Bibliographic record
Abstract
Background: Although previous unpublished research has demonstrated low breastfeeding rates among the James Bay Cree of Northern Ontario, the reasons for this are not immediately clear. Methods: A retrospective medical chart review of women who had given birth at the Weeneebayko General Hospital in Moose Factory, Ontario in the seven-year period 1997 to 2003 was performed. A variety of demographic variables were documented and overall breastfeeding initiation rates and yearly variations were assessed. Results: Univariate chi-square analysis of the data indicated that young maternal age (mean=23; p=0.001), maternal smoking (average rate=52.1%; p=0.03), living location (in a small coastal community; p=0.001); and low education status (not completing high school; p<0.001) were risk factors for a mother choosing not to breastfeed. Regression analysis revealed that only living in small coastal communities and not having post-secondary education were independently associated with not breastfeeding. Absence of a partner nearly reached statistical significance on regression analysis (p=0.056). The overall
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".