MétaCan
Menu
Back to cohort
Record W1589171601 · doi:10.7202/005062ar

Les nouveaux visages du vieillissement de la population française

2002· article· fr· W1589171601 on OpenAlexvenueno aff
Patrice Bourdelais

Bibliographic record

VenueLien social et Politiques · 2002
Typearticle
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Les démographes français ont inventé la notion de vieillissement de la population dans un contexte politique et culturel particulier. Les connotations de cette notion sont si pernicieuses qu'elles pèsent jusqu'à nos jours sur notre perception de l'âge de la vieillesse. Or les changements survenus dans cet âge rendent non pertinente toute analyse du vieillissement démographique fondée sur un seuil d'âge immuable. Au cours des trente dernières années, la santé des sexagénaires, leur place dans la succession des générations, leurs capacités économiques et leur rôle social ont changé. Il convient d'en tenir compte dans l'étude de l'évolution des structures par âge, d'éviter que la catégorie statistique définisse la réalité humaine qu'elle était censée contribuer à décrire. La mise au point d'un seuil d'âge évolutif d'entrée dans la vieillesse permet de montrer que le vieillissement de la population observé traditionnellement n'est qu'une apparence, sans consistance sociale. En revanche, les progrès réalisés depuis trente ans quant à la mortalité après 35 ans ont accentué les disparités sociales et amplifié des représentations divergentes de l'âge de la retraite.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.690
Threshold uncertainty score0.625

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.040
GPT teacher head0.402
Teacher spread0.362 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueLien social et PolitiquesSame topicAging, Elder Care, and Social IssuesFrench-language works237,207