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Record W2106864840 · doi:10.1177/0022466910397374

Adequacy of the Regular Early Education Classroom Environment for Students With Visual Impairment

2011· article· en· W2106864840 on OpenAlexaff
Cherylee M Brown, Tanya Packer, Anne Passmore

Bibliographic record

VenueThe Journal of Special Education · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsDalhousie University
Fundersnot available
KeywordsVisual impairmentCurriculumPsychologyMedical educationPedagogyMedicine

Abstract

fetched live from OpenAlex

This study describes the classroom environment that students with visual impairment typically experience in regular Australian early education. Adequacy of the classroom environment (teacher training and experience, teacher support, parent involvement, adult involvement, inclusive attitude, individualization of the curriculum, physical environment, and vision aids) for students with visual impairment in early regular education was assessed at the start and the end of one year. A total of 20 students with visual impairment (age M = 5.4 years) attending regular early education participated. In general, teacher-reported curriculum individualization and the physical environment were adequate. However, support provided for staff, teacher training, adult involvement, access to visual aids, and inclusive attitudes were less than adequate. More than 40% of students experienced fewer than four out of nine adequate environmental features. These results indicate that strategies to improve teacher training, support, attitudes, and access to vision aids are needed.

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)0.004
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.345
Teacher spread0.325 · 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

Citations44
Published2011
Admission routes1
Has abstractyes

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