Academic ableism and the experiences of disabled and neurodiverse Ph.D. students in LIS programs
Bibliographic record
Abstract
This article continues the discussion of the experiences of disabled and neurodiverse Ph.D. students in Library and Information Science programs in American and Canadian universities, following up on the previous report that addressed their struggles during and in the immediate aftermath of the COVID-19 pandemic. This article directs attention to their experiences in Ph.D. programs irrespective of the pandemic and focuses on both existing barriers and support mechanisms. Based on the results of a qualitative, online, self-administered survey, guided by hermeneutic phenomenology, the study identifies barriers rooted in attitudes and perceptions; policies and procedures; information and communication; physical spaces; virtual spaces and technology; and access to support services and networks. At the same time, an only mitigating factor and an only sustainable and consistently mentioned support mechanism was the good will, compassion, and supportive actions of individual faculty members. The article places the analysis and interpretation of empirical data in the context of academic ableism, conceptualizing the situation of Ph.D. students as a lingering state that was not improved even through the lessons and experiences of the pandemic.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.017 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.022 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".