Teen pregnancy in Inuit communities – gaps still needed to be filled
Bibliographic record
Abstract
Teen pregnancy is depicted around the world as an important cause of health disparities both for the child and the mother. Accordingly, much effort has been invested in its prevention and led to its decline in the northern hemisphere since the mid-1990s. Despite that, high rates are still observed in the circumpolar regions. As Inuit communities have granted better understanding of teenage pregnancy a priority for the coming years, this article comprehensively reviews this multidimensional issue. By depicting current prevalence, likely determinants and possible impacts documented among Inuit of Canada, Alaska and Greenland, and contrasting them to common knowledge that has emerged from other populations over the years, great gaps surface. In some regions, the number of pregnancies per number of Inuit women aged between 15 and 19 years has increased since the turn of the millennium, while statistics from others are either absent or difficult to compare. Only few likely determinants of teenage pregnancy such as low education and some household factors have actually been recognized among Inuit populations. Documented impacts of early pregnancy on Inuit women and their children are also limited compared to those from other populations. As a way to better address early pregnancy in the circumpolar context, the defence for additional scientific efforts and the provision of culturally adapted sexual health prevention programmes appear critical.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".