................... 44 Conclusion …............................................................................................................................... 46 References .................................................................................................................................. 47
viii LIST OF TABLES Table 1. Multilevel logistic regression results predicting wining or not winning the Stanley Cup with player statistics...................................................................................................................... 56 Table 2. Results of Opportunity t-tests and Descriptive Statistics (Non-Winners) ..................... 57 Table 3. Results of Opportunity t-tests and Descriptive Statistics (Finalists) ............................. 58 Table 4. Results of Productivity t-tests and Descriptive Statistics (Non-Winners) ..................... 59 Table 5. Results of Productivity t-tests and Descriptive Statistics (Finalists) ............................. 60 Table 6. Results of Opportunity t-tests and Descriptive Statistics (Non-Winners, Best Players Removed) ..................................................................................................................................... 61 Table 7. Results of Opportunity t-tests and Descriptive Statistics (Finalists, Best Players Removed) ..................................................................................................................................... 62 Table 8. Results of Productivity t-tests and Descriptive Statistics (Non-Winners, Best Players Removed) ..................................................................................................................................... 63 Table 9. Results of Productivity t-tests and Descriptive Statistics (Finalists, Best Players Removed) ..................................................................................................................................... 64 Table 10. Means and standard deviations for GP as a function of a 2(Won Cup) X 2(Time) design ........................................................................................................................................... 65 Table 11. Means and standard deviations for TOI as a function of a 2(Won Cup) X 2(Time) design ........................................................................................................................................... 66 Table 12. Means and standard deviations for Pts as a function of a 2(Won Cup) X 2(Time) design ........................................................................................................................................... 67 Table 13. Fixed-Effects ANOVA results using Games Played as the criterion .......................... 68 Table 14. Fixed-Effects ANOVA results using Total Ice Time as the criterion .......................... 69
ix Table 15. Fixed-Effects ANOVA results using Points as the criterion ....................................... 70 Table 16. Causal Mediation Analysis .......................................................................................... 71 Table 17. Results of t-tests and Descriptive Statistics (Compensation) ...................................... 72
x LIST OF FIGURES Figure 1. Group means for the interaction of Games Played as a function of a 2 (Won Cup) X 2 (Time) design................................................................................................................................ 73 Figure 2. Group means for the interaction of Total Ice as a function of a 2 (Won Cup) X 2 (Time) design ............................................................................................................................... 74 Figure 3. Group means for the interaction of Points as a function of a 2 (Won Cup) X 2 (Time) design ........................................................................................................................................... 75 Figure 4. . Proposed mediation between being a Stanley Cup winner and points as mediated by games played ................................................................................................................................ 76 Figure 5. Unstandardized coefficients for the relationship between being a Stanley Cup winner and points as mediated by games played ..................................................................................... 77
And the Award Goes too… External Status as a Driver of Cumulative Advantage Awards are prevalent in almost every area of life from sports, the arts, culture, politics, academia through to the corporate domain (Frey, 2005). There are high school awards, government awards, business awards, professional awards, military awards, entertainment awards, and athletic awards. There are even tongue and cheek satirical awards (e.g., Ig Nobel awards, Razzies). Awards can be awarded to organisations, teams or individuals and can recognise a single event or an enduring activity (Harrison & Jespen, 2015). Although awards can differ in several aspects, awards fundamentally serve to recognize and distinguish an individual on criteria deemed important by the award giver (Gallus & Frey, 2017). In most cases, awards are markers of recognition, distinction, and as such, are often celebrated and announced in a public fashion (Gallus & Frey, 2017). Awards are intended to have a positive effect on the recipient and yield a number of material and immaterial benefits (Kosfeld & Neckermann, 2011). Material benefits from winning an award may include money, medals, statuettes or specific privileges (Gemser et al., 2007), whereas immaterial benefits often include status, social recognition, and popularity (Kosfeld & Neckermann, 2011). The value of both material and immaterial benefits varies according to the award received. For example, a paper certificate might be awarded to the winner of a workplace award. Here, the material benefits can be rather trivial (i.e., receiving a special piece of paper) and perhaps only ones’ colleagues and family members might be aware of the recognition. In contrast, an individual who is awarded the MacArthur Fellowship (colloquially known as the MacArthur “Genius” Grant) wins $625 000 USD over a five-year period (Schuessler, 2019) and receives wider reaching public recognition, popularity, and status as a result of their award win (e.g., 1
