Public Policy Trends: Unequal Burden: Learning from Canada's Responses to the Influenza Pandemic of 1918-20
Bibliographic record
Abstract
Analyzing Canada's responses to the 1918-20 influenza pandemic can offer insights into the current policy and social context of the coronavirus pandemic, while also helping to ensure we do not repeat past mistakes.In spring 1918, a novel influenza frequently called "Spanish Flu" arrived in Canada.Most authorities took little action because of its shared symptoms with seasonal influenza and its low mortality.However, six months later the influenza had mutated and its second-and most deadly-wave crashed down.Landing first in the Maritimes, Quebec, and Ontario via American travelers from New England and Canadian soldiers returning from Europe, influenza rapidly spread westward with railroad traffic to the Prairies and British Columbia.Of the estimated 50 million global deaths as a result of influenza, about 55 000 were Canadian (Fahrni & Jones 2012, 4).
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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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.034 | 0.012 |
| Scholarly communication | 0.018 | 0.012 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.014 | 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".