Remote Work in a Changing World: A Nod to Personal Space, Self-Regulation and Other Health and Wellness Strategies
Bibliographic record
Abstract
Remote work has escalated as a result of the coronavirus pandemic, and citizens have been doing their part to mitigate the spread of viral infection. The downside of quickly switching from a workplace office to remote work is that neither employees nor employers have had time to consciously process the new work environment and formally evaluate health and safety concerns. The aim of this commentary was to make suggestions on how to make remote work more satisfying, safe, and healthy for employees. First, I explored existing research on disease outbreaks and mental stress as the backdrop for discussing health-related strategies. To determine which types of strategies or measures would help, next I examined existing organizational research, including a qualitative study by my colleagues on workers' perceptions about what makes a healthy workplace. Themes that emerged from the qualitative study align with three broad recommendations discussed in this commentary: cultivating personal space, building in ergonomics, and boosting self-regulation (self-learning) skills. Finally, I suggested that future research should explore the joint roles of the worker and his/her management team in recognition of organizational commitment to occupational health and safety alongside each worker's need for autonomy in their personal workspace.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".