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Record W6995987090

Preventing and responding to early and forced child marriage of Iranian-Canadians in Canada

2019· article· en· W6995987090 on OpenAlexaboutno aff

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Gene Expression Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCircumstantial evidenceGovernment (linguistics)PopulationPoison controlWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.001
GPT teacher head0.152
Teacher spread0.150 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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