❖ Sex Therapy Intimate Partner Violence and Women’s Sexual Health: Implications for Couples Therapists
Bibliographic record
Abstract
Intimate partner violence (IPV) affects approximately one in four women every year and approximately one third of all female victims of homicide are killed by an intimate partner. The negative physical and mental outcomes of IPV and the sexual manifestations of these outcomes are identified. Furthermore, the implications of these outcomes for couples therapists are identified. Keywords: intimate partner violence; domestic violence; sexual violence; couples therapy Domestic violence is the willful intimidation, assault, battery, sexual assault, and/or other abusive behavior perpetrated by one intimate partner against another. It is an epidemic affecting individuals in every community, regardless of age, economic status, race, religion, nationality or educational background. Violence against women is often accompanied by emotionally abusive and controlling behavior, and thus is part of a systematic pattern of dominance and control. Domestic violence results in physical injury, psychological trauma, and sometimes death. The consequences of domestic violence can cross generations and truly last a lifetime (National Coalition against Domestic Violence [NCADV], 2007). According to the NCADV (2007), an estimated 1.3 million women are assaulted by their intimate partners each year, and one in every four women will be abused by a partner during her lifetime. Women between 20 and 24 years of age are most at risk for intimate partner violence (IPV). International in scope, IPV in the UK is reported to occur in one in four households and, in Canada, one half of Authors ’ Note: Correspondence concerning this article should be
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.022 | 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".