Intimate male partner violence in the migration process: intersections of gender, race and class
Bibliographic record
Abstract
AIM: This paper is a report of a study of Sri Lankan Tamil Canadian immigrants' perspectives on factors that contribute to intimate male partner violence in the postmigration context. BACKGROUND: Increasing evidence illustrates the extent and nature of intimate male partner violence and its links to a range of physical and mental health problems for women around the world. However, there has been little health sciences research on intimate male partner violence in the postmigration context in Canada. METHODS: Data were collected for this qualitative descriptive study in 2004 and 2005, through individual interviews with community leaders (n = 16), four focus groups with women and four with men from the general community (n = 41), and individual interviews with women who had experienced intimate male partner violence (n = 6). The research was informed by a postcolonial feminist perspective and an ecosystemic framework. FINDINGS: Participants' conceptualization of the production of intimate male partner violence in the postmigration context involved (a) experiences of violence in the premigration context and during border crossing; (b) gender inequity in the marital institution; (c) changes in social networks and supports; and (d) changes in socioeconomic status and privilege. CONCLUSION: Increasing immigration requires that nurses pay attention to and respond appropriately to women's unique needs, based on complex and interrelated factors that produce intimate male partner violence in the postmigration context.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".