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Record W2106029318 · doi:10.1002/cjas.1240

Capacité d'apprentissage organisationnel : analyse théorique et étude empirique dans le contexte des équipes de projets d'aide publique au développement

2013· article· en· W2106029318 on OpenAlexvenueno aff
Ababacar Mbengue, Seydou Sané

Bibliographic record

VenueCanadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Learning and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsOperationalizationFormative assessmentAutonomyReflexivityDimension (graph theory)PsychologySociologyPolitical scienceEpistemologyPedagogySocial sciencePhilosophyLawMathematics

Abstract

fetched live from OpenAlex

Abstract Although several studies have investigated Organizational Learning Capability (OLC), the question of its operationalization remains open. We review the OLC concept, analyze its relationship to Organizational Learning (OL), and assess the validity of its operationalization through three models (formative, reflexive, mixed). While part of the literature states that OLC has five dimensions (experimentation, risk taking, dialogue, interaction with stakeholders, and participation in decision making), our exploratory study of 41 Official Development Aid projects suggests the existence of an important sixth dimension for OLC: autonomy vis‐à‐vis the national supervisor. The theoretical and practical implications of this finding are then discussed. Copyright © 2013 ASAC. Published by John Wiley & Sons, Ltd.

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)0.036
metaresearch head score (Gemma)0.106
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.106
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.006
Science and technology studies0.0020.010
Scholarly communication0.0120.010
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.100
GPT teacher head0.296
Teacher spread0.196 · 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 designObservational
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

Citations13
Published2013
Admission routes1
Has abstractyes

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