Disentangling Indigenous Women’s Experiences with Intimate Partner Violence in the United States
Bibliographic record
Abstract
Although violence against Indigenous women is a global human rights and social justice issue, it must be examined within the local context. This article focuses on Indigenous women’s experiences with intimate partner violence (IPV). These women reside in an Indigenous community in the United States that is traditionally matrilineal. The article explores how the power and status of women have been constrained to the extent that many women now experience epidemic rates of IPV. Through the use of the theoretical framework of Paulo Freire, this critical ethnography examined how IPV is situated within a broader context of historical oppression, filling a gap in the literature with respect to understanding Indigenous women’s experiences of IPV in the United States by understanding IPV from the voices of women themselves and connecting IPV experiences to a framework of historical oppression. As part of a critical ethnography, reconstructive analysis of 29 life history interviews with Indigenous women revealed an intergenerational cycle of violence, dehumanizing tactics, and women breaking free from violent relationships. The importance of social work practitioners and researchers examining the challenges experienced by Indigenous peoples within the broader historical context of historical oppression, as well as implementing policies that enable greater self-determination for Indigenous peoples are highlighted.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".