https://www.nytimes.com/2019/09/25/arts/macarthur-genius-grant-winners-list.html). Thus, immaterial and material benefits are usually present in all awards, but their respective magnitudes are dependent on the award and the context in which it is given. As valuable as some material benefits may be (i.e., large monetary sums, elegant statues), the immaterial benefits of awards might outweigh the material benefits. Because publicity is often a central feature of awards, the potential for immaterial benefits are ubiquitous. However, despite the ubiquity of awards and their potential to convey immaterial benefits, little is understood about the consequences of awards on recipients (Gallus & Frey, 2017). RK Merton started an investigation as to how the immaterial benefits from winning an award impacts career outcomes in the 1960’s. Dubbed The Mathew Effect, Merton posits that status from winning an award results in more opportunities -- and from the increased opportunities, more productivity results (Merton, 1968). The Mathew Effect has been thought to explain productivity differences that arise between the careers of winners and non-winners (e.g., Merton, 1968; (e.g., Chan et al., 2014; Erfanmanesh & Moghiseh, 2018; Bol et al., 2018). However, because awards are generally thought to be awarded to the top candidate in a domain and winners receive both material and immaterial benefits, it is challenging to determine the extent to which career outcomes may be due to the positive individual characteristics that resulted receiving the award (e.g., talent, ability) or are the result of immaterial benefits (e.g., status, reputation) that came from receiving the award. These questions present a possible false cause scenario, where a causal link is thought to exist that may not exist (Manninen, 2019). Specifically, if award winners are found to have better career outcomes than non-winners, are the outcomes attributed to the award itself or to the positive qualities of the winner that were in place prior to receiving the award? The goal of the current paper is to examine this issue specifically 2
and investigate if immaterial benefits from receiving an award (e.g., status, reputation) can get converted into positive career outcomes, irrespective of recipients’ positive endogenous characteristics of winners (e.g. talent, ability). Awards and Status Although material benefits are valuable to recipients, the immaterial benefits of awards may outweigh material benefits due to their lastingness. Material benefits of awards are typically finite and discontinuous (Frey, 2007), whereas immaterial benefits need not be. For example, material benefits are often awarded once (e.g., an Oscar) or over a finite period of time (e.g., funding awards). In contrast, winning an award sets the recipient apart from their peers and results in a special form of social distinction that can last for years, decades, and even spread and grow over time (Frey, 2007). As long as prospective recipients value the award and have a desire to obtain it, recipients will enjoy immaterial benefits such as status, reputational, and recognitional benefits as a result of being connected to the award (Frey, 2007). The extent of this benefit and its lifespan is not readily quantifiable (e.g., How many people and to what extent do these people hold someone in high esteem?). Additionally, these non-material benefits associated with winning an award may be quite enduring. The continuous immaterial benefits conferred by awards has also been referred to as external status. External status can be defined as how broad one’s visibility is outside of their own organization (Kehoe et al., 2018). Per Kehoe et al. (2018) employees may attain external status as the result of attributes independent of the level or visibility of his or her current task performance (Kehoe et al., 2018). A sub-type of external status, affiliation-based external status, is status gained as a result of a close personal connections with and/or sponsorship by an elite individual or institution (Kehoe et al., 2018; Merton, 1973). Affiliation-based external status can 3
be either biologically or figuratively inherited, rather than established from demonstrated quality (Kehoe et al., 2018). Most individuals receive affiliation-based external status or favorable attributions on the basis of their affiliation after winning an award (Judge et al., 2004; Long et al., 1979; Nahapiet & Ghoshal, 1998). Essentially, affiliation-based external status is the social capital one receives simply by winning an award and by being associated with that award. Affiliation-based external status can be very beneficial for award winners, both new and old. The perception of the award’s past recipients is directly affected by entry of new members, who have favourable reputations, and new members benefit from entering a group with esteemed members (Frey & Gallus, 2017). The exclusivity and reputation of the past award recipients results in the award having value as a signal of valor and prestige for the new award recipients (Frey & Gallus, 2017). Since winners are accepted into the “inner circles” of an industry’s elite, they enjoy favorable attributions ascribed on the basis of their associations with high status actors (Judge et al., 2004; Long et al., 1979). Thus, affiliation-based external status serves as a signal or message to outsiders, regardless if they are a subject matter expert or not, that the award winner is excellent (Bruno & Gallus, 2016). Not surprisingly, affiliation-based external status is often used to render judgments about the award winner. Changes to an individual’s status, such as winning an award, often influences perceptions of the quality of what the individual produces (Azoulay et al., 2014). Status creates the presumption of higher quality, thereby implicitly suggesting that greater attention is warranted to awards winners (Merton, 1968). As such, one of the benefits of status is that those who possess it attract more attention and resources, which further enhance their ability to create goods of high quality (Azoulay et al., 2014). So, award winners receive more favourable judgments as a result of their affiliation-based external status and this can, in turn, result in more 4
