Collaborative approaches to wellness and health equity in the Circumpolar North: Introduction to the Special Issue
Bibliographic record
Abstract
This special issue brings together a series of papers that were presented at the Northern, Rural, and Remote Health Conference in Labrador, Canada. In this collection, scholars and community leaders use local examples to explore some of the most pressing issues in Circumpolar health: Indigenous self-determination in health care and health research; access to traditional medicines; language and identity; youth engagement; mental health; climate change; and health technology. Recognizing the dynamic ways that these topics were raised at the conference, we've included a diverse slate of papers: from commentary essays and case studies, to primary research and evidence synthesis. The goal of this special issue is to bridge local insights, innovations, and varied forms of evidence from the Circumpolar North, with global conversations about health equity, health system transformation, and the rights of Indigenous peoples. This editorial provides an overview of the conference and an introduction to the scholarship that emerged from it.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.015 |
| Insufficient payload (model declined to judge) | 0.008 | 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".