SS04-03 RETURN TO WORK MANAGEMENT FOLLOWING AN OCCUPATIONAL INJURY
Bibliographic record
Abstract
Abstract Introduction It is important to focus on the issue of returning to work following a professional injury and to better understand it. By doing so, it is possible to identify the complexities and difficulties that can prolong the situation of incapacity. Methods For this, the intervention and involvement of several actors in the organization are necessary. The goal of this intervention project is to better understand what influences the return to work within the emergency health corporation, from the worker's perspective. This qualitative project takes the ecological model of disability management as its conceptual model. Semi-structured interviews were conducted for this project with paramedics and heads of departments concerned with returning to work. Subsequently, an analysis of the interviews is conducted to highlight the elements that facilitate and hinder the return to work. Discussion Elements such as the adaptation strategy, the reactions and emotions of the paramedics and their relatives, as well as elements related to the personal life of the worker, emerged. Concerning the work environment, the quality of working relationships between the employee and their manager, the culture of the organization, and the management practices used are the main elements highlighted by the participants. Conclusion The results obtained during these interviews are consistent with the literature and prompt further reflection on exploring the influence on returning to work within the emergency health corporation.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".