Undergraduate Disabled Students as Knowledge Producers Including Researchers: Perspectives of Disabled Students
Bibliographic record
Abstract
Knowledge influences policy development and policies impact disabled people. Scientific and technological advancements, including neuro-advancements and their governance, have social implications for disabled people. However, knowledge is missing on this topic. Although efforts are underway to increase the number of disabled academics, the numbers remain low. Engaging undergraduate disabled students in knowledge production, especially research, could decrease the knowledge deficit and increase the pool of disabled students considering an academic career. We performed 10 semi-structured interviews of disabled students to understand the reality of undergraduate disabled students as knowledge producers, including researchers. Using a directed thematic content analysis, we found that participants felt that undergraduate disabled students were insufficiently exposed to and supported in the identity of being knowledge producers including researchers. Participants identified ethical, legal, and social implications of science and technology and argued that undergraduate disabled students and disabled people have a role to play in the discussions of these. Exposing disabled students at the undergraduate and high school level to knowledge production including researcher identity could increase the numbers of undergraduate disabled researchers, disabled academics, and disabled students doing research in the community after graduation and decrease the knowledge gaps around the social situation of disabled people.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.021 | 0.022 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.002 | 0.022 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".