Evaluating the Role of Goal Setting in Reducing Dropout for Men With and Without Substance Use Problems Attending a Court-Mandated Intimate Partner Violence Perpetrator Program
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High dropout rates, particularly among intimate partner violence (IPV) perpetrators with alcohol and other drug use problems (ADUPs), challenge IPV perpetrator programs’ effectiveness. This study sought to examine factors associated with goal setting, a motivational strategy to promote engagement, in a sample of IPV perpetrators (n = 285), including participants with ADUPs (n = 127) and investigated whether goal setting predicted lower dropout by adjusting for relevant variables. Results revealed goal setting could be an effective strategy to reduce dropout in IPV perpetrators and those with ADUPs and support the need to tailor interventions to participants’ needs to enhance effectiveness.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it