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Record W3007089147 · doi:10.1111/1471-3802.12488

Sociodemographic profiles of high school students across multiple types of special needs and disabilities

2020· article· en· W3007089147 on OpenAlex
Jennifer E. V. Lloyd, Danjie Zou, Jennifer Baumbusch

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Research in Special Educational Needs · 2020
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSpecial needsQuarter (Canadian coin)Diversity (politics)Sample (material)PsychologyPopulationSpecial educationScope (computer science)Needs assessmentSpecial populationsInclusion (mineral)Developmental psychologyGeographyMedicineEnvironmental healthSocial psychologyMathematics educationPsychiatrySociologySocial scienceComputer science

Abstract

fetched live from OpenAlex

A paucity of population‐based research explores the prevalence and sociodemographic characteristics of high school students with varieties of special needs and disabilities. Utilising a population‐based sample of self‐reported data collected in British Columbia, Canada, we investigated the scope and sociodemographic characteristics of adolescents between and within multiple categories of physical, mental, emotional and behavioural needs – including those with two or more conditions and no conditions. First, we computed the most commonly occurring and least commonly occurring special needs categories. Second, we created profiles of the broad sociodemographic characteristics of adolescents in each special needs category. Finally, we determined whether the profiles indicated statistically significant between‐ and within‐category heterogeneity. We found that over one‐quarter of adolescents had one or more special needs, while nearly three‐quarters of the special needs subpopulation had only three of the nine special needs tracked. Also, whether adolescents with a given special need were compared to those from different categories or those within the same category, there was considerable diversity in their sociodemographic attributes. Our study is one of the first to describe adolescents with special needs in this population‐based fashion. We hope that our findings may guide programme and policy development in British Columbia and around the world.

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.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.109
GPT teacher head0.465
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