favourable career outcomes through access to attention and resources. Cumulative Advantage and the Mathew Effect The conversion of acquired resources to additional future resources has been examined via cumulative advantage (Merton, 1968). Cumulative advantage has been proposed as one mechanism that may explain the potential positive effects that awards can have on individuals’ career outcomes. The main idea in the cumulative advantage literature is that an advantage of an individual or group accumulates over time, resulting in increased disparity between groups (or individuals) increasing over time (Diprete & Eirich, 2006). The concept of cumulative advantage outlines a process through which initial comparative advantages make for successive increments of advantage, such that the gaps between those who have resources and those who do not widen over time (Merton, 1988). An initial advantage is typically a key resource or reward, for example, career position, income, wealth, or health (DiPrete & Eirich, 2006). Cumulative advantage has been frequently used in social sciences to explain differences in a variety of outcomes including social mobility, poverty, race, crime, education, and human development across people and groups (DiPrete & Eirich, 2006). The receipt of an award and benefitting from its positive effects is consistent with the Mathew Effect, a particular form of cumulative advantage (Merton, 1968, 1973ab, 1988). The Matthew effect takes its named from one of Jesus’ parables, The Parable of the Talents, written in the book of Matthew (Mathew 25:14-30, New American Bible). The parable is known for verse 29 which states, “For to all those who have, more will be given, and they will have an abundance; but from those who have nothing, even what they have will be taken away.” Merton defines the Matthew Effect as “the accruing of greater increments of recognition for particular scientific contributions to scientists of considerable repute and the withholding of such 5
recognition from scientists who have not yet made their mark” (Merton 1973a, p. 446). The Mathew Effect exists as a mechanism to explain how initial advantages can grow over time. The Mathew Effect was identified during an analysis of Nobel Laureates. Merton (1968) determined that, due to the scarcity of prizes, there was and will always be scientists who have created prize-winning caliber work and have made equivalent contributions to science as laureates have, but who will not win the Nobel Prize. As such, Merton (1968) sought to investigate the ways psychosocial processes affect the allocation of rewards to scientists. Merton (1968) found that the recognition accorded by scientific achievement (e.g., winning an award) is an instrumental asset. This finding led to the articulation of the Mathew Effect and years of subsequent scientific research (e.g., Bol et al., 2018; Azoulay et al., 2014; Borjas & Doran, 2015; Chan et al., 2014). The Mathew Effect is particularly influential because it impacts how scientists view and consume research. Namely, Merton (1968) proposed that a scientific contribution will have greater visibility in the community of scientists when it is introduced by a scientist of higher rank (as measured by the prestige of the awards they have received for scientific work) than when it is introduced by one who has not made their mark. Eminent scientists get disproportionately greater credit for their contributions to science, whereas relatively unknown scientists tend to get disproportionately less for their comparable contributions (Merton, 1988). As such, award- winning scientists accrue large amounts of peer recognition, and their contributions are the most likely to enter promptly and widely into the communication networks of science, and this accelerates the works development (Merton, 1968, 1988). It is the initial recognition, achieved by winning an award, that is thought to begin the cycle of cumulative advantage between winner and non-winners. 6
A key principal of cumulative advantage, the Mathew Effect, is that a driver of current and future achievements may be past recognitions, irrespective of differences in ability. When award-winning scientists begin to receive peer recognition, it is thought to begin a process of cumulative advantage in which those individuals tend to acquire successively greater opportunities for advancing their work (and the rewards that go with it; Merton, 1988). Merton (1988) proposes that this initial success increases one’s level of resources, and it is the heightened level of resources that, in combination with skill, leads to future productivity. In a process similar to compound interest, small initial differences compound to yield larger differences over time (Maillart et al., 2008). Differences in individual capabilities aside, the process of cumulative advantage may accentuate inequalities in the amount of recognition one receives, access to resources, and subsequent productivity (Merton, 1988). Thus, an initial award win may result in winners being more productive over the course of their career, as compared to a finalist for that same award, as a result of a potentially initial small advantageous position. The Mathew Effect proposes that receiving an award can potentially create substantial inequalities between two individuals of relatively similar ability by way of its conferred immaterial benefits (i.e., affiliation-based external status) over time. However, empirical research on whether the Matthew Effect, after receiving awards, influences future productivity has been mixed (e.g., Borjas & Doran, 2015; Chan et al., 2014; Wagner et al., 2015). Some research supports the idea that winning an award facilitates subsequent productivity; however, there is also evidence to suggest award winners are actually less productive post-win (e.g., Borjas & Doran, 2015; Chan et al., 2014; Wagner et al., 2015). A number of studies lend support to the idea that receiving a prestigious award perpetuates cumulative advantage and results in increased productivity. For example, winners of 7
