The Linkage of Microcensus Data and Vital Records: an Assessment of Results on Quebec Historical Population Data (1852–1911)
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 interconnection between civil records and census data, along with linkage across censuses, can substantially broaden and enrich the avenues of research in both the social and the biological sciences. Here we present a linkage program developed to match nominative microdata from the Canadian censuses to those from Quebec civil records. We provide a critical assessment of linkage results obtained on two geographical settings by investigating household and individual characteristics that could impact on linkage rates and raise bias issues. The linkage program is at the heart of the construction of the Integrated Infrastructure of the Quebec Population Historical Microdata which will integrate available historical microdata (vital records and census data) on the Quebec population dating back to the beginning of European settlement.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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