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Record W2754003819 · doi:10.5463/dcid.v28i2.573

Teachers’ Perceptions of Disabilities on the Island of Roatán, Honduras

2017· article· en· W2754003819 on OpenAlexaff
Cornelia Schneider

Bibliographic record

VenueDisability CBR & Inclusive Development · 2017
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsPerceptionPsychologyGeographyNeuroscience

Abstract

fetched live from OpenAlex

Purpose: Roatán, a small island in Honduras, is home to six ethnic groups. Due to financial constraints, many children have limited access to schooling. This article is a study on teachers’ perceptions of disabilities and students with disabilities and inclusive education on the island. Method: Twenty seven teachers working in public and private schools, and schools funded by the World Bank, were interviewed in March-April of 2014 in order to explore cultural and social representations of disabilities on the island. Results: The findings show that many of the teachers’ representations can be analysed under the lens of different models of disability - the medical model, the social model, and a religious-moral model. Inclusive education is perceived less as a means of including children with disabilities in the regular classroom, and more as a method of creating institutions to take care of their needs. Conclusion: There is a strong intersection of poverty, post-colonialism and disability which makes working under an inclusive lens very difficult for teachers. The cultural norms influence ideas of normalcy and disabilities, and the blame is on parents for having children with disabilities.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.534

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.055
GPT teacher head0.381
Teacher spread0.326 · 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 designQualitative
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

Citations5
Published2017
Admission routes1
Has abstractyes

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