the John Bates Clark Medal, awarded to an American economist under forty who made a significant contribution to the field, resulted in increased future productivity (measured by publications) as well as higher status (reflected by citations; Chan et al., 2014). Similarly, after becoming an Economic Society fellow, fellows similarly produced significantly more publications than the control group (Erfanmanesh & Moghiseh, 2018). Further, winning the Derek de Solla Price Memorial award, an award given in the field of quantitative science, similarly facilitated research performance and publishing behavior of medalists (Erfanmanesh & Moghiseh, 2018). Similarly, Azoulay et al. (2014) find evidence of a moderate post-appointment citation boost after scientists who are appointed as investigators at the Howard Hughes Medical Institute (HHMI). Award winners in these studies were found to be more productive after winning their award and this finding lends support to the concept of cumulative advantage. There is also evidence to suggest that award winners receive additional resources after winning an award. Bol et al. (2018) find that, despite having similar academic backgrounds, early award winners accumulate more than twice as much research funding (€180,000) during the following eight years as nonwinners with near-identical, but slightly lower grant application review scores. Yan et al. (2020) analyze citation sentiments of articles and find individuals enjoy a moderate sentiment gain for their Nobel articles after they win a Nobel Prize. Ye et al. (2013) suggest that 70% of the Nobel laureates (during 1983–2012) had obtained the Gardiner Award prior to getting the Prize, suggesting those who win an award are more likely to win another later in their career. In the field of entertainment, Levy (1987) found that actors had increased power and earnings after an Oscar win. In a similar vein, Redelmeier and Singh (2001) found winning an Academy Award increases longevity for actors, with Academy Award winners living 3.9 years longer than non-winners. This literature provides support for the mechanism of cumulative 8
advantage as award winners are more productive and earn more resources than their peers that have not won awards. Specifically, it also suggests that immaterial benefits from awards have the potential to be converted to increased material benefits overtime. In contrast, other research investigating the impacts of awards does not find evidence for the cumulative advantage hypothesis. For example, Borjas and Doran (2015) find that Fields Medal winners, the most prestigious award in mathematics, produce fewer papers per year in the post-medal period than would be predicted either from their previous output or from the output of other mathematicians who were in contention for the award, but who did not win. Not only are Fields Medal recipients publishing fewer papers in the post-medal period, but those papers are relatively less important, and they are accepting fewer mentees. Despite the decline in productivity after winning the field medal, medal winners receive more wealth in terms of academic prestige and in academic freedom than non-winners (Borjas & Doran, 2015). Similarly, Wagner et al. (2015) compared Nobel Laureates in Physiology or Medicine to scientists of comparable abilities and found that the Laureates produced fewer papers than their peers after winning, but those papers had higher average citations. This evidence partially contradicts what cumulative advantage hypothesizes as winners are less productive post-win, but does suggests winners do enjoy affiliation-based external status (i.e., freedom, prestige and recognition) as a result of belonging to elite institutions. Other works similarly find evidence that contradicts the cumulative advantage hypothesis. Chan and Torgler (2014) examined Nobel laureates in physics, chemistry, and medicine or physiology and found laureates enjoyed increasing rate of awards before Nobel reception, reaching the summit precisely in the year of the Nobel Prize. After this pinnacle year, awards drop sharply. Farys and Wollbring (2017) examined the impact of winning the Nobel 9
Prize on citations and found winning the Nobel Prize did not have an impact. Kovacs and Sharkey (2014) found that winning a literature award lead to increased popularity, but lower ratings. Lastly, Harrison and Jespen (2015) interviewed winners of prominent workplace awards and did not find a relationship between winning an award and career success measures such as promotions or salary increases. As such, there appears to be findings that both support and contradict the Mathew Effect in the literature. Awards and career outcomes: Cause or false cause? Empirical research suggests that the effect of awards on recipients’ may not be straightforward. The effect of awards on career outcomes is likely a dynamic process that unfolds over a long period of time (e.g., years and decades) and involves the interaction between a number of psychological, perceptual, and decision-making processes both within and outside of the recipient. In addition, one of the main challenges of interpreting empirical results on the effect of awards on outcomes is the confounding nature of awards winner’s endogenous characteristics with the receipt of an award. That is, trying to answer the question of if and the extent to which affiliation-based external status from awards and recognitions uniquely contributes to career outcomes is inherently difficult because it is generally recognized that awards are commonly the result of some type of excellent performance generally attributed to something special about the individual. Indeed, most of the research on awards examines awards that are achievement-based (e.g., Fields Medal, Nobel Prize). As a result, the extent to which an award is perceived to have merit, winners may be presumed to be more deserving, via better performance, achievements, etc. than non-winners, because if non-winners were better or equivalent, they would have won the award. Bol et al. (2018) note that research on the Matthew Effect has been hampered by the 10
