Student Health and Well-Being in Indigenous Communities: “No One Is Healed Until Everyone Is Healed”
Bibliographic record
Abstract
In this interview, Maggie MacDonnell, recipient of the 2017 Global Teacher Prize, discusses how growing up near a First Nations reserve in Nova Scotia opened her eyes to inequalities between Indigenous and non-Indigenous peoples in Canada. She talks about the influence of Moses Coady, who instilled in her an appreciation for co-operative development, and T’hohahoken Michael Doxtater, an Indigenous scholar at McGill University, whose message, “No one is healed until everyone is healed,” she did not fully appreciate until she began working in the Inuit village of Salluit. She describes the life situation of the youth living in this kind of closed community where addiction and violence often become part of their everyday experience. Her interventions with this group of at-risk youth have helped decrease the school drop-out rate, improve students’ work and social skills, and raise awareness about suicide prevention. She concludes by giving advice to teachers who may be interested in working with students in remote communities.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.015 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.010 |
| 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".