Player Pay and Productivity in the Reserve Clause and Collusion Eras
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION Professional athletes are among the highest paid workers in the American economy. Their minimum salaries are several times that of the average American salary, and the average wages are an even greater multiple. Among professional athletes, professional baseball players fare particularly well. They enjoy a minimum salary of $390,000 per year, an average salary exceeding $2 million per year, guaranteed contracts, and arguably the strongest union in American history. Stories of the financial escapades of professional baseball teams and the salaries they pay their employees are common in the sports and business press. It was not always this way. It was not until the mid-1970s when professional baseball players blazed the trail for all professional athletes by gaining the right to bargain competitively for their wages. Before that time, players were bound to their original employer for the duration of their careers. The labor market for ballplayers was a classic monopsony--a market in which there is a single employer and a large number of potential employees. Theory suggests that labor will be exploited in such a market. Previous literature suggests this is the case, but a comprehensive test of this theory using data from the pre-free agency period has not previously been undertaken. Whenever a worker is paid a wage less than the value of his or her contribution to the firm's total revenue, we say that the worker is being exploited. The degree of depends on the amount by which the worker is underpaid relative to his or her contribution to the firm's revenue. The contribution a worker makes to the firm's revenue is called marginal revenue product, and is discussed later. Exploitation of workers can occur in many circumstances, but is more likely to occur in circumstances when workers are unable to bargain for their wages. This is exactly the situation that existed in Major League Baseball (MLB) prior to free agency. Because players were tied to one team, they had limited ability to bargain for their wages, thus it was easier for team owners to exploit them by paying them a wage less than what they were actually worth. Players would tolerate this exploitation because even though they were paid less than their value to the team, the salary they were paid was usually higher than what they could have earned in any other line of work. Baseball salaries in the 1920s, while not as outrageous as today, were still substantially higher than the average wage. (1) Since the dawning of free agency, there have been numerous studies of the baseball player labor market. (2) These previous works have focused on issues such as labor exploitation, the effect of competitive labor markets on competitiveness in the league, and the impact of competition for players on league structure and financial stability. This earlier research has produced some interesting results, including models to calculate the financial contribution of individual players to their teams and the degree of labor exploitation. One of the most famous studies, and the one I use for comparison in this research, is by Andrew Zimbalist, who measured the rate of of MLB players from 1984-86. (3) Baseball fans will immediately recognize this as the famous collusion era. While that is an issue of some concern for measuring labor rates, it is not of particular concern in my work. For this study, the Zimbalist results serve as a reasonable comparison, as I will discuss later. One thing missing in all of this previous work, however, has been a historical foundation for these studies. No work has been done using player salaries for the years prior to 1968 because of a lack of sufficient data. None of these previous studies has covered a time period of more than ten years, and no study to date has used actual team revenue information to calculate a player's financial value to his team and measure the team's of his labor. …
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it