“Don’t You Love Me?” Abusers’ use of shame-to-guilt to coercively control 2SLGBTQQIA+ individuals and rural women experiencing intimate partner violence
Bibliographic record
Abstract
BACKGROUND: Abusers' use of manipulative behaviors to trigger feelings of shame-to-guilt (a process through which abusers shame their partners to incur feelings of guilt) among their 2SLGBTQQIA+ and rural women intimate partners is a type of emotional abuse used to coercively control their partners. OBJECTIVE: This study investigated the different tactics that abusers use to shame-to-guilt their partners who identify as 2SLGBTQQIA+ and/or reside in rural areas. DESIGN: A qualitative design was used to conduct this study. METHODS: = 24). RESULTS: Seven themes were identified based on participants' experiences, including shaming identity in relation to gender and sexual orientation (manifesting differentially between 2SLGBTQQ+ and rural women participants), emotional and sexual manipulation, threats of death by suicide (predominating among 2SLGBTQQ+ individuals), apologies and vacuous promises as components of the cycle of abuse, using one's parenting and children's well-being to manipulate partners, the use of health conditions and faking illness, and the use of religion or faith to reinforce gender standards. CONCLUSION: For 2SLGBTQQIA+ and rural women groups, situating shame-to-guilt behaviors within the cycle of abuse is important information that has not been explored extensively in the intimate partner violence literature. For individuals self-identifying as 2SLGBTQQIA+ or women living rurally, the means through which they are shamed-to-guilt intersects with their unique identities and positionality. Therefore, recommendations are presented to help these groups rebuild their identities when shame-to-guilt behaviors were experienced as part of the abusive dynamic.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".