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Record W4285273215 · doi:10.7202/1088796ar

« Montre-moi que tu t’intéresses à moi et que tu me crois » : questionner les relations de pouvoir adulte-enfant en recherche

2022· article· fr· W4285273215 on OpenAlexaffvenue
Vicky Lafantaisie, Sarah Tourigny, Mélissa David

Bibliographic record

VenueRecherches qualitatives · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Les enfants ont rarement la chance de participer de manière active et centrale aux interventions qu’ils reçoivent et à la construction de savoirs les concernant. En nous inspirant de la Youth Participatory Action Research, une approche qui s’inscrit dans le champ de la recherche à visée transformatrice, nous avons travaillé avec des enfants de 7 à 12 ans pour identifier des éléments qui facilitent leur participation à l’intérieur des organisations de services. Afin d’éviter de reproduire les inégalités qui organisent habituellement les rapports enfant-adulte, nous avons voulu, comme point d’ancrage du projet, favoriser l’établissement d’une relation enfant-chercheuse. Cet article souhaite 1) identifier des repères épistémologiques qui justifient la pertinence de la création d’une relation en recherche, 2) décrire des initiatives mises en place pour soutenir la création d’une relation non hiérarchique avec des jeunes de 7 à 12 ans, 3) cibler des éléments qui favorisent leur participation et 4) discuter des tensions qui apparaissent dans une démarche de recherche participative avec des enfants.

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)0.045
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.955
Threshold uncertainty score0.239

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.056
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0120.024
Scholarly communication0.0120.011
Open science0.0020.009
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.311
GPT teacher head0.486
Teacher spread0.175 · 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.

Study designQualitative
DomainMethods
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

Citations3
Published2022
Admission routes2
Has abstractyes

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