How political change paved the way for Indigenous knowledge: The Mackenzie Valley Resource Management Act 2007
Bibliographic record
Abstract
ABSTRACT. This paper highlights the process of political change that led to the Mackenzie Valley Resource Management Act (MVRMA), an attempt to recognize the legitimacy of indigenous knowledge in resource management. Evidence from ethnographic interviews shows the importance of involving indigenous knowledge holders in local land and resource management decisions, which are grounded in land-claim settlement processes. However, the authority of the Indian and Northern Affairs Canada minister acts as a barrier to genuine involvement of indigenous knowledge and its holders in resource management. True capacity building in the Northwest Territories cannot succeed without devolution of power from the federal government to territorial and First Nations governments. Key words: indigenous knowledge, resource management, post-colonialism, land claims RÉSUMÉ. Cet article porte sur le changement d’ordre politique qui a donné lieu à la Loi sur la gestion des ressources de la vallée du Mackenzie (LGRVM) visant la reconnaissance de la légitimité des connaissances indigènes en matière de gestion des ressources. Des éléments probants découlant d’entrevues ethnographiques attestent de l’importance de faire appel aux indigènes possédant des connaissances en ce qui a trait aux décisions relatives aux terres régionales et à la gestion des ressources qui sont enracinées dans les processus de règlement des revendications territoriales. Cependant, l’autorité du ministre des Affaires indiennes et du Nord canadien constitue un obstacle à la possibilité de faire véritablement appel aux connaissances indigènes et aux personnes possédant ces connaissances en matière de gestion des ressources. Dans les Territoires du Nord-Ouest, l’habilitation
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| 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".