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Record W4381513582 · doi:10.3917/gs1.170.0091

L’occultation de la violence sexuelle envers les personnes âgées

2023· article· fr· W4381513582 on OpenAlexaff
Adina Cismaru Inescu, Bastien Hahaut, Nicolas Berg, Stéphane Adam, Marie Beaulieu, Laurent Nisen

Bibliographic record

VenueGérontologie et société · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHumanitiesPolitical scienceVictimisationPoison controlArtSuicide preventionMedicineMedical emergency

Abstract

fetched live from OpenAlex

Cet article interroge le regard que portent nos sociétés sur les violences sexuelles subies par les personnes âgées, en explorant l’âgisme comme facteur qui peut expliquer la perception actuelle entourant la sexualité et les violences sexuelles envers elles. Bien que la violence sexuelle soit une thématique largement étudiée, sur le plan international, peu de recherches se concentrent sur les personnes âgées. Suivant les différentes perspectives et disciplines, leur prévalence à l’encontre des personnes âgées varie entre 0,9 et 15 %. À l’instar des populations plus jeunes, les personnes âgées ayant subi des violences sexuelles sont également plus à risques de subir une victimisation secondaire si elles ne sont pas crues lors de leur témoignage. La victimisation secondaire consiste à revivre le traumatisme par un événement lié ou non au traumatisme initial. Les professionnels de la santé ne sont pas formés pour accueillir, détecter et orienter leurs patients âgés, victimes de violences sexuelles. Cet article se termine en proposant quelques pistes de réflexion quant au modèle de société dans laquelle nous aimerions vivre et vieillir.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.063
GPT teacher head0.411
Teacher spread0.348 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2023
Admission routes1
Has abstractyes

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