A Topology of Baseball Player Behavior. (Triple Play)
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
The owner of a Major League Baseball team is interested in achieving a specific goal. The goal may be to win a championship, secure a position of prestige in the community, earn a profit, or some combination of these and other aspirations. In the course of reaching the goal, baseball games must be played. Since the owners cannot play the games themselves, they must hire players to do it for them. Economists term this arrangement the principal-agent relationship. In this relationship, the principal--the owner--contracts with the agent--the player--to perform a service on the principal's behalf. Like owners, players also have goals, such as winning a championship or earning fame or fortune. While there may be some similarity, there is no assurance that a player's goal is consistent with that of the owner. The prospect that the goal of the principal and agent may not naturally align is the principalagent problem. Furthermore, a player shirks when his pursuit of a personal goal hinders the owner's efforts. For example, an owner's goal of winning a World Series championship can be compromised by a player who stands and admires--rather than running from first base during--what appears to be a certain World Series home run and is subsequently thrown out at the plate when the hit bounces off the top of the outfield wall. a player benched during a playoff game who is caught by the television camera playing cards in the dugout tunnel. a player who, on the eve of the playoffs, is arrested for drug use in violation of his probation. From the owner's perspective, the solution to the principal-agent problem lies in the terms of the player's contract. Contracts need terms that give players the incentive to perform in a manner that is most likely to result in the team reaching the owner's goal. However, finding the right contract terms is complex. For example, the level of a player's salary is usually the most important component of a contract. The owner must balance the trade- off between paying a player a high salary to elicit his very best performance and maintaining an acceptable level of team profits. Furthermore, the rules set forth by the collective bargaining agreement and the presiding culture in the labor market affect players' behavior and the effectiveness of alternative contract terms. Consequently, to negotiate the optimal contract terms, the owner needs information about the array of player behaviors that can be expected under the presiding labor market regime. This paper develops a topology of baseball player behavior. Player behavior is delineated in terms of on-field production, attitude, and preparation and is stratified into four groups that range from the perfect owner's whose behavior is exactly aligned with the owner's goals, to a shirker, who is so malfeasant that he harms the sport. The influence different labor market regimes have on player behavior and contract terms is explored. Finally, because it is a systematic description of a diverse set of behaviors, the topology permits evaluation of how different labor market regimes encouraged and discouraged different types of player behavior. ENUMERATION OF PLAYER BEHAVIOR Actions by players that may be considered shirking stem from multiple sources. To facilitate the discussion of these sources, the topology groups them into three categories--performance, attitude, and preparation--and defines for each category the behavior that would be characteristic of the owners player, that is, one who is not shirking. Performance concerns the amount and quality of the player's on-field production. By the time a player reaches the Major Leagues, he has been heavily scouted and his potential is well-known. An owner's then, is one who contributes to the team by playing at or above his potential consistently throughout his career. This player has slumps and makes errors. His statistics vary, and occasionally he has a bad year. …
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.087 | 0.001 |
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