Multiple sclerosis and academic work: Socio‐spatial strategies adopted to maintain employment
Bibliographic record
Abstract
Maintaining paid work and the occupational identity it entails after onset of multiple sclerosis is important and beneficial. Research consistently shows that employees with multiple sclerosis who are more highly educated and in positions with greater occupational prestige are more likely to remain in the workforce. We ask: what is it about the specific workplaces in which such workers are employed that facilitates these employment outcomes? To answer this question we conducted an exploratory pilot study involving 10 semi‐structured interviews with Canadian academics with multiple sclerosis. Respondents’ adoption of socio‐spatials trategies related to travel, spatio‐temporalr outines, and social networks was central to maintaining a place in the academic workforce. Factors such as flexibility, access to resources, and symptom fluctuation enabled these strategies. The findings show that the relationships between place and occupation are complex in that multiple physical and social spaces and also roles are invoked in maintaining a particular occupational identity.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".