MétaCan
Menu
Back to cohort
Record W2886195855 · doi:10.5206/eei.v28i1.7757

College Students with Disabilities Explain Challenges Encountered in Professional Preparation Programs

2018· article· en· W2886195855 on OpenAlexvenueno aff
Maureen E. Squires, Brad Countermine

Bibliographic record

VenueExceptionality Education International · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMedical educationQualitative researchHigher educationPresentation (obstetrics)PedagogySpecial educationProfessional developmentMedicineSociologyPolitical science

Abstract

fetched live from OpenAlex

Throughout the United States, students with disabilities (SWD) are entering higher education in greater numbers than in the past; they also encounter barriers that negatively impact their college experience. This qualitative study explores the challenges of SWD at a public comprehensive college in the northeastern United States. Our research questions include the following: What are the internal and external challenges of college SWD in professional preparation programs? What might this mean for practice in higher education? In total, 541 participants completed an open-ended survey. Of this group, 45 participants disclosed having a disability, and 12 participated in follow-up interviews. Primary themes that emerged from this study include under- developed self-determination skills, lack of understanding (by SWD and faculty), the stigma associated with disabilities, and ineffective accommodations and support services. What follows is a review of relevant literature, discussion of findings, and presentation of implications for college SWD and professionals in higher education.

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)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0120.007
Scholarly communication0.0060.004
Open science0.0010.010
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.072
GPT teacher head0.439
Teacher spread0.367 · 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 designQualitative
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

Citations15
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueExceptionality Education InternationalSame topicDisability Education and EmploymentFrench-language works237,207