Sport slavery : The exploitation of teenagers by ‘mock-amateur’ for-profit sport cartels : a study of the National Collegiate Athletic Association (NCAA) & the Canadian Hockey League (CHL) : can law obtain compensation for these monetized young stars?
Bibliographic record
Abstract
This thesis is a scholarly contribution to law, sport, economics, politics, and children’s human rights. It represents thousands of teenagers tricked into working for no compensation by ‘mock-amateur’ billion-dollar sport cartels. The thesis examines six North American sport cartels, focusing on the Canadian Hockey League [CHL] and National Collegiate Athletic Association [NCAA]. Sport cartels easily exploit teenage athletes because of unrestrained use of the word ‘amateur’. The power behind ‘mock-amateur’ cartels is that they are absolute monopolies with monopsony control, plus hold strategic lobbyist and hegemonic influence — powers that create lawmaking. It is hypothesized that normal civil legal actions and statute law are unable to achieve the teenagers’ compensation rights. The thesis answer is the use of public law and the public inquiry. O’Bannon and Northwestern 2016 litigation results affirmed that mock-amateur cartels are untouchable via litigation strategies, with Canadian 2018 CHL class action trilogy of Berg and Walter likely to produce the same result. I further conclude that the rule of law, Canadian Constitution, separation of powers, federalism, and common law interfere in obtaining fair results. The thesis aims to overturn the cartel arrangement of no-pay, no-Name-Image-Likeness [NIL] rights, and the thesis also aims to expose the cartel’s extortion of the teenagers’ education trust funds. Investigatory methods were research of relevant texts and broadcasts of scholarly and journalistic experts in economics, law, and sport and commerce, with examination of extensive statutory provisions and the common-law of the US and Canada in areas of anti-competition, labour rights/relations, contract law, constitutional law, class action procedures, and public law. Three field studies were completed for this thesis, in California (O’Bannon), Michigan (Northwestern), and Saskatchewan/Alberta to research CHL revenue. The thesis hypothesis was correct: the rule of law requires that the separation of powers’ three branches must all act to achieve justice. Judiciary and politicians failing, the executive branch must act. This thesis recommends a transnational Canada/US public inquiry addressing working children’s unique existence and helplessness, also addressing due process, accountability and transparency from dangerous ‘mock-amateur’ sport cartels.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".