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Record W1590775914 · doi:10.1080/07053436.2015.1040638

La voie associative génératrice de lien social : le cas de la France

2015· article· fr· W1590775914 on OpenAlexvenueno aff
Jean-Michel Peter, Roger Sue

Bibliographic record

VenueLoisir et Société / Society and Leisure · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Aujourd’hui, le modèle républicain français, socle de sa cohésion identitaire et sociale, semble à la croisée des chemins. Il doit se réinventer pour répondre aux enjeux d’une société complexe et plurielle. Dans ce contexte, quelle peut être la contribution des associations au renouveau d’une société plus démocratique? Le projet de cet article est d’apporter des éléments de réponse. Premièrement, avec une analyse prospective des grandes tendances qui sous-tendent les relations entre les citoyens. Deuxièmement, dans une observation plus fine des transformations de l’engagement bénévole, il s’agit de montrer le renouveau des modalités d’un engagement dans la vie de la Cité. Les résultats de deux enquêtes récentes dévoilent comment les intérêts d’être bénévole oscillent entre un individu relationnel réclamant plus d’autonomie et le respect de la gestion de son temps libre, et la création de liens sociaux porteurs de solidarité. En tout état de cause, le principe d’association entre les hommes procède d’une modernité à l’œuvre.

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)0.005
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 score0.109
Threshold uncertainty score0.217

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0090.014
Scholarly communication0.0080.004
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.027
GPT teacher head0.347
Teacher spread0.321 · 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
Published2015
Admission routes1
Has abstractyes

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