'Disabled or not, people just want to feel welcome': stories of microaggressions and microaffimations from college students with intellectual disability
Bibliographic record
Abstract
As part of a larger storytelling project with college students belonging to minoritized social groups, nine young adults from an inclusive college program for students with intellectual disability (ID) participated in narrative interviews. All were invited to tell stories about campus incidents of microaggression and microaffirmation related to their disability. They also were invited to tell stories about other social identities they claimed. Stories were analyzed thematically and for correspondence with findings from previous studies involving other social identity groups. Students told a variety of stories about interpersonal incidents on campus that made them feel respected or disrespected. They also shared stories of institutional encounters that influenced their sense of acceptance at the university. Although they told more stories about microaffirmations, they were not immune to microaggressions. However, many of the students' microaffirmation stories placed importance on not being perceived as different rather than a clear affirmation of disability identity. Students' stories have implications for fostering a campus climate where students with ID are respected and included and where ableism is addressed in substantial ways.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".