Organizational culture, climate and person-environment fit: Relationships with employment outcomes for mental health consumers
Bibliographic record
Abstract
Although the effects of organizational culture, climate and person-environment fit have been widely studied in the general population, little research exists in this area regarding consumers of mental health services. This research focuses on organizational culture, climate and person-environment fit and their relationship to employment outcomes for mental health consumers. It also examines specific components of organizational culture which are both desired and perceived by mental health consumers. Thirty-six (N=36) consumers were recruited into one of two groups: individuals who were employed at the time of the study and those who had recently left their jobs. Instruments used were the Workplace Climate Questionnaire (WCQ) and the Organizational Culture Profile (OCP). Significant differences were found between groups along the dimensions of organizational culture/climate and person-environment fit. Although few differences were found between groups with regards to desired workplace characteristics, many differences in perceived characteristics were found. The findings point to the importance of assessing the organizational culture/climate and its congruence with individuals' value systems as part of the work integration process.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".