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Record W4389065809 · doi:10.7202/1106955ar

Pratiques plurielles d’évaluation propres aux organismes communautaires au Québec : état des lieux

2023· article· fr· W4389065809 on OpenAlexaffvenueabout
Sonia Tello‐Rozas, Maude Léonard, Florence Lussier-Lejeune, Hind Obad-Fathallah, V. Goulet, Céline Métivier, Lise Gervais, Geneviève Chicoine

Bibliographic record

VenueReflets Revue d’intervention sociale et communautaire · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsRelais FemmesUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceValuation (finance)ArtEconomics

Abstract

fetched live from OpenAlex

Cet article, résultat d’une recherche partenariale combinant des méthodes quantitatives et qualitatives, fait état des pratiques d’évaluation des organismes communautaires au Québec. Nos résultats montrent que l’évaluation comme processus réflexif fait partie de l’ADN des organismes communautaires. Ils corroborent deux éléments soulignés dans la littérature sur le sujet : la confusion encore présente entre la reddition de comptes et l’évaluation, et le rôle fondamental des ressources. Nos résultats font ressortir également un élément essentiel à la compréhension des pratiques d’évaluation propres aux organismes communautaires : la cohabitation des pratiques réflexives, dites parfois « informelles », qui sont intégrées au fonctionnement quotidien des organismes, avec des pratiques d’évaluation systématisées. Ces dernières ont un caractère plus complexe, se focalisent sur quelques objectifs ou thèmes précis, nécessitent une expertise et des capacités en évaluation et demandent des ressources financières importantes.

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)0.026
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 score0.218
Threshold uncertainty score0.439

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0080.006
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0010.002
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 head0.085
GPT teacher head0.391
Teacher spread0.306 · 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

Citations3
Published2023
Admission routes3
Has abstractyes

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