The impact of COVID-19 on intimate partner violence in Europe
Bibliographic record
Abstract
The family and intimate relationships should be a place of safety, but for many, violence and trauma occur even within this context. Intimate partner violence (IPV) can take many forms and can include physical, sexual, and emotional abuse and a range of controlling behaviours. It affects younger and older, cis and transgender women and men. What we do know is that across the European region, more than a quarter of ever-partnered women, aged 15 and older, have experienced IPV. This has contributed to interpersonal violence being the fourth leading cause of death among people aged 15-29 years in the WHO European Region. Over the past year and a half, in a world in a constant state of emergency during the COVID-19 pandemic, increases in sexual assault and violence, particularly against women, have been reported. The WHO Europe member states have reported a 60% increase on average in emergency calls from women subjected to IPV, alongside a 23-32% increase in IPV and domestic violence (DV) cases since the lockdown began. This may not reflect the true scale of the problem as less than 40% of women seek help of any kind and men and boys may be less likely to report it. In most countries with available data on the issue, most women rely on family and friends, and rarely ask formal institutions for assistance. Even as pandemic lockdown measures are lifted, there are long-term health, wellbeing, and socioeconomic consequences that will prevail. The European Union (EU) has incorporated new measures in response to intimate partner violence. Examples are the Gender Equality Strategy 2020-2025 and the Victims’ Right Directive and EU Strategy on victims’ rights. These strategies outline a set of key actions including preventing gender-based violence, supporting and protecting victims (i.e., empowering victims to report a crime, claim compensation, and recover from consequences of crime), and holding perpetrators accountable during crises such as the COVID-19 pandemic. Both strategies are specifically focused on vulnerable victims (e.g., children, victims of gender-based violence, and/or domestic violence) as one of their key priorities.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".