Service providers challenging Orientalism and supporting HRVO victims and perpetrators
Bibliographic record
Abstract
Violence against racialized women that is known as “honour”-killing or “honour”-related violence and oppression (HRVO) is typically depicted in dominant media discourses as being the result of the cultures of the victims and perpetrators. Culture is framed as causing HRVO because dominant media discourses in the Western world tend to depict racialized communities through an Orientalist lens. Orientalist discourses are problematic because they contribute to the oppression of racialized communities by framing them as homogeneously dangerous, uncivilized, and barbaric. Most literature on HRVO takes a discursive approach, analyzing and critiquing how Orientalist narratives are advanced in government reports and policies as well as the mainstream media. While this research has important implications in identifying Orientalism and suggesting alternative perspectives, this dissertation investigates the perspectives service providers use to understand and deal with HRVO and what role these perspectives play in challenging Orientalism. The conceptual framework for this study is the theory of Orientalism combined with the heterogeneity of culture, the migration context, and intersectionality perspectives. In addition, critical realism is used to guide the methodology, particularly data analysis. In this dissertation, 13 service providers in British Columbia, Alberta, and Ontario—from settings such as ethnocultural organizations, shelters, law enforcement, education, and mental health—were interviewed, while an additional 10 service providers participated in group interviews. The study found that the most effective perspectives for service providers to use to challenge Orientalism were two-fold: (a) the heterogeneity of cultural approach, which recognizes internal differentiations within cultures; and (b) the migration context approach, which focuses on social forces that may shape and influence attitudes that support HRVO. Further, critical realism reveals several non-discursive factors—namely, embodiment (experiences of the body), materiality (physical nature of the world), and power (institutions and how through policy and force they control access to resources)—that service providers encounter and must manage to effectively counsel and support victims of HRVO. Recommendations are identified regarding education and risk assessment tools that can assist service providers to advance the heterogeneity of culture and migration context approaches as well as manage non-discursive factors.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.032 | 0.017 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".