A Kick in the Caboose: Recovering the Judicial Horizontality of Constitutional Equality Rights
Bibliographic record
Abstract
The peculiarity I examine in this paper is that the judiciary’s involvement in the horizontality of equality has little to do with modifying the common law applicable to private parties to create antidiscrimination duties. Rather, it is restricted to following behind legislative efforts to protect citizens from discrimination perpetrated by other citizens. Courts opt to interpret section 15 as in certain circumstances prohibiting legislatures from not going far enough to cover the “residual category” of horizontal private relations left untouched by an antidiscrimination statute, an approach that has been fittingly referred to as “caboose constitutionalism.” I argue that we Canadians should reject this approach — that we should kick the caboose. I sketch a theoretical blueprint for how to do this, and I make suggestions about how to operationalize this blueprint in practice.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.006 | 0.044 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".