Oil Development and Intimate Partner Violence: Implementation of Section 8 Housing Policies in the Bakken Region of North Dakota and Montana
Bibliographic record
Abstract
One of the challenges survivors of intimate partner violence (IPV) often face is securing safe and affordable housing. Many survivors qualify for public housing programs such as the Section 8 Project-Based Rental Assistance (PBRA) program and tenant-based Housing Choice Voucher Program (HCVP). These programs can be vital for survivors fleeing abuse and trying to rebuild their lives. But how might regional conditions such as rapid population growth resulting from an oil boom affect the implementation of such programs for survivors? In addition, what role might such policies play in preventing future violence in resource boom communities? Analyzing existing policies and qualitative data collected from in-depth interviews with survivors, community members, and service providers in the Bakken region of North Dakota and Montana, we evaluate the implementation of Section 8 housing programs in oil-affected communities for survivors of IPV. We find that survivors of IPV often had a difficult time accessing affordable housing in the Bakken. Eligibility restrictions prevented some survivors from utilizing Section 8 housing programs, some landlords opted out of Section 8 program participation at the height of the oil boom, and the housing crisis may have simultaneously contributed to low utilization of housing vouchers. These conditions increased vulnerability for IPV survivors. We conclude by exploring the impact of the Violence Against Women Act (VAWA), state, and local initiatives on housing access and affordability, and the efficacy of Section 8 housing programs during the oil boom. Understanding the relationship between natural resource development, rapid population increases, housing inflation, and Section 8 housing programs should be considered as policy makers prioritize social programs in boomtown communities that may affect the well-being and safety of IPV 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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".