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Record W4303431171 · doi:10.7202/1091515ar

MOTIVATION ASSOCIÉE AU PROCESSUS DE RACCROCHAGE SCOLAIRE DE JEUNES FRÉQUENTANT UN ORGANISME COMMUNAUTAIRE

2022· article· fr· W4303431171 on OpenAlexvenueno aff
Camille Jutras-Dupont, Annie Dubeau, Danielle Desmarais, Maryvonne Merri, Dominique Eybalin

Bibliographic record

VenueCanadian social work review · 2022
Typearticle
Languagefr
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyPhilosophy

Abstract

fetched live from OpenAlex

Revenir à l’école après avoir décroché constitue un projet laborieux, notamment parce que plusieurs jeunes réintégrant le milieu de l’éducation formelle le quittent à nouveau (Marcotte et coll., 2011). Afin de mieux comprendre les enjeux motivationnels auxquels les jeunes raccrocheurs font face, notre étude s’est intéressée au projet scolaire de 28 jeunes adultes Montréalais en recourant au modèle attentes-valeur (Eccles et Wigfield, 2002). Les discours de ces jeunes font d’abord ressortir l’importance d’avoir un projet scolaire bien défini. Sur le plan de leurs attentes de succès, nous constatons que les jeunes qui identifient des moyens leur permettant de réaliser leur projet scolaire sont plus confiants. Ces éléments suggèrent qu’un accompagnement permettant de préciser son projet scolaire et d’identifier des moyens permettant sa réalisation serait bénéfique. Sur le plan de la valeur accordée au projet scolaire, le désir d’améliorer ses conditions de vie et l’importance d’obtenir un premier diplôme influencent positivement la motivation des jeunes rencontrés alors que le manque de soutien financier et familial contribue à miner celle-ci. Ce faisant, pour contrecarrer ces éléments négatifs un accompagnement visant à accroitre l’autonomie financière du jeune et son émancipation sociale est à préconiser.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.715
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0470.000

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 head0.026
GPT teacher head0.297
Teacher spread0.271 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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