The National Collegiate Athletic Association as a Social-Control Agent: Addressing Misconduct Through Organizational Layering
Bibliographic record
Abstract
The present study focuses on the National Collegiate Athletic Association and cases of misconduct from 1953 to 2016 to examine evidence of organizational layering created by social-control agents. The historical method was employed and found wrongdoing may influence the creation of organizational layers to control and/or manage future behavior. Furthermore, the activities of the National Collegiate Athletic Association featured variation in centralization, formalization, and complexity through expanding horizontal; vertical (e.g., institutional, managerial, and technical); and spatial differentiations. Second, individual social-control agents impact future organizational policies and member behavior but social-control agents’ power may be challenged as an organization grows. Third, as a social-control agent, the National Collegiate Athletic Association struggled with assessing cases of misconduct, assigning sanctions in a timely manner and at a level to deter future wrongdoing. Finally, the present study offers several propositions connecting third-party regulators to the synergy between complexity (i.e., horizontal and vertical differentiations); formalization; and centralization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".