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Record W2018485833 · doi:10.1177/1088357615583465

Overview and Evaluation of a Mentorship Program for University Students With ASD

2015· article· en· W2018485833 on OpenAlexaffabout
Megan E. Ames, Carly A. McMorris, Lisa N. Alli, James M. Bebko

Bibliographic record

VenueFocus on Autism and Other Developmental Disabilities · 2015
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsYork University
Fundersnot available
KeywordsMentorshipPsychologyAutism spectrum disorderMedical educationAutismLife satisfactionSample (material)Developmental psychologyMedicine

Abstract

fetched live from OpenAlex

The number of students with autism spectrum disorder (ASD) pursuing postsecondary education is increasing. A mentorship program was developed to help students with ASD navigate the social and academic framework of postsecondary campus life. The present study (a) provides information about a sample of university students with ASD and (b) evaluates satisfaction with the support provided. This is the first study in Canada to report on the experience of students with ASD and to evaluate this novel approach. Students ( N = 23) provided demographic information in the fall and completed surveys evaluating their satisfaction at the end of each academic year. Since beginning the program, the number of students has increased by 200%. High levels of satisfaction were reported. The majority of students reported success in achieving personal goals in part due to their participation in the program. Results better inform the development of supports for students with ASD.

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)0.006
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.136
GPT teacher head0.365
Teacher spread0.228 · 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

Citations129
Published2015
Admission routes2
Has abstractyes

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