Vocational experiences and career support opportunities among Canadian men with moderate and severe haemophilia
Bibliographic record
Abstract
AIM: The purpose of this research was to provide haemophilia treatment centres (HTCs) with guidance for the potential development of appropriate and timely interventions related to employment and vocational counselling and supports. METHODS: A multi-method approach was employed, where initial focus groups (n = 13) and review of the literature were used to construct a structured survey instrument (n = 75). RESULTS: Focus group participants made choices about employment with keen awareness of how their bleeding disorder might limit them physically; they described the role of social networks in career choices; and they wrestled with issues of disclosure. Among survey respondents, 47% per cent of respondents reported that haemophilia had a small negative impact, 27% felt that it had a moderate negative impact and 13% indicated that it had a very large negative impact. One-third of respondents had at some point received employment-related advice from a member of their haemophilia treatment centre team. Roughly two-thirds of respondents suggested that vocational advice would be "somewhat" or "very" useful at present. CONCLUSION: Canadian men with haemophilia continue to experience challenges related to employment and career development. There appears to be an opportunity for HTCs to incorporate additional supports on these topics into the range of services which they currently provide.
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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 | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".