Bibliographic record
Abstract
Trauma-informed care and practice was developed over 20 years ago and is emerging as a way of working for the police, in corrections and courts, and broader contexts such as health and education services. I started my criminal justice career with South Australia Police in 2001. It was not until 2014 that I first heard the term “trauma-informed,” which was regarding victim services. Back then, it was unclear how it might be applied in practice. Soon after, I was appointed to the Parole Board of South Australia in 2015. As a Parole Board member, I have interviewed more than 1,000 adults, many with chronic offending histories and most with trauma histories. In this paper, I draw from local case studies and apply the SAMHSA (2014) trauma-informed practice framework to explore “trauma-informed” policing. Trauma is understood to mean the impact of adversity (i.e., potentially traumatic events and experiences) on an individual’s functioning and well-being. I outline the ABCs of a trauma-informed policing response: (A) trauma-informed policing requires an agenda, (B) trauma-informed policing is broad, and (C) trauma-informed policing is compassionate. Without the ABCs of traumainformed policing, police responses may be, at best, well-intentioned good practice, but they should not be considered to be trauma-informed.
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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 | 0.002 | 0.000 |
| 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 | 0.000 | 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".