possibility that observed cumulative differences in achievement may in fact be the gradual manifestation of interpersonal differences in talent or productivity (Bol et al, 2018). Further, Azoulay et al. (2014) note that an actor's quality and status are typically tightly intertwined and question if status itself affects outcomes or if status is simply a by-product of an actor’s quality. As such, it is difficult to evaluate the Mathew Effect and examine the effect affiliation-based external status has on career outcomes if exceptional individuals receive awards. The Mathew Effect is therefore vulnerable to the false cause fallacy. A false cause fallacy is committed when an argument mistakenly identifies a causal link between a premise and conclusion that may not exist (Manninen, 2019).The fallacy comes in many forms, one of which is the post hoc ergo propter hoc (or post hoc) version and is when an event B is followed event A and A is attributed to be the cause of B (Manninen, 2019). An oft-cited example of this fallacy is that childhood vaccines are the cause of autism (Manninen, 2019). Another example of false cause fallacy is ignoring a common cause (Manninen, 2019). Namely, identifying a correlation and attributing one side of the correlation as a cause and the other as an effect, when they were both caused by a third variable. When trying to establish causality between receiving an award and having positive career outcomes, it may be easy to commit the false cause fallacy. The Mathew Effect could be an instance of ignoring the common cause: the winner’s ability and/or other exceptional characteristics. In response to causality concerns, researchers of the Mathew Effect have started to focus on specific mechanisms and use different research designs. Azoulay et al. (2014) utilized a research design that offers a more definitive test of the effect of a change in status on performance. Specifically, the authors focused on how a change in status affected evaluations of outputs that were produced prior to the time the prize was granted to determine how a shock to 11
status influences perceptions of quality (Azoulay et al., 2014). The authors note that though the focus on the perceptual mechanism results in a study of a singular component of the Matthew effect, they are able to further understanding of a specific mechanism that is imperative to the cumulative advantage process (Azoulay et al., 2014). The authors call for future research to parcel out specific components of the Mathew Effect to help disentangle the effect of immaterial benefits of awards from other contributors and determine the impact of increased status. Are there other mechanisms that are critical in the cumulative advantage process? An important mechanism to understand cumulative advantage may be opportunity. Merton (1988) suggests that when award-winning scientists begin to receive peer recognition, it begins a process of cumulative advantage in which those individuals tend to acquire successively inflated opportunities for advancing their work (and the rewards that go with it). Specifically, the theory of cumulative advantage postulates that winners enjoy elevated status and therefore get better access to opportunities. This, in turn, facilitates higher performance and resource gains (Merton, 1988). Thus, opportunities may be imperative to understanding cumulative advantage. Despite the importance of opportunities, it is not clear if winning an award affects subsequent opportunities. The majority of papers strictly compare measures of post award productivity and do not gather explicit measures of opportunities pre or post award (e.g., Chan et al., 2014; Wagner et al., 2015). In contrast, Boras and Doran (2015) analyzed opportunities post- win and found that winning is associated with a strong increase in the likelihood that a mathematician tries out fields that are very distant from those fields that established their reputation (Boras & Doran, 2015). This suggests that award winners are more likely to follow up or pursue new opportunities following their win. In this particular case, because these opportunities tended to be outside of winners’ fields of expertise, it made winners less 12
productive. However, if winners pursued increased opportunities in their home fields, it is possible that productivity would have increased. The findings of Boras and Doran (2015) highlight the potential important role that opportunities can play in determining the outcomes of award winners. In particular, it highlights that it is not only the availability of opportunities but also the type of opportunities that are available and pursued that is important. Can we examine the effect of awards on career outcomes independent of recipient’s endogenous characteristics? Investigating affiliation-based external status may provide a unique opportunity to examine the effect of awards on outcomes, irrespective of ability and other positive endogenous characteristics. Affiliation-based external status occurs when an individual enjoys broad attention as a result from a close affiliation with an elite person or institution and is independent of the level or visibility of their current task performance (Kehoe et al., 2018; Merton, 1968). Affiliation-based external status is the recognition one receives as a result of belonging to an elite group (Kehoe et al., 2018) and can thus be achieved without requiring a high level of performance or productivity in a particular domain. Thus, pinpointing and examining the onset of affiliation-based external status may provide a unique opportunity to assess the Mathew Effect. Additionally, correctly identifying the onset of affiliation-based external status provides a scenario were one can compare post status acquisition outcomes against those who did not receive the status, while not conflating outcomes with other endogenous characteristics. Isolating the onset of affiliation-based external status is challenging because the acquisition of affiliation-based external status is a result of connections or association and is not recorded formally nor is it publicly bequeathed in a ceremonial way. As a result, it is difficult to isolate the moment in time when individuals acquire affiliation-based status. However, if there 13
