Beyond Window Dressing: Does Moving to a New Building Really Shape the Perception of, and Actual Safety on Forensic Inpatient Programs?
Bibliographic record
Abstract
Waypoint Centre for Mental Health Care expanded its facility in 2014 to include a new state-of-the-art forensic hospital building, called the Atrium. Prior to moving Waypoint’s forensic programs into the Atrium, the Therapeutic Climate Study (TCS) was launched in order to monitor changes in perceived and objective safety indicators among forensic staff and patients. The present study consisted of a 5-year cross-sectional sequential design, consisting of both survey and hospital administrative data. Across all years of data collection, inpatients ([Formula: see text] = 256) reported higher perceived safety when compared to staff ([Formula: see text] = 932). However, changes in perceived safety were not linear and only slightly improved for staff over time. Sociodemographic characteristics and perceived recovery measures predicted perceived safety for staff and inpatients, regardless of the move. Male staff reported higher perceived quality of patient-service provider relationships and lower perceived safety, whereas female staff reported higher perceived patient cohesion and higher perceived safety. Both staff and inpatients who perceived the hospital’s principles and practices as more recovery-oriented reported higher perceived safety. Inpatients who have been at the hospital longer reported lower perceived safety, regardless of the move. Hospital administrative data showed the number of incidents in a centralized emergency response system spiked right after the move but eventually tapered off, whereas the rates of violent incidents had increased and remained higher since moving to the new building. Results from this study suggest that staffs’ and inpatients’ sense of safety is determined by multiple factors, of which physical environment seems to play a less central role.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".