A TROJAN HORSE: CAN INDIAN SELF-GOVERNMENT BE PROMOTED THROUGH THE INDIAN ACT?
Bibliographic record
Abstract
Section 90(1), first included in the Indian Act (“Act”) in its present form in 1951, deems “treaty” or “agreement” property to be situated on reserve. It is read together with sections 87 and 89 of the Act to exempt Indian property on reserve from taxation or attachment. Historically, all Indian property on reserve was broadly exempted from possible taxation or attachment. In McDiarmid Lumber Ltd v God’s Lake First Nation, the Supreme Court of Canada held that Parliament intended a narrow interpretation of section 90(1) such that only treaty-related property should be exempted in order to promote Indian self-government. I deconstruct the historical, social, and political events leading up to 1951 as depicted in Parliamentary records to demonstrate that the Court’s interpretation in McDiarmid is not supported by the record. I first argue that the promotion of Indian self-government cannot be achieved through the assimilation effect of the Act. Next, I argue that, because only half of the Indian population were treaty Indians in 1951, it was unlikely that Parliament would have contemplated only treaty Indians in making amendments to the Act. I conclude that McDiarmid-type decisions demonstrate dissonance in the Court’s interpretation of laws that impact Indigenous peoples. The consequence for Indigenous peoples is that the status quo remains.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.026 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".