Academic Coverage of Social Stressors Experienced by Disabled People: A Scoping Review
Bibliographic record
Abstract
Social stress can be caused by many factors. The United Nations Convention on the Rights of Persons with Disabilities (CRPD) highlights many social stressors disabled people experience in their daily lives. How social stressors experienced by disabled people are discussed in the academic literature and what data are generated influence social-stressor related policies, education, and research. Therefore, the aim of our study was to better understand the academic coverage of social stressors experienced by disabled people. We performed a scoping review study of academic abstracts employing SCOPUS, the 70 databases of EBSCO-HOST and Web of Science, and a directed qualitative content analysis to achieve our aim. Using many different search strategies, we found few to no abstracts covering social stressors experienced by disabled people. Of the 1809 abstracts obtained using various stress-related phrases and disability terms, we found a bias towards covering disabled people as stressors for others. Seventeen abstracts mentioned social stressors experienced by disabled people. Fourteen abstracts flagged “disability” as the stressor. No abstract contained stress phrases specific to social stressors disabled people experience, such as “disablism stress*” or “ableism stress*”. Of the abstracts containing equity, diversity, and inclusion phrases and policy frameworks, only one was relevant, and none of the abstracts covering emergency and disaster discussions, stress-identifying technologies, or science and technology governance were relevant. Anxiety is one consequence of social stressors. We found no abstract that contained anxiety phrases that are specific to social stressors disabled people experience, such as “ableism anxiety”, “disablism anxiety” or “disability anxiety”. Within the 1809 abstract, only one stated that a social stressor is a cause of anxiety. Finally, of the abstracts that contained anxiety phrases linked to a changing natural environment, such as “climate anxiety”, none were relevant. Our study found many gaps in the academic literature that should be fixed and with that highlights many opportunities.
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 | 0.020 | 0.108 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.041 | 0.041 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".