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Record W2093563774 · doi:10.7202/1018231ar

Les aîné-es trans : une population émergente ayant des besoins spécifiques en soins de santé, en services sociaux et en soins liés au vieillissement

2013· article· fr· W2093563774 on OpenAlexaffvenue
Billy Hébert, Line Chamberland, Mickael Chacha Enriquez

Bibliographic record

VenueFrontières · 2013
Typearticle
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Les aîné-es trans sont une population en devenir constituée d’individus aux identités, réalités et trajectoires très diversifiées. Cet article basé sur une recension des écrits, présente tout d’abord cette diversité, notamment en ce qui a trait à l’âge, tant à l’appartenance générationnelle qu’à l’âge du début de la transition. On y traite ensuite de la santé physique des aîné-es trans, soit des problèmes et des besoins de santé qui leur sont propres, puis des barrières auxquelles ils et elles se heurtent dans leurs démarches pour avoir accès à des soins et des services de santé adéquats. Le texte relève certaines difficultés comme l’isolement et le manque de soutien qui sont souvent le lot des aînés trans ainsi que les obstacles dans leur accès aux services sociaux et aux soins liés au vieillissement. L’article propose des pistes d’action pour les personnes professionnelles dans le domaine de la santé et des services sociaux et se conclut sur des pistes de recherche.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.003
Scholarly communication0.0040.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.047
GPT teacher head0.403
Teacher spread0.356 · 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 designNot applicable
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

Citations14
Published2013
Admission routes2
Has abstractyes

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Same venueFrontièresSame topicAging, Elder Care, and Social IssuesFrench-language works237,207