Eating in the oil sands: Sâkawiyiniwak(Northern Bush Cree) experiences with wild food contamination in Alberta's oil sands
Bibliographic record
Abstract
Cette dissertation est un travail de recherche des expériences des sakâwiyiniwak (les cris des bois du nord) avec la contamination des plantes sauvages comestibles dans la région des sables bitumineux de l'Alberta. Cette étude est basé sur les expériences ethnographiques des membres de la Nation Crie de Bigstone et de la Première Nation de Fort McKay et leurs territoires traditionnels dans la région du Traité numéro huit. Ceci a pris lieu sur ce terrain lors d'études de surveillance environnementale communautaire sur la contamination des plantes sauvages comestibles. Tout d'abord, je présente un examen approfondi des «diagnostiques» et des «étiologies» implicites dans la connaissance écologique sakâwiyiniwak de la contamination de l'environnement en particulier, et des critères sakâwiyiniwak pour la qualité de la nourriture en général. Deuxièmement, je considère cette recherche ethnoécologique du point de vue de la théorie culturelle liée aux notions de «pollution» et de «risque», ainsi que la compréhension politique écologique des relations de pouvoir auxquelles les savoirs autochtones sont soumis dans des évaluations politiques publiques et la gestion des polluants.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".