The Work Disability Prevention CIHR Strategic Training Program: Program Performance After 5 Years of Implementation
Bibliographic record
Abstract
INTRODUCTION: The Work Disability Prevention (WDP) Canadian Institutes of Health Research (CIHR) Strategic Training Program was developed in 2001 and is a unique program in the world. The main objective of this program is to help future researchers develop transdisciplinary knowledge, skills and attitudes regarding WDP. The purpose of this paper is to present a descriptive portrait of the program's performance over the past 5 years, as well as the trainees' and alumni's perspectives on the WDP CIHR Training Program. METHODS: Data on the program's performance were collected from documents in the program records. The trainees' opinions on the WDP training program were obtained through focus groups and telephone interviews. The data collected were compiled and divided into themes to summarize the qualitative findings pertaining to each question. RESULTS: From 2003 to 2007, five successive summer sessions have been offered, involving 44 high-caliber applicants from nine countries, 34 mentors and collaborators, 29 guest speakers and 15 stakeholders. Overall, trainees appreciated the networking, the opportunity to interact with people from different disciplines and countries, the openness, and the international perspective and uniqueness of the program. The least appreciated aspects concerned mainly the e-learning course, evaluations and information on optional courses. The coordination and logistics were judged appropriate and several topics were suggested to improve the program quality. CONCLUSION: In general, the program implementation went well, with good participation from mentors, speakers and stakeholders; the program was appreciated by the trainees and alumni. This paper underscores the importance of the international perspective, the transdisciplinarity and the scientific networking established through the program.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".