From Pillar to Post: Understanding the Victimisation of Women and Children who Experience Domestic Violence in an Age of Austerity
Bibliographic record
Abstract
The dismantling of the welfare state across the United Kingdom (and indeed a number of other Western industrialised democracies, such as Canada and the United States) and the reductions to welfare provisions and entitlements are having a detrimental impact on women's equality and safety. Towers and Walby argue that the recent cuts to welfare provision in the United Kingdom, particularly for women's services, could lead to increased levels of violence for women and girls. This paper makes the argument that female victims of domestic abuse experience violence on two levels: first, at the intimate/personal level through their relationship with an abuser and, second, at a structural level, through the state failing to provide adequate protection and provision for women who have experienced violence in intimate relationships. Using a specific example of post-violence community services delivered to both the children of women who have experienced domestic violence and the women themselves, this paper draws on empirical research carried out in 2010–2011 with London-based third-sector and public sector organisations delivering the Against Violence and Abuse Project ‘Community Group Programme’. We argue that the lack of services for women involved in, or exiting, a violent relationship can amount to state-sanctioned violence, if funding is withheld, or indeed, stretched to breaking point.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".