was an award, given to individuals in a public, ceremonial way that conferred affiliation-based external status, then it would be possible to identify the precise moment of the acquisition of status with the receipt of the award. Moreover, because affiliation-based external status is not necessarily linked to ability or talent, this award would still need to provide a significant amount of status, but not be awarded based on superior individual differences. Should this criterion be met, it would provide an opportunity to examine if winners have better career outcomes than non-winners due to the benefits of the award or their ability. I propose that a league championship trophy from a professional team sport is an award that confers affiliation-based external status. Specifically, a championship in a team sport is a team award and therefore is not specifically a marker of individual team members’ task performance; yet, the team award provides affiliation-based status to all individual winners. For instance, a player can win the league championship in a year where their individual performance and productivity was the worst of their individual career. Moreover, certain team sports transfer team level achievement to individual players by way of clear ceremonies or rituals. For example, individual players may receive personalized trophies (e.g., championship rings) or have their individual names engraved on the league trophy (e.g., Stanley Cup). In team sports, both winning teams and non-winning teams consist of a large number of players with variable skill and productivity levels. This allows for naturally occurring control groups, where one can find players from winning and non-winning teams of equal ability. Thus, award winners can be matched with non-award winners of commensurate ability and comparisons can be made post- award win to determine the impact of the award. Considering league championships are awards that are not allocated based on individual productivity, but still transmit a substantial amount of status, I propose that a league championship trophy may be utilized of affiliation-based external 14
status. Examining cumulative advantage and the Matthew Effect in the context of professional sports has other advantages. Sports data provide a number of objective measures to study the cumulative advantage process: awards, opportunities, and productivity. These data also facilitate the examination of phenomena over time as individual player statistics are recorded and logged across careers. This allows researchers to use behavioral data from real-world contexts and makes it possible to create relatively large samples from a variety of sources (Heng et al., 2018). The meticulous tracking and recording of statistics, public nature of the dataset, and objective measures of individual productivity makes a good fit for determining how affiliation-based external status may affect career outcomes of individuals. The Current Study In the current research, I seek to determine if winning an award that confers affiliation- based external status is associated with differences in career outcomes. In doing so, I attempt to address limitations of previous work by formally operationalizing and investigating opportunity as a mechanism of the effect of awards on career outcomes. Further, I select and study an award that is not conflated with individual’s positive exogenous characteristics. Using professional sport data, I examine if being designated as “a winner” (by way of attaining a league championship) is associated with better career outcomes (i.e., opportunities, productivity, compensation) irrespective of other individual differences that are known to predict success. Specifically, this work seeks to answer: 1) Do individuals with affiliation-based external status have more opportunities across their careers than individuals of equal ability who do not have the same affiliation-based external status? 15
2) Are those with affiliation-based external status more productive across their careers than individuals of equal ability that do not have the same affiliation-based external status? To answer these questions, I use several analytic strategies from two different datasets. In one dataset (Study 1), I compare award winners to different groups of non-winners. I compare award winners and a group of non-winners on career opportunity and productivity statistics. Next, I compare career outcomes between award winners and award finalists. Then, I use a matching technique to compare winners and with similar peers at the time of the win. I then examine whether opportunity increases are a mechanism for productivity increases using mediational analyses. In the second dataset (Study 2), my goal is to explore how potential opportunity and productivity differences between winners and non-winner accumulate over time by examining if winners receive immediate benefits upon their win. Study 1 Method About the Data To investigate these questions, I will use data from the National Hockey League (NHL). The league championship trophy of the NHL is called the Stanley Cup. The Stanley Cup was chosen for several reasons. I decided to utilize a team championship trophy because they provide the opportunity to analyze affiliation-based external status in a context where winners have varying levels of ability. Professional sports actively work to prevent all of the top players from ending up on the same team by instituting salary management practices (“What is a Salary Cap”, 2020). Part of the NHL’s salary management practice involves implementing a salary cap. Salary caps are wage caps that impose a limit on the total amount of money a team can spend on 16
