Bibliographic record
Abstract
@font-face { font-family: "Cambria Math"; }@font-face { font-family: "Calibri"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoNoSpacing, li.MsoNoSpacing, div.MsoNoSpacing { margin: 0cm 0cm 0.0001pt; font-size: 11pt; font-family: Cambria; }.MsoChpDefault { font-family: Cambria; }div.WordSection1 { page: WordSection1; }\nABSTRACT\nFew epidemics have been documented in the context of historical Quebec. The rich epidemiological and demographic data contained in the Registre de population du Québec ancien makes it possible to conduct detailed analyses of historical epidemics and can be beneficial to filling in gaps in modern knowledge. The historical studies of measles have a distinct advantage over modern ones, in that epidemics can be analyzed in a natural state unhindered by modern medical treatment and vaccine campaigns. This dissertation attempts to fill this knowledge gap of infectious diseases through the development of methods to analyze epidemics in the absence of cause of death records. The results show the suitability of these methods to investigate the 1714-15 measles epidemic and its impact on the children in the population.\nThe first study examined the general dynamics of the epidemic that provisioned the baseline for the subsequent studies. Measles entry to the Montreal area was from Colonial America circa late-March of 1714. The epidemic spread eastwards to most other parts of the colony by late-August of the same year and disappeared early in 1715. Measles was virulent with an estimated death rate of 52.8 per thousand for children under age 15. Infants and toddlers were the main victims, while females were slightly more likely than males to have died from the virus. Although the epidemic originated in the Western parishes, severity finally turned out to be higher in the Eastern parishes of the colony.\nThe second study identified several measles-specific risk factors among children under age 5 were identified with case/control comparisons, which revealed that the effects of these factors were only significant and intensified during the acute phase of the epidemic. Contrary to what was reported in modern studies, singletons or children with fewer siblings had higher odds of dying than children in larger sibships. The age difference between siblings appeared to be a more important predictor of death than the size of the sibship, as a larger average difference led to an increased likelihood of death. As well, children with a sibling who died during the epidemic and children with immigrant parents were at higher risk.\nIn the third study, exposed children who survived the acute episode of the epidemic were followed for 25 months past the estimated date of infection. It was found that children exposed before age 3 had higher long-term mortality than the unexposed children. The difference remained significant while assessing the effects of the demographic and sibship risk factors. For the exposed cohort, the risk of death also varied by age and sex. Only females exposed during infancy had a significantly higher risk of dying, while both exposed male and female toddlers had higher mortality during the follow-up period. In this case, the effect was slightly stronger for males. No significant long-term mortality difference was found among children exposed between 36 and 59 months of age.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".