The social interaction of return to work explored from co-workers experiences
Bibliographic record
Abstract
PURPOSE: The objective was to explore the role and contribution of co-workers in the return-to-work process. The social interaction of co-workers in the return-to-work process are analysed within the framework of the Swedish national and local employer organisational return-to-work policies. METHODS: An exploratory qualitative method was used, consisting of open-ended interviews with 33 workplace actors across seven work units. Organisational return-to-work policies were collected from the three public sector employers. RESULTS: The key findings that emerged during analysis showed that some co-workers have a more work-task oriented approach towards the return-to-work process, whilst others had a more social relational approach. In both situations, the social relations worked hand in hand with job tasks (how task were allocated, and how returning workers were supported by others) and could make or break the return-to-work process. CONCLUSION: A suggestion for improvement of return-to-work models and policies is the need to take into account the social relations amongst workplace actors, especially involving co-workers when planning for return-to-work interventions. Otherwise the proper attention to work arrangements, social communication and the role of co-workers in the return-to-work process might not be seen.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.015 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".