Learning from Place: A Return to Traditional Mushkegowuk Ways of Knowing
Bibliographic record
Abstract
This paper details a research project dedicated to honouring Mushkegowuk Creeconcepts of land, environment and life in Fort Albany First Nation. Communityyouth interviewed local Elders to produce an audio documentary about therelations of the people to their traditional territory. These interactions evolved intoa 10-day river trip with youth, adult and elder participants traveling together ontheir traditional waters and lands learning about the meaning of paquataskamik,the Cree word used for traditional territory, all of the environment, nature, andeverything it contains. Bringing generations of community members together onthe land led to reclamation of culture and indigenous knowledge and built greatercommunity resistance to external forms of economic exploitation anddevelopment.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.030 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".