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Record W2072799406 · doi:10.1111/cdev.12124

Swiss Children's Moral and Psychological Judgments About Inclusion and Exclusion of Children With Disabilities

2013· article· en· W2072799406 on OpenAlexaff
Luciano Gasser, Tina Malti, Alois Buholzer

Bibliographic record

VenueChild Development · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsUniversity of Toronto
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsPsychologyInclusion (mineral)Developmental psychologyInclusion–exclusion principleSocial exclusionContext (archaeology)Learning disabilitySocial psychology

Abstract

fetched live from OpenAlex

Children's judgments about inclusion and exclusion of children with disabilities were investigated in a Swiss sample of 6-, 9-, and 12-year-old children from inclusive and noninclusive classrooms (N = 422). Overall, the majority of children judged it as morally wrong to exclude children with disabilities. Yet, participants were less likely to expect the inclusion of children with mental or physical disabilities in academic and athletic contexts compared to social contexts. Moreover, older children more consistently coordinated disability type with context of exclusion. There were also significant differences depending on the type of classroom. The findings extend existing research on exclusion by investigating exclusion based on disability across different age groups and educational settings.

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)0.001
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.308
Teacher spread0.282 · 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

Citations53
Published2013
Admission routes1
Has abstractyes

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