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Record W2738616233 · doi:10.1177/1057567717719966

Intimate Partner Violence and Intergenerational Trauma Among Indigenous Women

2017· article· en· W2738616233 on OpenAlexaffabout
Renée Hoffart, Nicholas A. Jones

Bibliographic record

VenueInternational Criminal Justice Review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Regina
FundersAustralian Government
KeywordsIndigenousDomestic violenceNormalization (sociology)Thematic analysisGovernment (linguistics)PopulationCriminologySexual violenceSuicide preventionPoison controlSociologySocioeconomicsPsychologyPolitical scienceGender studiesQualitative researchMedicineEnvironmental healthDemographySocial science

Abstract

fetched live from OpenAlex

The establishment of the Indian Residential Schools by the Canadian federal government to assimilate indigenous peoples to European and Christian ideals has had generational repercussions on Canada’s indigenous peoples. Many emotional, physical, and sexual abuses occurred within these schools resulting in significant trauma within this population. In order to shed light on these impacts, indigenous women were interviewed about their experiences with these schools. Thematic network analysis was used to analyze the data, and a number of themes emerged, including identifying the relationships between residential schools, intergenerational trauma, and the normalization of intimate partner violence (IPV) in domestic relationships. The findings add to the existing discourse on IPV in indigenous populations and may be used to inform violence reduction strategies.

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: Empirical
Teacher disagreement score0.919
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.385
Teacher spread0.342 · 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

Citations27
Published2017
Admission routes2
Has abstractyes

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