Taking a PAWS to Reflect on How the Work of a Therapy Dog Supports a Trauma-Informed Approach to Prisoner Health
Bibliographic record
Abstract
Canada's Correctional Investigator has found that mental health disorders, alone or in combination with alcohol and drug abuse, challenge public health and safety. Trauma is a key contributor among Canada's inmate population. Therapy dogs can assist in supporting individuals with mental health, addiction, and trauma concerns. This case report presents the work of a St. John Ambulance therapy dog in a trauma-informed approach to prisoner health. The Substance Abuse and Mental Health Services Administration articulates six evidence-based trauma principles for service providers; safety; trustworthiness and transparency; peer support; collaboration and mutuality; empowerment, voice, and choice; and cultural, historical, and gender issues. These principles are used as a lens to examine what the therapy dog appears to offer instinctively and effortlessly in its interactions with prisoners. Illustrative examples are provided.Video Abstract available for additional insights from the authors (see Supplemental Digital Content 1, http://links.lww.com/JFN/A16).
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.035 | 0.033 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.009 | 0.019 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".