Constitutional silence, section 36, and public services on Indian reserves
Bibliographic record
Abstract
Canada’s belated legal reckoning with unequal public services on Indian reserves is only beginning. This article proceeds in two main parts. First, I address a puzzle: even though the problem of deficient services on reserves endured for decades – and, in many respects, endures still – Canadian courts have hardly addressed its constitutionality. This constitutional silence can appear surprising, even astonishing. Second, I suggest that the curiously neglected section 36 of the Constitution Act, 1982, which calls for ‘reasonably comparable services’ and ‘essential public services of reasonable quality to all Canadians,’ should inform the constitutional conversation about unequal services on reserves. The exclusion of reserves from equalization, a principle enshrined in section 36, is a largely-overlooked legal omission that has enabled the problem to fester. Conceiving of section 36's components as ‘directive principles’ – neither enforceable fundamental rights nor empty political aspirations – helps unlock new possibilities for judicial and political use, particularly in light of the treatment of directive principles in other countries. The language of section 36 has never been explicitly used by a Canadian judge as an interpretive aid. This should change.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.030 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".