296 UK survey of young adults with juvenile idiopathic arthritis and their vocational experiences
Bibliographic record
Abstract
Background: There is little known about the experiences of young adults living with juvenile idiopathic arthritis (JIA) preparing for employment and career development. The purpose of this study was to understand the impact JIA has on career planning and early employment experiences of young adults (16-30 years). Methods: Using existing literature (including grey literature), an online survey was developed and sent to National Rheumatoid Arthritis Society (NRAS) members and distributed to non-members via social media tools. Data collected included views and experiences in career planning and employment. Results: Of 1241 respondents, 19 were young adults with JIA, of these 89% were female. There is incomplete data for all 19 young adults. 9/17 respondents reported their school did not offer additional work-related activities to students with disabilities and/or additional needs. Respondents agreed with few statements relating to school organised work placements. However, 10/14 young adults felt their school did not provide advice about coping with possible limitations on placements/traineeships due to their arthritis (Table 1). 11/14 respondents thought about their condition when thinking about future career plans. However, 8/14 felt their career advisors did not take their arthritis into account. 8/14 young adults changed their career plans because of their arthritis. Managing JIA symptoms and a physically demanding role, as well as wanting to stay healthy, were the main reason for changing career. 9/13 respondents were in paid employment. Important aspects of employment included: “good relationships with your line manager, work you like doing and a job you can use your initiative”.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".