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Record W7074697021

Canadian Mapping of Autism Specific Supports for Postsecondary Students

2022· article· en· W7074697021 on OpenAlexaboutno aff

Bibliographic record

VenueLancaster EPrints (Lancaster University) · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAutismPostsecondary educationHigher educationPeer groupInclusion (mineral)Peer support
DOInot available

Abstract

fetched live from OpenAlex

Background Many autistic students have a variety of strengths and the desire to succeed in postsecondary education. Nonetheless, most autistic students report not receiving adequate support in postsecondary education to ensure their success. Students also report difficulty in navigating complex institutional systems. We conducted an environmental scan of autism-specific supports (e.g., website information, transition programs, peer mentoring) available to autistic students within Canada’s publicly-funded postsecondary institutions. We also examined distribution of autism-specific supports across institutional type (i.e., university, junior college, technical/vocational) and geographic region. Method A Boolean search strategy was used to collect data from institutional websites. Results Of the 258 publicly-funded postsecondary institutions in Canada, only 15 institutions (6%) had at least one support. Of the 15 institutions identified, the most common autism-specific support included information on the institution’s website (67%), followed by transition to university support (47%), social group(s) (33%), peer mentoring (27%), specialist tutoring and support with daily living (20%), transition to employment support (13%), and student-led societies and autistic student advocate (7%). In general, universities and institutions in Central Canada (i.e., Ontario) had a disproportionate number of provisions. Conclusions There are promising advances with respect to autism-specific supports in postsecondary institutions across Canada. We recommend further research to better understand how students access these supports and more comprehensive evaluations of such supports, specifically informed by collaborations with autistic students.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0240.002

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 head0.035
GPT teacher head0.189
Teacher spread0.154 · 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; both teacher heads agree on what is shown here.

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
Published2022
Admission routes1
Has abstractyes

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