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Record W2092806692 · doi:10.3917/riges.314.0216

Prévenir les conflits liés à la diversité : l'interculturel comme pratique de gestion

2006· article· fr· W2092806692 on OpenAlexaffvenueabout
Sébastien Arcand

Bibliographic record

VenueGestion · 2006
Typearticle
Languagefr
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Résumé L’accroissement de la diversité ethnoculturelle au sein de la société québécoise entraîne des défis particuliers pour les organisations. Que ce soit aux différents paliers de gouvernement, dans les institutions scolaires, les P.M.E. ou les grandes entreprises, la question de la diversité pose en termes clairs les rapports parfois conflictuels qu’entretiennent les différents acteurs sociaux. Les gestionnaires d’organisations publiques, parapubliques et privées font face à de nouvelles dynamiques qui les forcent à revoir les modèles de gestion à partir desquels ils structurent leur environnement de travail. Dans ce contexte, et en considérant le nombre croissant de demandes venant de groupes divers pour obtenir des dérogations ou certains privilèges, la gestion interculturelle devient de plus en plus une solution viable à l’atténuation des conflits potentiels. En revoyant certaines prémisses sur lesquelles se fonde la gestion interculturelle, nous explorons dans cet article les possibilités et les limites de l’interculturel dans le contexte québécois. À cet égard, nous postulons que, pour être efficace, la gestion interculturelle ne peut se borner à sa dimension culturelle; elle doit être intégrée à un ensemble de pratiques de gestion englobant diverses facettes des organisations.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.419
Threshold uncertainty score0.834

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.033
Scholarly communication0.0100.004
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.099
GPT teacher head0.365
Teacher spread0.266 · 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

Citations8
Published2006
Admission routes3
Has abstractyes

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