Post-secondary students with disabilities share stories of belonging
Bibliographic record
Abstract
This study examined a sense of belonging as integral to inclusion for students with disabilities within a post-secondary context. Grounded in a critical disability lens, coupled with identity theories, a narrative research approach was used. Nine students with disabilities from a small, Canadian, rural college shared stories of belonging and of the significance they ascribe to belonging in their overall post-secondary experience. Three prominent themes, narratives of becoming a student, narratives of engagement and narratives of barriers to belonging were uncovered. Narratives of becoming a student relate to the development of a student identity and its reciprocal relationship to the development of a sense of belonging. Narratives of engagement capture the positive and/or negative interactions of students with faculty and peers and the impact on belongingness. Narratives of barriers to belonging highlight the environmental, physical, systemic and attitudinal obstacles encountered by students. Analyzing narrative accounts through critical disability and identity frameworks revealed in-depth understandings of students’ belonging experiences. Results of this study offer both theoretical and practical implications for institutions to consider in their commitment to cultivating belonging-centred campuses. Further, I suggest including disability as part of institutional diversity and also the use of a multifaceted critical lens of identity and disability in which to view stories of belonging.
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 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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".