Still Thriving: A Case Illustrating How COVID-19 Affected Indigenous Health and Wellness
Bibliographic record
Abstract
The myriad of social, financial, material health, and educational inequities that continue to plague Indigenous communities was exacerbated by COVID-19. In order to place on spotlight on them, this case follows Star, an Indigenous Student Success Coordinator, as she navigated the policies and practices couched in the rhetoric of supporting the success, health and wellness of students and families during a global pandemic. The case and teaching notes that follow illustrate the limitations that Westernized models of health and wellness create for Indigenous and non-Indigenous educators when it comes to maintaining their students’ and own well-being. As an alternative to the dominant Westernized models, the teaching notes offer a more holistic and integrated model of Indigenous health and wellness. The elements of the model situate health and wellness as encompassing all aspects of an individual’s life by connecting them relationally to their families and communities, nations, and the land.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".