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Record W4320486838 · doi:10.21203/rs.3.rs-2560015/v1

Disabled Students in Fieldwork Education: Academic Coordinators’ Perspectives on Accommodation Process

2023· preprint· en· W4320486838 on OpenAlexaff
Yael Mayer, Fernanda Mira, Shahbano Zaman, Tal Jarus

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAccommodationInclusion (mineral)Medical educationExploratory researchPedagogyHigher educationPsychologySociologyMedicinePolitical science

Abstract

fetched live from OpenAlex

Abstract Learning in a fieldwork setting is a requirement of many professional postsecondary programs, and prominent in health professions education. However, fieldwork education requirements can create additional challenges for disabled students. Academic coordinators, who are responsible for students’ placements, hold an important role in supporting disabled students in their fieldwork education. Nevertheless, studies on the roles and experiences of academic coordinators supporting students who require accommodations are limited. This exploratory study examined the perspectives of academic coordinators regarding their practices in supporting disabled students in health professions programs. The study employed a mixed methods design. Fifteen academic coordinators from occupational therapy programs completed a quantitative survey. Then, five of the academic coordinators participated in semi-structured interviews that supported the interpretation of the quantitative results. Academic coordinators faced complex barriers in providing disabled students the support they needed to succeed in fieldwork. Two main themes emerged: (1) ACs constantly navigated tensions with institutional norms regarding fieldwork and (2) ACs manage fieldwork accommodations within ever-changing human dynamics and social norms. Collaborative practices with fieldwork educators enabled the academic coordinators to overcome some of these barriers and create a more inclusive fieldwork education experience for disabled students. Further institutional and community resources are required.

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)0.021
metaresearch head score (Gemma)0.023
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 score0.021
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0130.012
Scholarly communication0.0120.004
Open science0.0020.009
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.213
GPT teacher head0.637
Teacher spread0.424 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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