Measuring Dimensions of a Healthy Workplace Climate: A User-Friendly Assessment Tool
Bibliographic record
Abstract
Although the concept of healthy workplaces has historical roots in the extant literature, it remains an elusive concept to define and apply in the workplace. Nonetheless, the literature does suggest that it is a challenging and continuously improving process of supporting, protecting and promoting the health of the employee. The aim of this study was to devise a user-friendly, climate-specific assessment tool to evaluate employees’ perceptions and knowledge of the practices and procedures in the workplace that prioritise the development of a healthy, supportive workplace. After extensive literature review and early stage pilot-testing of several independent sites within an organisation, a 31-item Likert-type scale — The Workplace Scale (WPS) — was brought forward to test its psychometric properties using an independent international sample that was gathered using email distribution. These initial distribution contacts were two of the author's professional colleagues and thereafter the scale was cascaded electronically to respondents in several countries. The factor analysis conducted on the data obtained from 108 respondents yielded a solid five factor solution that was consistent with earlier test administrations and revealed interpretable and distinct factors that strongly loaded on pertinent dimensions relevant to a healthy workplace. The tangible product is a user-friendly tool to baseline the development of a healthy, supportive workplace, while providing employees with an efficient upward communication mechanism to enable management to monitor progress. Devising the WPS was undertaken as part of wider study that subsequently compared the WPS against measures of climate, leadership and culture and is reported elsewhere.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".