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Record W7096286178

Maya Oza Ollek Forced Migration Student Conference 1 The Role of Non-Governmental Organizations in Preventing Partner Violence Against Immigrant and Refugee Women in Canada

2014· article· en· W7096286178 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeDomestic violenceGovernment (linguistics)ImmigrationLaw enforcementSilenceIntervention (counseling)Public policyMaya
DOInot available

Abstract

fetched live from OpenAlex

Until the 1970s, violence occurring within the home was regarded as a purely private issue which was not to be addressed within the public sphere. Thousands of Canadian women suffered repeated abuse at the hands of their partner. With few crisis intervention services available to them and little in the way of law enforcement involvement, these women were left to suffer in silence as the country ignored their plight. During the 1980s, the women’s movement in Canada played an instrumental role in exposing the problem of partner violence to the Canadian public (Agnew 1998: 4). The gradual recognition of partner violence as a social problem alongside growing public awareness of the issue prompted the involvement by the Canadian government (Hagen 2001: 120). Partner violence shifted from the confines of the home to the forefront of the public conscience. Canadian society’s understanding of issues related to partner violence has improved drastically since the issue first emerged in the public sphere some three decades ago. Nevertheless, there remain large gaps within existing knowledge of this issue. Most noticeably, very little has been written from either the policy or academic perspective regarding the particular obstacles faced by immigrant and refugee women suffering from partner violence in Canada.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.057
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.002
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.001

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 head0.006
GPT teacher head0.253
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2014
Admission routes1
Has abstractyes

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