players' salaries. During a “free agency” period, when players are allowed to sell their services to teams, a salary cap prevents the most well-capitalized teams from recruiting and signing all of the top players (“What is a Salary Cap”, 2020). One of the rationales for the use of a salary cap is that they prevent one team from gaining an unfair advantage over the rest of the competition because they can afford more star players (“What is a Salary Cap”, 2020).Whereas differences in career outcomes after winning an individual award are often conflated with ability prior to receiving the award, the structure of professional sports necessitates winning teams having players of differing abilities. Thus, there will be players on non-winning teams that are of commensurate abilities as players on winning teams and analyses can be conducted on low or moderate performers. As such, using a team-based award helps to negate the potential effects of endogenous characteristics of winners. The NHL employs fairly strict salary management practices, and this has resulted in a relatively significant amount parity in the league. In sports, parity occurs when teams have roughly equal levels of talent and ability. Puopolo (2016) used preseason title odds, normalized the probabilities of winning a championship to ensure that they summed to 1, and then calculated the Gini Coefficient of these title probabilities to determine which professional sports league had the most parity. The Gini coefficient is a metric used to compare income inequality in different countries. For example, if a country has a Gini coefficient of 0, that means that everyone within the country has the same income level whereas a Gini coefficient of 100 means that all the income is held by one individual (Puoplo, 2016). Puopolo (2016) found the NHL had the lowest Gini coefficient (40.9) compared to the NBA (66.2), MLB (46), and NFL (46.1). Therefore, the NBA had the most unequal economy based on the Gini coefficient of preseason title odds, whereas the NHL has the most equal economy of the big four North American professional 17
sports. Further, most academic research considers the equality of teams within a given season as the central measurement of parity (Lopez, n.d.). Rockerbie (2012) measured parity using relative standard deviation (RSD), where high RSD’s indicate higher variability within each league. The NHL (RSD of 1.606 in the 2000’s) and the NFL (RSD of 1.581), as measured by their lower RSD values, appear to be the professional league’s with the highest amount of parity in recent years. However, the results suggest that the NFL’s parity is as much a function of its number of games as anything else; under the same number of games, it’s the NHL and MLB which show the lowest year-to-year consistency (Lopez, n.d.). Thus, there is some evidence to suggest that the NHL has a significant amount of parity or equality between teams and helps assuage concerns of endogeneity. Further, it is arguable that the Stanley Cup produces the most affiliation-based external status of the major four sports championship trophies. The Stanley Cup is by far the largest trophy, weight 34 lbs and standing at 35.25 inches (Rumore & Tercha, 2017). In North America, it is the only professional sports trophy where the name of every member of the winning team is inscribed on it (Rumore & Tercha, 2017). This process represents players joining a fraternity of those who came before them (Bisson, 2013). The Stanley Cup only one of the big four North American sports to be awarded to a player, not ownership during the league trophy championship presentation (Svrluga, 2020). Hockey is the only sport where the players, as a group, are honoured before anyone else. Lastly, the Stanley Cup is passed from champion to champion. The League Championship trophy for basketball (the Larry O’Brien Trophy), football (The Vince Lombardi Trohy), and baseball (The Commisioner’s Trophy) are remade every year and teams are given replicas of the original (Bisson, 2013). Thus, NHL is uniquely suited to study these processes because the league championship trophy, the Stanley Cup, conveys a high 18
level of affiliation based external status and the NHL has a degree of parity and variability of abilities on each team. Individual player statistics from the National Hockey League (NHL) players drafted in the years 1996 – 2002 were gathered from an online database (HockeyReference). Goaltenders were excluded as they have different performance statistics than forwards and defenseman. In order for a player to be recognized as a Stanley Cup winner, a player on the Stanley Cup winning team must have played at least 41 games in a single season. Therefore, players drafted within the 1996 – 2002 drafts who did not play in at least 41 gamed in a single season were excluded from the data as they were not eligible to have their name on the Stanley Cup. Of the 1896 players drafted in 1996 – 2002, 427 players were eligible for dataset. 75 of those players won the Stanley Cup (18%). Measures Team Award To win the Stanley Cup, the team first has to make the playoffs. In the NHL, there are currently 31 teams, sorted into 2 conferences (the Eastern Conference and the Western Conference). 16 teams make the playoffs. The top three teams in each division (Metropolitan Division, the Atlantic Division, Central Division, Pacific Division) make up the first 12 teams in the playoffs. The remaining four spots are filled by the next two highest-placed finishers in each conference, based on regular-season record and regardless of division. It is possible for one division in each conference to send five teams to the postseason while the other sends just three (“Stanley Cup playoff format”, 2019). In the playoffs, there are four rounds. Winners of a round advance and keep playing, whereas losers do not continue and no longer play. To win a round, a team must be the first to 19
