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Record W4254553487 · doi:10.32920/ryerson.14654262.v1

Examining preparation of general education teachers for working with children with disabilities

2021· preprint· en· W4254553487 on OpenAlexaffabout
Penny Diamantouros

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsUniversity of WindsorToronto Metropolitan UniversityEducation and Early Childhood DevelopmentUniversity of Toronto
Fundersnot available
KeywordsPsychologySpecial educationSchool teachersTeacher preparationMathematics educationQualitative researchMedical educationPedagogyTeacher educationMedicineSociology

Abstract

fetched live from OpenAlex

This qualitative study explored how well prepared first year teachers feel in teaching children with disabilities in the regular classroom. Six elementary school teachers, recent graduates from Faculties of Education in Ontario were interviewed. Findings indicate that the teachers in this study do not feel that their pre-service education program prepared them for the reality of teaching students with disabilities in the regular classroom, and that they will need to look to their School Board for further training. In addition, many feel that they lack the knowledge necessary to design and implement an IEP. The importance of further preparation for first year teachers to work with students with IEPs is discussed and explored.

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)0.008
metaresearch head score (Gemma)0.023
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.023
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0090.007
Scholarly communication0.0040.002
Open science0.0020.004
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 head0.061
GPT teacher head0.361
Teacher spread0.301 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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