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Record W4250771387 · doi:10.7202/1085403ar

L’analyse de contenu pour la recherche en didactique de la littérature. Le traitement de données quantitatives pour une analyse qualitative : parcours d’une approche mixte

2006· article· fr· W4250771387 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueRecherches qualitatives · 2006
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Afin de contribuer à l’épistémologie de la didactique de la littérature, nous avons mené une recherche doctorale visant à identifier et à hiérarchiser les finalités de l’enseignement de la littérature au cours de la scolarité pré-universitaire, dans la perspective de la construction d’un modèle didactique de cet enseignement. Notre recherche a fait appel à deux démarches d’investigation complémentaires. La première consiste en une analyse documentaire de type analyse de contenu. Cette analyse descriptive et critique a été suivie d’une démarche interprétative afin de comprendre les finalités assignées à cet enseignement. Le choix d’une approche méthodologique mixte, qui combine des éléments quantitatifs et qualitatifs, nous semble inusité et prometteur pour la recherche en didactique de la littérature, un champ encore trop souvent imprégné d’implicites et de flous méthodologiques.

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)0.152
metaresearch head score (Gemma)0.099
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.291
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1520.099
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0010.004
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0000.000

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 head0.379
GPT teacher head0.516
Teacher spread0.137 · 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