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Record W4319310321 · doi:10.7202/1095696ar

Pratiques de soutien au cours d’un groupe d’intégration sociale et professionnelle : retombées sur les capabilités de personnes réfugiées dans leur parcours d’apprentissage

2023· article· fr· W4319310321 on OpenAlexaffvenueabout
Patricia Dionne, Jo Anni Joncas, Josée Charette

Bibliographic record

VenueNouveaux cahiers de la recherche en éducation · 2023
Typearticle
Languagefr
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversité du Québec à MontréalUniversité de Sherbrooke
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyPhilosophy

Abstract

fetched live from OpenAlex

Au Québec, des centres d’aide à l’emploi offrent des programmes d’intégration sociale et professionnelle (ISP) des personnes réfugiées ou demandeuses d’asile, qui arrivent avec un parcours souvent sinueux, parfois ponctué d’expériences traumatisantes. Ce parcours peut complexifier leur ISP dans leur société d’accueil et les exposer à des situations de vulnérabilité sociale. Nous cherchons à comprendre comment le parcours d’apprentissage au cours d’un programme d’ISP en groupe permet d’ouvrir l’éventail des opportunités réelles et favorise la justice sociale du point de vue opérationnel de l’approche par les capabilités. L’analyse qualitative processuelle des parcours d’apprentissage de ces personnes articule les ressources que rend disponible le programme en vue d’élargir leurs opportunités réelles d’ISP. Sont également analysées, les entraves à la conversion des ressources transmises en instruments pour l’apprentissage.

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)0.008
metaresearch head score (Gemma)0.013
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 score0.622
Threshold uncertainty score0.761

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0230.017
Scholarly communication0.0070.004
Open science0.0020.007
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.214
GPT teacher head0.477
Teacher spread0.263 · 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

Citations0
Published2023
Admission routes3
Has abstractyes

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