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Record W4406633449 · doi:10.7202/1115416ar

Le leadership dans les organisations scolaires : une pragmatique de la rencontre

2024· article· fr· W4406633449 on OpenAlexvenueno aff
Christophe Mauny

Bibliographic record

VenueÉducation et francophonie · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceSociology

Abstract

fetched live from OpenAlex

Agir sur l’individu est complexe; agir sur le collectif l’est plus encore. Comment, dès lors, assurer un acte productif collectif ? L’article pose le concept de rencontre comme un analyseur heuristique du processus de leadership. En effet, maîtriser les déterminants structurels et fonctionnels de l’organisation scolaire est nécessaire, mais non suffisant pour être reconnu leader. Le leadership se caractérise moins par les attributs de la fonction (ce qu’on lui reconnaît) que par l’activité du leader (ce qu’il fait). En appui à une approche pragmatique, la rencontre est un construit du leadership pour conjuguer la cohérence et la convergence de la guidance du collectif pour garantir la stabilité et la transformation des organisations. Notre proposition explorera trois entrées réflexives que sont : i) Créer les proximités, c’est rendre la rencontre possible par la mobilisation des énergies au confluent des proximités géographique, cognitive, sociale, organisationnelle et institutionnelle; ii) Créer les synergies pour faire vivre la rencontre, c’est conjuguer trois actes : conventionner pour s’accorder, réguler les engagements et reconnaître la qualité du travail accompli; et iii) Structurer l’autonomie collective pour pérenniser la rencontre articule distributivité décisionnelle, engagement évaluatif et formation des personnels.

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)0.018
metaresearch head score (Gemma)0.015
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 score0.018
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0080.043
Scholarly communication0.0170.017
Open science0.0030.008
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0050.001

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 head0.147
GPT teacher head0.426
Teacher spread0.279 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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