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Record W4412578491 · doi:10.1353/cpr.2025.a965354

Understanding Research Participation Experiences Among Persons Identifying as African, Caribbean, and Black in British Columbia

2025· article· en· W4412578491 on OpenAlexfundaboutno aff
Tsion Gebremedhen, Amber R Campbell, Patience Magagula, Rebecca Gormley, Charity V. Mudhikwa, Evelyn J. Maan, Hélène C. F. Côté, Melanie C. M. Murray, Angela Kaida

Bibliographic record

VenueProgress in community health partnerships · 2025
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchMitacsSimon Fraser University
KeywordsDescriptive statisticsCommunity engagementCommunity-based participatory researchPerspective (graphical)Descriptive researchMental healthReproductive healthPsychologyData collectionGerontologyMedicinePolitical scienceEnvironmental healthPublic relationsParticipatory action researchSociologySocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Health research in Canada has insufficiently engaged African, Caribbean, and Black (ACB) people, yielding under-representation of their priorities and unmet health needs. OBJECTIVE: To understand research experiences and priorities among ACB people in British Columbia. METHODS: Cross-sectional data from an online survey was summarized using descriptive statistics. Content analysis was used for open-ended text responses. Data collection and analysis was conducted with ACB community partners. RESULTS: Of 56 respondents, 50.0% were aged 16 to 25 years; 78.6% identified as women. Although only 42.9% had previous research experience, 91.1% were willing to participate. Participation barriers included time constraints (53.1%) and mistrust (30.6%). Facilitators included perceived benefits to ACB individuals/communities (83.9%) and opportunities to share perspective(s) (60.7%). Research priorities included mental health, substance use, and sexual and reproductive health. CONCLUSION: Findings highlight ACB individuals' willingness to participate in health research, while identifying participation barriers and facilitators. Researchers must build trust through anti-racist community engagement efforts.

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)0.019
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0070.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.006
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 head0.597
GPT teacher head0.563
Teacher spread0.035 · 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 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

Citations1
Published2025
Admission routes2
Has abstractyes

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