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Record W7066911239

Inclusion and health: A study of the 2001 Participation and Activity Limitation Survey (PALS)

2008· article· en· W7066911239 on OpenAlexaboutno aff

Bibliographic record

VenueIslandScholar (University of Prince Edward Island) · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsInclusion (mineral)Framing (construction)Special educational needsStatistical analysisSurvey data collectionData collectionEducational research
DOInot available

Abstract

fetched live from OpenAlex

This thesis presents findings of a quantitative study into the relationship between inclusive education settings and the parent-reported health of more than 140, 000 Canadian children with disabilities between 5 and 14 years of age. In framing the research questions and analysis of the data, the thesis includes a critical review of the concepts of disability, inclusive education and health. The main statistical data that were used were retrieved from the children's component of Statistics Canada's 2001 Children's Participation and Activity Limitation Survey (PALS), a major post-censal survey of people with disabilities. PALS provides a wealth of information about children with disabilities in Canada. Responses to questions from PALS were selected to compile a framework to distinguish three levels of inclusiveness of educational settings: low, middle and high. Using the broad approach to health that guided the research and these three levels of educational inclusiveness, the analysis revealed that parents were more likely to report that their children with disabilities are in better general health, progress very well/well at school, interact very well/well with their peers, and frequently look forward to going to school in higher inclusive educational settings than in mid-range or lower inclusion settings. This positive trend was consistent, regardless of severity and type of disability.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.006
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

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

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 head0.040
GPT teacher head0.277
Teacher spread0.237 · 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 teacher head, 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

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

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