Epidemic cycles and environmental pressure in colonial Quebec
Bibliographic record
Abstract
OBJECTIVES: Research on historical populations in Europe finds that infectious disease epidemics appear to induce predictable cycles in age-specific mortality. We know little, however, about whether such cycles also occurred in less dense founder populations of North America. We used high-quality data on the Quebecois population from 1680 to 1798 to examine the extent to which age-specific mortality showed predictable epidemic cycles. We further examined whether environmental pressures-temperature, lack of precipitation, or crop failure-may have set the stage for the emergence of epidemics. METHODS: We applied autoregressive, integrated, moving average time series methods to annual counts of period mortality for the following age groups: < 1 year, 1 to < 5 years, 5 to < 15 years, 15 to < 50 years, and 50 years and above. These methods controlled for other patterns (e.g., trend) before empirically identifying cycles. RESULTS: Results indicate a strong seven-year cycle in mortality among infants and children under seven years of age. Warm temperatures (across Quebec overall) and relatively dry years (in Eastern Quebec) also predicted an increased risk of mortality in infancy and childhood, although these environmental variables appear to act independently of the epidemic cycle pattern. DISCUSSION: Findings indicate a strong seven-year epidemic cycle in historical Quebec which afflicted naïve birth cohorts not previously exposed to the prior epidemic. We contend that smallpox epidemics likely contributed to this cycle. The seven-year cycle occurred only in the latter half of the test period (post 1740) with increasing size of the colony and population concentration in urban areas.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".