OBSTACLES TO CROSSING THE DISCRIMINATION THRESHOLD: CONNECTING INDIVIDUAL EXCLUSION TO GROUP-BASED INEQUALITIES
Bibliographic record
Abstract
In two important unanimous judgments, Quebec (Commission des droits de la personne et des droits de la jeunesse) v Bombardier Inc (Bombardier Aerospace Training Centre) and Kahkewistahaw First Nation v Taypotat, the Supreme Court of Canada concluded that there was insufficient evidence of discrimination. Consequently, it dismissed both claims without requiring that the defendants justify the allegedly exclusionary criteria being challenged. While these cases arose in very different factual and legal contexts, there are troubling common threads that tie them together. Most poignantly, in both cases, the plaintiffs do not succeed in proving what is often referred to as a prima facie case of discrimination, and the predominant justification for this failure is the inadequacy of the evidence. These cases, therefore, provide an important starting point for thinking about how to prove discrimination. They raise questions regarding the use of the terminology “prima facie discrimination”, the role of factual inferences in statutory or constitutional discrimination analysis and the significance of broader evidence about social context in individual discrimination cases. Finally, they remind us that how plaintiffs lose matters. The fact that the Court did not get beyond the preliminary finding of prima facie discrimination stands in stark contrast to many anti-discrimination cases where the heart of the dispute revolves around the adequacy of the justification for the challenged exclusionary criteria.
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.
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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.057 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".