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Record W4402278029 · doi:10.1136/bmjgh-2024-015068

Effective community entry: reflections on community engagement in culturally sensitive research in southwestern Nigeria

2024· article· en· W4402278029 on OpenAlexafffund
Olubukola Omobowale, Alissa Koski, Halimat Omowumi Olaniyan, Bidemi Nelson, Olayinka Egbokhare, Olayinka Omigbodun

Bibliographic record

VenueBMJ Global Health · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsMcGill University
FundersGrand Challenges Canada
KeywordsPublic relationsCommunity engagementCLARITYCoproductionDocumentationCulturally appropriatePsychological interventionSociologyPolitical scienceNursingMedicine

Abstract

fetched live from OpenAlex

Effective community entry processes influence community participation and acceptance of public health interventions. Though there is a growing body of literature on the importance of community partnerships, there is a lack of pragmatic and practical documentation of the experiences involved in the community entry process as it relates to culturally sensitive topics such as child marriage which can help to support researchers working in this field. This article highlights key themes related to knowledge of the community, effective communication, cultural sensitivity, coproduction and giving feedback which help to build trust between the community members and the research team. Institutional representation, not managing expectations, and lack of clarity, along with personal opinions of community gatekeepers can create challenges for the fostering of trustworthy relationships with the community. These realities must be actively addressed right at the onset of the process between the research team and community stakeholders. Researchers can develop trust, form connections and engage different communities by working with local groups and leaders, using culturally appropriate methods, and addressing community concerns. Future projects working with communities on child marriage in Nigeria and other countries would benefit from the reflections presented in this paper.

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)0.047
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0470.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.008
Insufficient payload (model declined to judge)0.0000.001

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 head0.764
GPT teacher head0.753
Teacher spread0.011 · 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.

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

Citations8
Published2024
Admission routes2
Has abstractyes

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