The impact of the traditional land use and occupancy study on the Dene Tha' First Nation
Bibliographic record
Abstract
I Resume Laura MacKinnon laura@mackinnon.on.ca Monique M. Ross Research Associate Canadian Institute of Resources Law MFH 3330 University of Calgary Calgary, Alberta Canada, T2N 1N4 mmross@ucalgary.ca This paper is an assessment of the Traditional Land Use and Occupancy Study (TLUOS) on the Dene Tha' First Nation in northern Alberta. Impacts of the study include: Identification of and greater protection of traditional Dene Tha' sites; enhanced traditional cultural values and increased traditional land uses, improved communication with industry and government; all of which seemed to nurture a greater sense of community empowerment. These are positive impacts and they could be an important step in this First Nation achieving greater self-sufficiency. eet article evalue I'impact de l'Etude d'utilisation et d'occupation traditionnelle des terres sur la Premiere nation Dene Tha' dans Ie nord de l'Alberta. Les effets de cette etude incluent: I'identification et une plus grande protection des sites traditionnels des Dene Tha'; une mise en valeur des valeurs culturelles et des utilisations traditionalles des terres; de meilleures relations avec I'industrie et Ie gouvernement; Ie tout resultant dans un sentiment accru d'habilitation dans la communaute. En fin de compte, ces effets sont positifs et pourraient etre un premier pas vers une plus grande autarcie pour cette Premiere nation. The Canadian Journal of Native Studies XXII, 2(2002}:361-398. 362 Horvath I MacKinnon I Dickerson I Ross
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".