Linking land displacement and environmental dispossession to <i>Mi'kmaw</i> health and well‐being: Culturally relevant place‐based interpretive frameworks matter
Bibliographic record
Abstract
For over five decades, Pictou Landing First Nation, a small Mi'kmaw community on the northern shore of Nova Scotia, has been told that the health of its community is not impacted by a pulp and paper mill pouring 85 million litres of effluent per day into a lagoon that was once a culturally significant place known as “A'se'k,” and which borders the community. Based on lived experience, the community knows otherwise. Despite countless government‐ and industry‐sponsored studies indicating the mill's pollutants are merely “nuisance” impacts and harmless, the community's concerns have not gone away. Using a “Piktukowaq” (Mi'kmaw) environmental health research framework to guide the interpretation of oral histories coming from the Knowledge Holders in Pictou Landing First Nation, we convey the deep, health‐enhancing relationship with A'se'k that the Piktukowaq enjoyed before it was destroyed, and the health suppression that has occurred since then. Conducting the research using a culturally relevant place‐based interpretive framework has demonstrated the absolute necessity of this kind of approach where Indigenous communities are concerned, particularly those facing health impacts vis‐à‐vis land displacement and environmental dispossession.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.042 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".