MétaCan
Menu
Back to cohort
Record W2113579896 · doi:10.1111/cch.12046

School participation, supports and barriers of students with and without disabilities

2013· article· en· W2113579896 on OpenAlexaffabout
Wendy J. Coster, Mary Law, Gary Bedell, Kendra Liljenquist, Ying‐Chia Kao, Mary A. Khetani, Rachel Teplicky

Bibliographic record

VenueChild Care Health and Development · 2013
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsMcMaster University
FundersNational Institute on Disability and Rehabilitation Research
KeywordsLimitingPsychologyMedical educationDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: We compared school participation patterns of students ages 5-17 with and without disabilities and examined whether features of the school environment were perceived to help or hinder their participation. METHODS: Parents (n = 576) residing in the USA and Canada completed the Participation and Environment Measure for Children and Youth (PEM-CY) via the internet. RESULTS: Parents of students with disabilities reported that their children participated less frequently in school clubs and organizations and getting together with peers outside the classroom and that they were less involved in all school activities. Parents of students with disabilities also were significantly more likely to report that features of the environment hindered school participation and that resources needed to support their child's participation were not adequate. CONCLUSIONS: Parents of students with disabilities report that their children are participating less in important school-related activities. Barriers limiting school participation include features of the physical and social environment as well as limited resources.

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 score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.010
GPT teacher head0.292
Teacher spread0.282 · 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

Citations161
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueChild Care Health and DevelopmentSame topicCerebral Palsy and Movement DisordersFrench-language works237,207