"Just get on with it." Linking data systems to report on infant mortality and the First Nations population in Manitoba (Canada)
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 routine reporting of actionable statistics to improve system performance and prevent premature mortality has been promoted for decades. A key statistic produced nationally and globally is infant mortality. State governments define, collect and report vital events. In Canada, vital statistics is a provincial responsibility. The provinces, however, do not uniformly collect vital events for First Nations who are under Federal fiduciary responsibility or uniformly maintain a registration group field for disaggregation purposes. In 2008, Canada's Public Health Agency conceded that a lack of a First Nations identifier has obscured any understanding of First Nations perinatal health. Given these drivers of variability and the complex multi-jurisdictional vital statistics environments in which they occur, this paper demonstrates, using data linkage methods, a way to improve the estimation of infant mortality for the First Nations population in Manitoba, Canada. The method improved estimation, and demonstrated a persistent gap in infant mortality.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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