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Record W154874506 · doi:10.5206/eei.v17i3.7611

The Characteristics and Experiences of CanadianStudents Receiving Special Education Services fora Learning Disability

2007· article· en· W154874506 on OpenAlexaffvenueabout
Jessica Whitley, Judy Lupart, Tanya Beran

Bibliographic record

VenueExceptionality Education International · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsUniversity of CalgaryUniversity of AlbertaLakehead University
Fundersnot available
KeywordsLearning disabilityPsychologySpecial educationDrop outPerceptionMedical educationDevelopmental psychologyMathematics educationPedagogyMedicine

Abstract

fetched live from OpenAlex

This article provides a description of the demographic characteristics as well as the social and academic experiences of a nationally representative sample of Canadian students receiving special education services for a learning disability (LD) and a comparison group without disabilities (NLD). Data summarized in this article were drawn from the National Longitudinal Survey of Children and Youth (NLSCY), which contains information provided by teachers, parents, and students. Results indicate that the demographic characteristics of the LD group are similar to the NLD group. As well, no signifi cant differences were found between the self-reports of children in the LD and NLD groups regarding school and social experiences. However, differences exist in teachers’ perceptions of students’ educational potential, social skills, and motivation. The findings inform school efforts focused on reducing the drop-out rate of students with LD. Other implications for practice as wellas for future research are discussed.

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)0.002
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 score0.146
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.022
GPT teacher head0.377
Teacher spread0.355 · 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

Citations1
Published2007
Admission routes3
Has abstractyes

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