What, How and Why of a Psychologically Informed Environment (PIE) Within Youth Refuge
Bibliographic record
Abstract
Being homeless is broadly understood to be traumagenic. Thus, support services for individuals experiencing homelessness (such as youth refuge) are encouraged to use trauma-informed models of care. However, there is a dearth of research that (1) focuses on youth refuge specifically, despite refuges being the most common response for youth homelessness worldwide, and (2) explains trauma-informed care models in detail so that they may be evaluated in practice. This paper outlines a trauma-aware framework used for nearly a decade within a youth refuge located in Melbourne, Australia: a psychologically informed environment (PIE). The paper provides: (1) an overview of trauma-informed care before describing what a PIE entails; (2) the how of a PIE, including core principles, their theoretical underpinnings, and how these principles are practically applied; and (3) the why of a PIE, focusing on implications for practice. A PIE is underpinned by key theoretical approaches such as attachment theory, the core emotional needs model, psychodynamic theory and formulation, social cognitive theory, and the transtheoretical model of change. A PIE encompasses five core principles of (1) relationships, rules, responsiveness, and roles; (2) physical and social spaces; (3) learning and enquiry; (4) staff support and training; and (5) psychological awareness. Overall, PIEs have been found to increase consumer engagement and decrease evictions, instill confidence and improve empathy within the staff, and decrease the risk for organizations, as seen by low incident rates. It is hoped that by providing this detailed outline of a PIE, more research can be undertaken into youth refuge care models, and more psychologically informed frameworks that address the multi-directional relationship between trauma and homelessness can be employed.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| 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".