The effect of universal influenza immunization on vaccination rates in Ontario.
Bibliographic record
Abstract
OBJECTIVES: This article examines the association between introduction of Ontario's Universal Influenza Immunization Program and changes in vaccination rates over time in Ontario, compared with the other provinces combined. DATA SOURCES: The data are from the 1996/97 National Population Health Survey and the 2000/01 and 2003 Canadian Community Health Survey, both conducted by Statistics Canada. ANALYTICAL TECHNIQUES: Cross-tabulations were used to estimate vaccination rates for the total population aged 12 or older, for groups especially vulnerable to the effects of influenza, and by selected socio-demographic variables. Z tests and multiple logistic regression were used to examine differences between estimates. MAIN RESULTS: Between 1996/97 and 2000/01, the increase in the overall vaccination rate in Ontario was 10 percentage points greater than the increase in the other provinces combined. Increases in Ontario were particularly pronounced among people who were: younger than 65, more educated, and had a higher household income. Between 2000/01 and 2003, vaccination rates were stable in Ontario, while rates continued to rise in the other provinces. Even so, Ontario's 2003 rates exceeded those in the other provinces.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".