The District of Sechelt, British Columbia and the Municipal System of Aboriginal Self-Government
Bibliographic record
Abstract
The purpose of this paper was, in exploring the details of the Sechelt Indian Band Self-Government Act and the powers it entails, to ascertain whether or not the Municipal Model represents a viable and successful option toward Aboriginal self-government. In this paper I examined the extent to which certain key provisions of the Sechelt Act align with the traditional goals of Aboriginal self-government to gauge its usefulness to Aboriginal groups. I performed this by first exploring the concept of Right and Title, its implications and the resulting powers which self-governing bands must possess to satisfy the provisions of Right and Title. I then used these criteria to establish a basic ‘report card’ against which the Municipal Model’s efficacy can be gauged through comparison with the provisions of the Sechelt Act. I found that not only does the Sechelt Act satisfy all vital criteria for an effective selfgovernment agreement, but that the Municipal Model name is itself a misnomer for a far wider package of rights and responsibilities than those given to municipalities. I conclude that the Sechelt Indian Band Self- Government Act is a highly effective iteration of the Municipal Model, contrary to criticism, and that the model’s success merits consideration as a viable Aboriginal self-government solution for future cases.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".