PILIRIQATIGIINNIQ ‘Working in a collaborative way for the common good’
Bibliographic record
Abstract
Increasing attention on the Arctic has led to an increase in research in this area. Health research in Arctic Indigenous communities is also increasing as part of this movement. A growing segment of the research community is focused on explaining and understanding Indigenous knowledge and ways of knowing. Researchers have become increasingly aware that Indigenous knowledge must be perceived, collected and shared in ways that are unique to, and shaped by, the communities and individuals from which this knowledge is gathered. This paper adds to this body of literature to provide Inuit perspectives on health-related research epistemologies and methodologies, with the intent that it may inform health researchers with an interest in Arctic health. The Inuit concepts of inuuqatigiittiarniq (“being respectful of all people”), unikkaaqatigiinniq (story-telling), pittiarniq (“being kind and good”), and iqqaumaqatigiinniq (“all things coming into one”) and piliriqatigiinniq (“working together for the common good”) are woven into a responsive community health research model grounded in Inuit ways of knowing which is shared and discussed.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".