Preventing and responding to early and forced child marriage of Iranian-Canadians in Canada
Bibliographic record
Abstract
The United Nations General Assembly (2017) and the Committee on the Rights of the Child on its General comment No. 13 (2011) recognize early and forced child marriage (EFCM) as a harmful practice and a form of violence against children. They are deeply concerned by multiple potentially long-lasting effects of EFCM on the children’s physical, emotional, and psychological health and development. The present qualitative study, based on 16 interviews with members of the Iranian-Canadian community, examines the participants’ opinions and perceptions on EFCM as a basis for identifying prevention measures to address the problem of EFCM within that community. The results of this study revealed that EFCM among that segment of the Iranian-Canadian community is linked to the strict compliance with cultural and religious customs and norms, protection of collective morality, honour, and reputation of a family, as well as parents’ fear and insecurity for the future of their children and their considerattion of the potential socioeconomic benefits derived from the marriage. All participants acknowledged that EFCM may result in long-lasting harmful effects on the development, safety, and health of children, especially girls. They also acknowledged the need for discussing, preventing, and responding to EFCM by improving support services for the victims and encouraging them to report violence and seek help in Canada. Finally, many participants believed that there is a need to develop culturally appropriate and relevant interventions and engage the community’s cultural and religious leaders in challenging the social norms, mentalities and attitudes that continue to tolerate or condone EFCM within the Iranian-Canadian community.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".