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Record W2586997284 · doi:10.7202/1033855ar

Secondes amours. Aimer la raison ?

2015· article· fr· W2586997284 on OpenAlexvenueno aff
Didier Le Gall

Bibliographic record

VenueInternational Review of Community Development · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical science

Abstract

fetched live from OpenAlex

La sociologie a-t-elle quelque chose à dire de l’amour ? Sans doute pas si l’on s’en tient à l’adage bien connu : le coeur a ses raisons que la raison ne connaît pas. En revanche, si nous considérons que les rapports affectifs sont une des dimensions des rapports sociaux, l’amour est alors susceptible de devenir l’objet d’une analyse sociologique. Partant de cette perspective, l’auteur se propose ici d’analyser les rapports affectifs à l’oeuvre sur le « second marché matrimonial », où ne se confrontent plus seulement des célibataires sans enfants. Prenant appui sur le matériau recueilli dans le cadre de deux recherches récentes, il défend la thèse selon laquelle ces rapports se particularisent car ils doivent s’inscrire dans des rôles non clairement définis et se déployer dans un cadre non strictement conjugal : l’un des deux partenaires au moins est déjà parent. De ce fait, si le couple ne nie pas la spécificité de l’union qu’il va former, il est alors rapidement confronté, faute de supports institués, à la nécessité de promouvoir un minimum de régulation, bref de s’ajuster; ce phénomène aurait pour conséquence directe de tempérer l’exubérance de la passion amoureuse. Paradoxe s’il en est, en favorisant l’instabilité conjugale, l’exaltation amoureuse conduirait à expérimenter une certaine sagesse de l’amour.

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)0.004
metaresearch head score (Gemma)0.009
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: none
Teacher disagreement score0.030
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0090.011
Scholarly communication0.0100.009
Open science0.0010.007
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0300.010

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 head0.145
GPT teacher head0.372
Teacher spread0.228 · 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

Citations6
Published2015
Admission routes1
Has abstractyes

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