Using the probabilistic fertility table to test the statistical significance of fertility trends
Bibliographic record
Abstract
At below replacement level, fertility changes are subtle and complex; distinguishing statistically significant trends from random shifts is becoming a relevant issue. The probabilistic fertility table describes the uncertainty of the childbearing process, and provides a significance test for the annual changes of various fertility measures, which is essential for distinguishing a statistically significant change from a random fluctuation. This paper provides an analytical model for the total fertility of the probabilistic fertility table, and extends the significance test to period trends that include multiple annual changes. The extended significance test indicates that complex annual changes could accumulate to become a significant trend. Applying the analytical model and extended test to the total fertility of Canada, it indicates that the 2002–11 increase trend is statistically significant and, therefore, supports project future increases of total fertility.En-dessous du seuil de remplacement des générations, les changements à la fertilité sont subtils et complexes. Aussi, il est devenu pertinent de pouvoir distinguer les tendances significatives au plan statistique des écarts aléatoires. Le tableau probabiliste de fertilité décrit l’incertitude liée au processus de reproduction et fournit un critère de signification des changements annuels dans les diverses mesures de fertilité, élément essentiel pour distinguer un changement important au plan statistique des fluctuations aléatoires. Cet article fournit un modèle analytique pour l’ensemble du tableau probabiliste de fertilité et élargit la portée de cette mesure aux tendances dans le temps incluant les multiples changements annuels. Ce critère élargi indique que les changements complexes annuels peuvent représenter une tendance significative. En appliquant le modèle analytique et le critère au tableau de fertilité du Canada, on constate que la tendance à la hausse de 2002–11 est importante au plan statistique et, par conséquent, augure des hausses futures dans la fertilité totale.
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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 | 0.010 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".