An examination of domestic partner violence and its justification in the Republic of Georgia
Bibliographic record
Abstract
BACKGROUND: Little research on Intimate Partner Violence (IPV) and social perceptions toward this behavior has been disseminated from Eastern Europe. This study explores the prevalence and risk factors of IPV and the justification of this behavior among women in the Republic of Georgia. It seeks to better understand how IPV and IPV justification relate and how social justification of IPV differs across socio-economic measures among this population of women. METHODS: This study utilizes a national sample of ever-married women from the Republic of Georgia (N = 4,302). We describe the factors that predict IPV justification among these women and the relationship between of the acceptability of IPV and victimization overall and across socio-demographic factors. RESULTS: While the overall lifetime prevalence of IPV in this sample was relatively low (4%), these women were two to four times more likely to justify IPV, Just under one-quarter of the sample agreed that IPV was justified in at least one scenario, namely when the wife was unfaithful, compared with women who had no experience being abused by a partner. Georgian women who were poor, from a rural community, had lower education, were not working and who experienced child abuse or IPV among their parents were more likely to justify this behavior. CONCLUSIONS: These findings begin to fill a gap in our understanding of IPV experienced by women in Eastern Europe. In addition, these findings emphasize the need for researchers, practitioners and policy makers to contextualize IPV in terms of the justification of this behavior among the population being considered as this can play an important role in perpetration, victimization and response.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".