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Record W4407758840 · doi:10.7202/1115810ar

Le rôle du <i>job-crafting</i> dans la transition professionnelle vers une nouvelle identité religieuse : accompagner la réconciliation identitaire ?

2024· article· fr· W4407758840 on OpenAlexvenueno aff
Hugo Gaillard

Bibliographic record

VenueRelations industrielles · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsnot available
Fundersnot available
KeywordsConciliationHumanitiesSociologyPhilosophyMediationSocial science

Abstract

fetched live from OpenAlex

L’expression de l’identité religieuse au travail a longtemps été une thématique négligée, malgré un regain d’intérêt croissant. Cette recherche répond à l’appel d’une vision plus dynamique de l’objet pour comprendre comment les personnes concilient religiosité et professionnalité dans des contextes plus ou moins contraignants. Nous étudions le cas de travailleurs qui se convertissent à une nouvelle religion au cours de leur carrière. À travers une méthodologie qualitative et longitudinale, nous suivons 22 personnes converties à l’islam travaillant dans des entreprises françaises, à travers trois entretiens sur un an (66 entretiens). Les résultats montrent l’existence de plusieurs formes de job-crafting identitaire, qui conduisent à quatre grandes stratégies de réconciliation entre identité religieuse et identité professionnelle. La recherche établit un lien original entre les transitions identitaires, sur l’identité religieuse et sur le job-crafting .

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.010
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.045
GPT teacher head0.326
Teacher spread0.282 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

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Same venueRelations industriellesSame topicMulticulturalism, Politics, Migration, GenderFrench-language works237,207