Shifting paradigm from biomedical to decolonised methods in Inuit public health research in Canada: a scoping review
Bibliographic record
Abstract
BACKGROUND: The National Inuit Strategy on Research focuses on advancing Inuit governance in research, increasing ownership over data and building capacity. Responding to this call for Inuit self-determination in research, academic researchers should consider cultural safety in research and ways to promote Inuit-led methods. METHODS: This scoping review collated academic literature on public health research in Inuit communities in Canada between 2010 and 2022. A critical assessment of methods used in public health research in Inuit communities examined cultural safety and the use of Inuit-attuned methods. Descriptive and analytical data were summarised in tables and figures. Knowledge user engagement in the research process was analysed with thematic analysis. RESULTS: 356 articles met the inclusion criteria. Much of the published research was in nutrition and mental health, and few initiatives reported translation into promotion programmes. Almost all published research was disease or deficit focused and based on a biomedical paradigm, especially in toxicology, maternal health and chronic diseases. Recent years saw an increased number of participatory studies using a decolonial lens and focusing on resilience. While some qualitative research referred to Inuit methodologies and engaged communities in the research process, most quantitative research was not culturally safe. Overall, community engagement remained in early stages of co-designing research protocols and interventions. Discussion on governance and data ownership was limited. Recent years saw emerging discussions on these issues. Knowledge user capacity-building was limited to brief training on conventional data collection methods. CONCLUSIONS: The last decade of published public health research has not responded to the National Inuit Strategy on Research. Participatory research is gaining ground, but has not reached its full potential. A shift from biomedical to decolonised methods is slowly taking place, and public health researchers who have not yet embraced this paradigm shift should do so.
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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 | 0.121 | 0.265 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.036 | 0.058 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.020 | 0.010 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".