Measuring Employer‐Based Discrimination Versus Customer‐Based Discrimination: The Case of French Canadians in the National Hockey League
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
Abstract This paper examines alternative hypotheses as to why French Canadians are underrepresented on National Hockey League teams based in English Canada relative to their representation on teams based in the United States. Using panel data, the paper accounts for the idiosyncratic behavior of specific teams by using a fixed‐effects model. With these fixed‐effects accounted for, the paper tests the degree to which the representation of French Canadians on a team is related to that team's location—either in English Canada or the United States—versus the degree to which the representation is related to the ethnic origin of that team's coach and general manager. It finds the ethnic origin variables to be unable to explain the representational patterns, leaving the team location variable as the only significant explanatory variable. These statistical findings thus support a “customer discrimination” explanation of the underrepresentation, as opposed to an “employer discrimination” explanation. Identifying this source of any potential discrimination is important, since different sources will have different implications for the prospects of reducing such discrimination.
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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 | 0.002 | 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