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Record W2442390

Challenges for inclusive education

2001· dissertation· en· W2442390 on OpenAlexvenueno aff
Corrienne Janet Beres

Bibliographic record

VenueThe Journal of Rheumatology · 2001
Typedissertation
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical sciencePedagogySociologyPsychology
DOInot available

Abstract

fetched live from OpenAlex

This study attempted to discover teachers' perceptions of the success of inclusive education - inclusion of learning disabled students - in the junior high schools of Westwind School Division #74. Several areas were explored. They included the extent to which inclusion is implemented across the Division, the teachers' perceptions of the academic and social success of the learning disabled students, the teachers' perceptions of the effects on the regular students, the teachers' evaluation of the extent to which factors stated in literature as being essential to the success of inclusion were present in their schools, and the changes needed for more successful inclusion. The sample for this study comprised all of the junior high teachers in the division who taught one or more of the core subject areas (science, social studies, mathematics, language arts) in Grades 7-9. All completed a written survey, then a sub-group were interviewed. The results demonstrated that although 82.93% of the teachers believed the regular classroom was the rightful place for the learning disabled students to learn, 80.48% felt that they were unable to meet the needs of these students. To improve the quality of the inclusive programming the respondents felt they required more planning and collaboration time, an increase in knowledge regarding programming adjustments for learning disabled students, reduced class sizes and other professional development activities to meet their individual needs.

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)0.018
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0120.019
Scholarly communication0.0210.018
Open science0.0020.022
Research integrity0.0100.016
Insufficient payload (model declined to judge)0.0430.007

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 head0.042
GPT teacher head0.417
Teacher spread0.375 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2001
Admission routes1
Has abstractyes

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