A Way Forward with Intersectionality: An Integrative Review of Women’s Experiences with Intimate Partner Violence
Bibliographic record
Abstract
Abstract Background: Intimate partner violence (IPV) is uniquely posited as both a public health challenge and an affront to human rights that spares no social group. Women, as victims, constitute two thirds of all instances of IPV worldwide (United Nations, 2013), though it is likely that this number is much higher as it speaks nothing of the women who are at risk of violence due to circumstances beyond their control. Intimate partner violence is a complex, ‘wicked’ problem that requires a proactive and upstream approach to address with an intersectional and gender equity lens. Such opportunities must be innovative, universally accessible, and demonstrate awareness of the multitude of intersections experienced by women (I.e., race, education, social status). This study examines the application of intersectionality as a framework to women’s experiences of intimate partner violence. Methods: The authors’ conducted an integrative review using the Whittemore and Knafl (2005) methodology. The search identified primary research papers from five databases, including Scopus, Soc Index, Criminal Justice Web of Science, and Public Health during March and April 2022. A total of 1686 articles were distilled into a final four articles that were that werereviewed and analysed extensively by two reviewers. Results: The major themes that emerged from the review included: (a) intersectionality as a critical social framework can inform holistic IPV interventions across disciplines and sectors; (b) intersectionality provides a unique lens through which to address the inherent power imbalance of IPV; and (c) interventions framed within an intersectional framework can be used to promote women’s agency and reclamation of self. Conclusions: The need for an intersectional approach to IPV is agreed upon and, given the urgency of this issue, the findings establish a way forward for intersectional research and presents connections between intersectionality and IPV. It is in these connections where interventions, policies, and programs can be developed to provide a holistic and comprehensive approach for survivors.
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 | 0.021 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.032 | 0.028 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".