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Méthodes de recherche en management

2014· book-chapter· fr· W3024447934 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDunod eBooks · 2014
Typebook-chapter
Languagefr
FieldSocial Sciences
TopicData Analysis and Archiving
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Ce chapitre présente d’abord la collecte des données primaires. À ce titre, il décrit les techniques utilisables en recherche quantitative : questionnaire, observation et méthode expérimentale. Il expose ensuite les outils de collecte de la recherche qualitative : entretien individuel, entretien de groupe, observation participante et non participante. Il analyse alors la gestion des sources de données, en termes d’accès, de flexibilité du chercheur, de risques de contamination et de perte du chantier de recherche. Le chapitre recense quelques stratégies d’approche et de gestion des sources fondées sur le formalisme de la relation entre le chercheur et les individus-sources de données, sur le caractère dissimulé ou ouvert de l’investigation et sur le degré d’intimité à adopter à l’égard des sujets-sources. Le chapitre montre ensuite l’intérêt et les limites de la collecte des données secondaires internes et externes aux organisations. Enfin, il indique les conditions de préservation de la confidentialité de la recherche, et ses conséquences sur la validation des résultats par les sujets-sources et sur la publication de la recherche.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.820
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.279
GPT teacher head0.413
Teacher spread0.134 · 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