The big sell: Managing stigma and workplace discrimination following moderate to severe brain injury
Bibliographic record
Abstract
BACKGROUND: Misperceptions regarding persons with brain injuries (PWBI) can lead to stigmatization, workplace discrimination and, in turn, influence PWBIs full vocational integration. OBJECTIVE: In this study we explored how stigma may influence return-to-work processes, experiences of stigma and discrimination at the workplace for persons with (moderate to severe) brain injuries, and strategies that can be employed to manage disclosure. METHODS: Exploratory qualitative study; used in-depth interviews and an inductive thematic analytical approach in data analysis. Ten PWBI and five employment service providers participated. PWBI discussed their work experiences, relationships with supervisors and co-workers and experiences of stigma and/or discrimination at work. Employment service providers discussed their perceptions regarding PWBI's rights and abilities to work, reported incidents of workplace discrimination, and how issues related to stigma, discrimination and disclosure are managed. RESULTS: Three themes were identified: i) public, employer and provider knowledge about brain injury and beliefs about PWBI; ii) incidents of workplace discrimination; iii) disclosure. Misperceptions regarding PWBI persist amongst the public and employers. Incidents of workplace discrimination included social exclusion at the workplace, hiring discrimination, denial of promotion/demotion, harassment, and failure to provide reasonable accommodations. Disclosure decisions required careful consideration of PWBI needs, the type of information that should be shared, and the context in which that information is shared. CONCLUSIONS: Public understanding about PWBI remains limited. PWBI require further assistance to manage disclosure and incidents of workplace discrimination.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".