win four games. In the First Round, the division winner with the best record in each conference will be matched against the wild card with the lesser record; the wild card with the better record will play the other division winner three (“Stanley Cup playoff format”, 2019). The teams finishing second and third in each division will meet in the First Round within the bracket headed by their respective division winner. First-round winners within each bracket play one another in the Second Round to determine the four participants in the Conference Finals. The winners of the Conference finals will play each other in the Stanley Cup Finals. The winner of the Stanley Cup finals is considered the Stanley Cup champion (“Stanley Cup playoff format”, 2019). Productivity All productivity measure collected were regular season productivity metrics. The Oxford Dictionary (n.d.) defines productivity as “the effectiveness of productive effort, especially in industry, as measured in terms of output or rates of output”. To win a game, a team must score more goals than their opponents and, as a result, the most commonly used productivity outputs in hockey are goals, assists, points, and plus/minus. A player receives credit for a goal every time they shoot the puck into the opposing team’s net. A player earns an assist if they pass the puck to a player who scores or if they pass the puck to the player who passes the puck to the player who scores. Up to 2 assists can be awarded for each goal scored. Points are the amount of goals plus the amount of assists a player accumulates Plus/minus is a player’s “plus” score less their “minus” score. A player receives a “plus” every time their own team scores a goal when they are on ice. A player receives a “minus” when the opposing team scores when they are on the ice. It is possible to have a negative plus/minus rating if a player in on the ice for more goals against than goals for his team. This work utilizes points and plus/minus as productivity measures. 20
Opportunities The Oxford Dictionary (n.d.) defines opportunity as "a set of circumstances that makes it possible to do something”. In hockey, each team typically has 22 players that can play. Only five players and a goalie are permitted to be on the ice at one time. Goalies typically will play the whole game, but the players do not play the game in its entirety. Players who are not on the ice sit on the bench beside the ice surface, awaiting their turn. Games are 60 minutes long and players can be on the ice for just a few minutes or can play as many as 35 minutes each game. Regardless of the amount of ice time a player receives, it is only possible for a player to be productive when they are on the ice. Players sitting on the bench cannot score goals or play defense. As such, I utilize regular season games played (GP) and total time on ice in minutes (TOI) as measures of opportunity. Playing in a game and being on the ice are occasions that make it possible to be a productive player. Results Stanley Cup as a marker of Affiliation-Based External Status Before proceeding with the primary analysis, I first wanted to empirically test, if the Stanley Cup can be classified as a marker of affiliation-based external status. Because the Stanley Cup is a team award, and because teams are comprised of individuals who have a range of skill levels, it is not likely that individual regular season performance is predictive of success in winning the league championship trophy. However, because it may be that teams who win the championship have individual players who are more productive in the year the team wins, I wanted to test if individual players’ individual level regular season performance is predictive of winning the Stanley Cup in a given season. If individual performance is predictive of winning 21
the Stanley Cup then it suggests that the award is not entirely affiliation-based but instead is at least partially based on how an individual player performs in the regular season. To test for this possibility, I used a multilevel logistic regression. The model sought to test if it was possible to predict the year in which winners won the Stanley Cup with players’ yearly individual productivity and opportunity statistics. Because data is collected across individual players’ careers, individual seasons are nested within players, necessitating multilevel regression. The outcome is at the season level and is whether a player won or did not win the Stanley Cup that year. It is important to note, that in this analysis, it only includes players in the draft cohorts that make up my dataset. As a result, this model tests if an individual player winning the Stanley Cup can be predicted by his individual regular season performance in the year they won. The multilevel logistic regression was run using the glmer function in the lme4 package in R. In this analysis, seasons are nested within players, and the annual outcome of winning (=1) or not winning the Stanley Cup (= 0) was regressed on individual player games played, goals, assists, penalty minutes, time on ice, and plus/minus. The results of this analysis revealed that winning the Stanley Cup was not predicted by games played ( !" = -.0008, p = .99, Table 2), goals ( !# = -.005, p = .97), assists ( !$ = -.005, p = .96), penalty minutes ( !% = -.0007, p = .98), time on ice ( !& = -.0005, p = .89), plus/minus ( !' = -.014, p = .84) (see Table 1). These results provide some evidence to suggest that winning the Stanley Cup can be viewed as being consistent with affiliation-based external status as it is not predicted by individual players’ regular season performance in the year that the award is won. Winners against Non-Winners and Finalists 22
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