The second epidemiologic transition on the brink: What we can learn from the island of Newfoundland during the early 20th century
Bibliographic record
Abstract
OBJECTIVES: We aim to understand how the second epidemiologic transition unfolded on the island of Newfoundland during the early 20th century. The focus is on changes in predominant causes of mortality throughout this period, urban and rural differences, and comparisons with other Western nations. We explore factors driving these patterns including the economy, nutrition, sanitation, and access to healthcare and discuss their relevance to understanding epidemiologic transitions in other developing regions. METHODS: We examined official provincial death records (n = 65,394) and census materials from 1900 to 1939 for three rural districts (Burgeo-La Poile, Bonavista, and Twillingate) and the large city of St. John's. Life expectancies, infant mortality rates, survival curves, and proportionate mortality from communicable and non-communicable diseases (NCDs) were calculated. RESULTS: In all districts, old age mortality increased while infant and childhood mortality decreased, with corresponding increases in life expectancy. Proportionate mortality from communicable causes decreased while deaths from NCDs increased. These changes occurred earlier in urban St. John's than in outlying districts, suggesting rural-urban differences played a significant role in Newfoundland's second epidemiologic transition. However, the transition was significantly delayed relative to other Western nations. CONCLUSIONS: We suggest that observed mortality patterns were the result of complex interactions between the poor economy, malnutrition, high prevalence of tuberculosis, and limited health and social services. These factors contribute to the delayed onset of the second epidemiologic transition in Newfoundland relative to other Western nations and the earlier onset in St. John's than in rural 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".