Rethinking the objectives of a pan-Canadian immunization information system
Bibliographic record
Abstract
Emerging from the pandemic and the largest mass vaccination campaign in history, governments at all levels are once again calling for the development of comprehensive vaccination registries. Yet these calls have persisted for decades at the federal level, and little progress has been made. At the heart of the challenge is the need to clarify the objectives of federal vaccine data collection and how these objectives dovetail with the federal government's constitutional role and jurisdiction in public health. We suggest that pan-Canadian immunization information collection initially focus on vaccine safety and effectiveness, as these would be most concordant with provincial/territorial aims and would fall under the federal government's jurisdiction. The federal spending power could be utilized to further support provincial/territorial systems to facilitate pan-Canadian data collection for coverage.
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 | 0.190 | 0.204 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.018 | 0.019 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.031 | 0.015 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".