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Record W6980000500

Are You In or Out? Canadian Students Who Register for Disability-Related Services in Junior/Community Colleges versus Those Who Do Not

2018· article· en· W6980000500 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2018
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRegister (sociolinguistics)Government (linguistics)Work (physics)Agency (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

"Junior/community colleges tend to enroll more students with disabilities than four-year colleges. Therefore, knowing about the nature of students’ disabilities and about which students register for campus disability-related services is important. Here, we report on a random sample of 1387 Canadian junior/community college students, 17% of whom self-reported a disability. The most common disabilities reported, in rank order, were learning disability with or without attention deficit hyperactivity disorder (LD/ADHD), mental illness, chronic health problems, hearing impairments, and visual impairments. Only 44% of students with self-reported disabilities indicated registering for campus disability-related services. Prominent among those who had not done so were students with mental illness and students with chronic medical conditions. When we split students into those with only LD versus those with only ADHD, we found that students with LD were quite likely to register for services, whereas those with ADHD were not. In general, students with disabilities were under-represented in the sciences, although we found no relationship between students’ disabilities and their programs of study. The same was true of students who had and those who had not registered for campus disability-related services. We speculate on why students with specific disabilities do not register for disability-related services. "@eng

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)0.005
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 score0.021
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0070.002
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0210.002

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 head0.063
GPT teacher head0.336
Teacher spread0.272 · 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

Citations2
Published2018
Admission routes1
Has abstractno

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