Bibliographic record
Abstract
Inuit infants throughout the Arctic experience higher mortality and poorer health than their non-Inuit counterparts, and suffer disproportionately from bacterial and viral infections. This research initially reviews the health status of these infants, with a focus on Canadian Inuit communities and reference to other circumpolar regions, as appropriate. It also discusses the wide range of inter-related factors that affect their health and their susceptibility to infection: their demographic, social, economic and physical environment, as well as personal health practices and the availability of high quality, culturally-appropriate health services within their communities. Data were then analyzed from a cohort study of 46 healthy Inuit infants that had been previously conducted in Iqaluit, Nunavut from December 1995 to November 1997. Hospitalization and morbidity patterns were examined over their first year of life. Infants experienced an average of four respiratory tract infections (RTIs) annually, which accounted for half of the hospitalizations in the cohort. Some interesting trends were evident from assessment of risk factors for hospitalization and infections using multiple linear regression. Infants of mothers with higher educational attainment spent six fewer days in hospital per year (95% CI: -14.6, 2.9), after adjustment for confounding variables. Adoption appeared to have adverse health effects in addition to those that would be expected due to lack of breastfeeding alone; among infants who were not breast-fed, adopted infants had three more RTIs per year than non-adopted infants (95% CI: 0.5, 5.1). These results provide support for undertaking larger epidemiological studies in order to clarify the role of these risk factors, so that future preventive efforts can be informed and effective.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".