A Comparison of Adjudicated Spousal Abusers and Controls using the MJvl.Pl-2 and MCML-Ul
Bibliographic record
Abstract
Approximately 21.000 women per week are assaulted by their domestic partners in the United States (Stamp & Sabourin, l 995). Beasley and Stoltenberg ( 1992) advised that "work with abusive men could benefit from careful attention to the role of anger and personality disorders in this population" (p.316). Research generally indicates that male spousal abusers have been characterized in various ways and nave been created with varying levels of success. In order to design effective prevention and treatment plans, it is important to comprehend the nature of spousal abuse, and what research has to say about intimate abusers and their personality characteristics. This study compared 68 men (abusers n=39. non-abusers n=29) from Northern British Columbia, Canada, using two self-report personality measures: the Minnesota Multiphasic Personality Inventory Second Edition (MMPI-2) and the Millon Clinical Multiaxial Inventory Third Edition (MCMI-III). An archival database was used, which was developed by Bogyo ( l 998) and which matched abuser and non-abuser subjects by age (plus or minus 24 months) and ethnic background. The present study found significant differences between abusers and non-abusers. as well as two clusters of abusers in the archival database as suggested in the literature. The dominant cluster could be characterized as resembling the cluster of abusers described in the literature as internally conflicted. disturbed. schizoid/borderline. asocial/avoidant/aggressive/negativistic. dysphoric/borderline. emotionally volatile. and impulsive/under-controlled (Dutton. l998). In this sample the MCMI-Ill was more effective than the MMPI-2 both for discriminating abusers from non-abusers and for characterizing their personality attributes. MCMI-Ill scales measuring willingness to self-disclose. Posttraumatic Stress Disorder. passive-aggressive features. drug and alcohol abuse. sadistic tendencies. self-critical statements. and unusual thinking patterns predicted abuse in this sample. It may be useful to administer a personality measure such as the MCMI-Ill in a community mental health or other clinical setting to match potential and/or actual spousal abusers to appropriate treatment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".