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Record W3028265432 · doi:10.5334/sta.766

‘They Were Going to the Beach, Acting like Tourists, Drinking, Chasing Girls’: A Mixed-Methods Study on Community Perceptions of Sexual Exploitation and Abuse by UN Peacekeepers in Haiti

2020· article· en· W3028265432 on OpenAlexaffvenue
Carla King, Sabine Lee, Susan A. Bartels

Bibliographic record

VenueStability International Journal of Security and Development · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsQueen's University
Fundersnot available
KeywordsPeacekeepingLegitimacyPerceptionSexual abusePolitical scienceNarrativeGender studiesCriminologySociologyPsychologySuicide preventionPoison controlPublic administrationLawMedicineEnvironmental healthArt

Abstract

fetched live from OpenAlex

The United Nations Stabilization Mission in Haiti (MINUSTAH) has been marred by reports of sexual exploitation and abuse (SEA) perpetrated against local women/girls. However, there is very limited empirical evidence on the community’s perceptions regarding these sexual interactions. Through a mixed-methods approach, this article examines community experiences and perceptions of SEA, with three prominent themes arising: peacekeepers as tourists, peacekeepers as sexual exploiters and abusers, and peacekeepers as ideal partners. Uruguayan (n = 107, 28.1 per cent) and Brazilian personnel (n = 83, 21.8 per cent) were most commonly named in SEA narratives. We explore how these perceptions of MINUSTAH peacekeepers undermine the purpose and legitimacy of UN peace support operations, and propose strategies to prevent and address peacekeeper-perpetrated SEA.

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)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.002
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 head0.055
GPT teacher head0.361
Teacher spread0.306 · 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 designQualitative
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

Citations21
Published2020
Admission routes2
Has abstractyes

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Same venueStability International Journal of Security and DevelopmentSame topicGender, Security, and ConflictFrench-language works237,207