MétaCan
Menu
Back to cohort
Record W1496986533 · doi:10.3917/rai.049.0055

Parler de sexe sans rougir

2013· article· fr· W1496986533 on OpenAlexaff
Marguerite van den Berg, Jan Willem Duyvendak, Alexandre Jaunait, Élisabeth Marteu

Bibliographic record

VenueRaisons politiques · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsCentre Intégré de Santé et Services Sociaux de Chaudière-Appalache
Fundersnot available
KeywordsHumanitiesArtSexual behaviorEthnologySociologyPsychology

Abstract

fetched live from OpenAlex

Résumé De nombreuses discussions sur les valeurs et les idéaux néerlandais portent aujourd'hui sur le sexe et la sexualité. Dans l'« approche globale » de la santé sexuelle aujourd'hui développée aux Pays-Bas, les parents et le travail parental jouent un rôle important. Cet article propose une analyse du matériau ethnographique et du contenu des supports pédagogiques développés pour le cours « Grandir dans l'amour » conçu pour former les parents à l'éducation sexuelle de leurs enfants dans les zones urbaines défavorisées. Dans ces cours, parler ouvertement de sexualité n'est pas seulement présenté comme étant « normal », mais également comme étant typiquement « néerlandais », ce qui contribue à la formation d'un nationalisme sexuel particulier. De ce mélange entre ce qui est « normal » et ce qui est « néerlandais » résulte une présentation des anomalies sexuelles comme étant d'ordre culturel et ce faisant, ressortissant de l'Autre culturel.

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)0.001
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 score0.019
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.001

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 head0.159
GPT teacher head0.434
Teacher spread0.274 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueRaisons politiquesSame topicMulticulturalism, Politics, Migration, GenderFrench-language works237,207