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Record W2583344653 · doi:10.1080/16549716.2017.1270816

‘Life under the tent is not safe, especially for young women’: understanding intersectional violence among internally displaced youth in Leogane, Haiti

2017· article· en· W2583344653 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGlobal Health Action · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsDalhousie UniversityWomen's College HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchGrand Challenges Canada
KeywordsInternally displaced personGender studiesRefugeeSociologyPolitical scienceGerontologyEconomic growthDemographyMedicinePopulation

Abstract

fetched live from OpenAlex

BACKGROUND: Haiti's 2010 earthquake devastated social, health, and economic infrastructure and left 2 million persons homeless. Over 6 years later 61,000 people remain displaced, most lacking protection, services, and durable solutions. Structural contexts elevate risks of gender-based violence (GBV) targeting internally displaced (ID) girls and women. OBJECTIVE: We used an intersectionality framework to explore lived experiences and understanding of violence among ID young men and women in Leogane, Haiti. METHODS: We conducted six focus groups, three with ID young women (n = 30) and three with ID young men (n = 30) aged 18-24 years, and 11 in-depth individual interviews with frontline workers in Leogane. Focus groups and interviews were conducted in Kreyol, transcribed verbatim, translated into English, and analyzed using narrative thematic techniques. RESULTS: Findings revealed violence experienced by ID youth was (re)produced at the intersection of gender, poverty, displacement, and age. Multi-level forms of violence included structural (e.g. poverty), community (e.g. gender norms, and interpersonal (e.g. family expectations) dimensions. Coping strategies spanned intrapersonal (hope), community (social support), and structural (employment/education) dimensions. CONCLUSIONS: Interventions to reduce violence should be tailored to address the social inequities that emerge at the intersection of youth, poverty, displacement, and hegemonic gender norms.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.096
GPT teacher head0.395
Teacher spread0.299 · 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