Supporting Indigenous Graduate Student Health Research Capacity: Mentorship through a Provincial Health Research Network Environment in British Columbia,
Bibliographic record
Abstract
The British Columbia Network Environment for Indigenous Health Research (BC NEIHR), funded by the Canadian Institute of Health Research, is an Indigenous-led network that supports the research development and knowledge sharing of Indigenous communities, collectives and organizations and Indigenous graduate students in BC. To understand how we impacted the health research journey of Indigenous graduate students, we conducted a critical analysis of our annual evaluation reports and offer a reflective narrative of our operations. In this article, we share our Indigenous mentorship model and describe how we supported and enhanced Indigenous-led research among Indigenous graduate students in BC by: addressing common challenges related to financial costs of pursuing health research; prioritizing cultural and land-based learning opportunities; providing exceptional academic and professional development opportunities; and promoting Indigenous cultural safety, equity, and self-determination by creating systems-level change through partnerships. We conclude that as we work toward systems change, the BC NEIHR offers a promising approach towards enhancing Indigenous health research capacity through mentorship.
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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 | 0.027 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.001 | 0.004 |
| 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".