Moving toward virtual interdisciplinary teams and a multi-stakeholder approach in community-based return-to-work care
Bibliographic record
Abstract
More efforts are needed to help stakeholders who are geographically isolated from one another become more collaborative in their approach to return-to-work (RTW). A review of the literature on team processes, and insights from the experiences of a federally funded Round Table Project on Safe and Timely Return to Function and Return to Work were used to inform strategies that might enhance collaboration among health professionals and stakeholders in injury and illness management and return-to-work. A case study serves to highlight the individual, identifies the problem and provides a potential solution at the broader service and system levels. It becomes evident that there is a need for a common language as well as policies that emphasize the importance of fostering awareness of interprofessional potentials and contributions of all stakeholders. Establishing shared goals, and building capacity for sustaining collaboration when multi-stakeholders do not function in the same physical location, but work virtually, might maximize effectiveness, efficiency and productivity.
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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 | 0.058 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.013 | 0.014 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".