Document Landscape: Exploring What Shapes Disabled Students ’Experiences in Practice- Based Education
Bibliographic record
Abstract
Disabled students often face challenges in effectively meeting their learning and practicum requirements, even though institutions have policies in place to support access. Practice-based learning helps to ensure students have acquired sufficient practical knowledge of the field. It is used in many disciplines for effective skill development, and is mandatory for some accreditations, particularly in healthcare professional training. A wide array of documents (information artifacts) has been produced in connection with efforts to mitigate practice-based- education access barriers. Organizational challenges, including availability and distribution of effective documents, have led to ongoing inaccessibility. In this work, we put ourselves in the shoes of a student and imagine what documents would appear if a student were to self-search for resources that were available on the internet. We assembled a corpus of such documents [n=43] and conducted a qualitative analysis of document form and content. Three themes emerged from the form of the documents: (1) across all artifacts reviewed, students were absent from production and authorship; (2) limited documents were directly related to practice-based education; and (3) higher education institutions grapple with tensions in the choice of media as this selection can affect how the documents operate within their communities. Looking at the content of the documents we found that (1) barriers to access are often described as the responsibility of the disabled student; and (2) the vast majority of documents require, expect, or presume disclosure of disability status to be a prerequisite to access, revealing a reliance on a medical/individual model of disability. We conclude with a reflection on how the form and content of the documents may shape disabled students ’experiences in practice-based education.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".