Timmins (2020) Study 1 data, Human Givens Rewind treatment for posttrauamtic stress in a police force
Bibliographic record
Abstract
The purpose of this preliminary study was to investigate the effectiveness of the Rewind treatment for post traumatic stress in a police force setting. Officers and staff in the police force were referred for treatment by the Occupational Health advisors, and all those who were referred were treated with no exclusion criteria. Any staff with a possible diagnosis for PTSD were first seen by the Forces Medical Advisor for a diagnosis before making a referral for Rewind treatment. All the clients treated using Rewind in a specific police force between 2009 and 2013 were included and gave informed consent to participate in this study prior to starting treatment. All those treated by the service completed the CORE-OM before and after treatment. Those with a diagnosis of PTSD or PTS were also given the IES-R before and after treatment. The Griffin and Tyrrell (2004) HG treatment was used with the Griffin and Tyrrell (2001) protocol for the Rewind technique.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.017 |
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".