Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Arctic regions are inhabited by diverse populations, both indigenous and non-indigenous. Health Transitions in Arctic Populations describes and explains changing health patterns in these areas, how particular patterns came about, and what can be done to improve the health of Arctic peoples. This study correlates changes in health status with major environmental, social, economic, and political changes in the Arctic. T. Kue Young and Peter Bjerregaard seek commonalities in the experiences of different peoples while recognizing their considerable diversity. They focus on five Arctic regions - Greenland, Northern Canada, Alaska, Arctic Russia, and Northern Fennoscandia, offering a general overview of the geography, history, economy, population characteristics, health status, and health services of each. The discussion moves on to specific indigenous populations (Inuit, Dene, and Sami), major health determinants and outcomes, and, finally, an integrative examination of what can be done to improve the health of circumpolar peoples. Health Transitions in Arctic Populations offers both an examination of key health issues in the north and a vision for the future of Arctic inhabitants.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it