Stabilité des estimations de l’espérance de vie sans perte d’autonomie calculées au moyen de deux méthodes de construction de tables de survie
Bibliographic record
Abstract
Cet article aborde empiriquement la question de la stabilité relative, sur deux intervalles de temps, des estimations de l'espérance de vie sans pêne d'autonomie obtenues par la méthode de Sullivan et par la méthode des tables de survie multi-états. Les données analysées ont été obtenues à partir de trois vagues de la LSOA (Longitudinal Study of Aging), enquête dont l'échantillon est représentatif de la population hors-institution de 70 ans et plus. Les estimations calculées par la méthode de Sullivan sont plus stables que celles qui sont fournies par la méthode des tables de survis multi-états car les séries de taux d'incidence sont moins stables que les séries de taux de prévalence. De plus, les profils de mortalité pour la population en perte d'autonomie, utilisés uniquement pour les tables de survie multi-états, semblent particulièrement influencés par l'instabilité, les changements de composition de l'échantillon et les sorties d'observation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".