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Record W4409134332 · doi:10.51657/w2a79h79

Enseignement-apprentissage des compétences socio-émotionnelles aux él`eves avec déficience visuelle : de la théorie à la pratique

2025· article· en· W4409134332 on OpenAlexvenueno aff
Alessio Barras

Bibliographic record

VenueRevue internationale du CRIRES innover dans la tradition de Vygotsky · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPsychologyPhilosophySociology

Abstract

fetched live from OpenAlex

Socio-emotional skills (SESs) are primarily acquired implicitly through observation and imitation in social interactions. Students with visual impairment (VI) are likely to face challenges in this area, which can affect their relationships with peers, increase their dependence on adults, and limit their social participation. Nevertheless, students with VI have the potential to learn SESs and develop compensatory strategies. This theoretical article therefore has three objectives. First, from a theoretical perspective, it explores the specific link between SESs and VI. Second, it proposes a general theory of teaching-learning of SESs, drawing on the vygotskian approach towards special education. Third, from a practical perspective, it presents assessment tools and teaching-learning strategies for SESs, aimed at supporting special education teachers and educators working in this field.

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)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.007
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.052
GPT teacher head0.379
Teacher spread0.327 · 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 designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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