Language as a Linguistic Barrier in Black Immigrants Accessing Domestic Violence Services
Bibliographic record
Abstract
This research paper investigates the impact of language barriers on help-seeking behaviors among Black immigrants, with a focus on their experiences in various domains, including accessing and utilizing domestic violence services. The research engages ten service providers, including frontline workers from domestic violence agencies. The study adopts a qualitative approach, incorporating interviews and focus groups, to comprehensively explore the complexities of language barriers and Black immigrant help-seeking behaviors through service providers’ perspectives. The qualitative findings reveal that language proficiency plays a pivotal role in shaping the help-seeking behaviors of Black immigrants. Participants with limited language skills expressed challenges in articulating their needs, understanding available resources, and navigating different service systems. Moreover, cultural stigmatization surrounding help-seeking in certain communities further discourages Black immigrants from accessing support services, contributing to underutilization. The research highlights the importance of culturally sensitive service provision and the need for social work practitioners to receive training in cultural competence. Bridging the linguistic divide and creating inclusive service delivery models are crucial steps toward providing equitable access to support resources for Black immigrants. Furthermore, the study calls for future research to explore effective interventions and strategies to overcome language barriers and encourage help-seeking behaviors in this vulnerable population.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".