Strengthening Our Voices: Urban-dwelling Aboriginal people and research protocols
Bibliographic record
Abstract
The study of Indigenous peoples and their cultures has in the past raised serious ethical questions within the academic sphere as well as in the Aboriginal community. This paper examines culturally appropriate and sensitive research ethics within urban Aboriginal communities in Canada, through the lens of the research guideline of Ownership, Control, Access and Possession, and the more recent Utility, Self-Voicing, Access and Inter-relationality framework created by the Ontario Federation of Indigenous Friendship Centres. Ethically sound research by and for Aboriginal peoples continues to advance, and this paper's findings underscore the ability of urban Indigenous communities to create, gather and interpret their own data using frameworks that recognize their skill and autonomy.
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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 | 0.403 | 0.339 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.019 | 0.016 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.008 | 0.013 |
| Research integrity | 0.007 | 0.015 |
| Insufficient payload (model declined to judge) | 0.026 | 0.011 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".