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Record W4389078085 · doi:10.3390/healthcare11233053

Conducting Ethical Field Research on Rape in West African Settings: Case Study of 2018 Liberian Field Survey

2023· article· en· W4389078085 on OpenAlexfundno aff
Jessi Hanson-DeFusco, E. G. Smith, Richard Ngafuan, William N. Dunn

Bibliographic record

VenueHealthcare · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsnot available
FundersForeign and Commonwealth OfficeMcMaster UniversityUniversity of PittsburghForeign, Commonwealth and Development OfficeUNICEF
KeywordsScholarshipContext (archaeology)AttritionField (mathematics)Research designData collectionQualitative researchField researchPublic relationsPsychologySociologyPolitical scienceSocial scienceMedicineGeography

Abstract

fetched live from OpenAlex

BACKGROUND: Rape scholarship in West Africa is growing, but studies often utilize Westernized approaches. A 2018 study using a randomized survey design assessing rape among Liberian girls incorporated modified survey design methods to improve ethical data collection relevant to the cultural and contextual contexts. This article presents the findings of a thorough review of rape scholarship and design methods. METHODS: Based on a qualitative analysis of field notes by the research team, we present lessons learned and best practices identified in the planning, pilot-testing, and implementation phases of the 2018 Liberian study. RESULTS: This study helps inform innovative design methods striving to (1) avoid using obtrusively graphic language or labels prevalent in westernized studies, (2) authentically collaborate with African experts to adapt strategies to be culturally appropriate and contextually relevant, and (3) create respectfully transparent interactions with respondents and communities. Extensive research preparation and inclusive regional expertise inform compassionate methodological techniques, yielding improved Afro-centric participant experience, low participant attrition, and quality data use in policymaking. (4) Conclusions: This article offers innovative design methods to study rape, placing context, culture, and participants at the heart. Authentic collaboration with national-level experts is vital for conducting more reliable and ethical field research in the African region.

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)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.554
GPT teacher head0.563
Teacher spread0.009 · 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.

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

Citations2
Published2023
Admission routes1
Has abstractyes

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