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Record W4396866889 · doi:10.1002/ajcp.12753

“We are mothers, sisters, and lovers too”: Examining young Black women's experiences navigating sex and sexual health

2024· article· en· W4396866889 on OpenAlexafffundabout
Natasha Afua Darko, Ciann Wilson, Vanessa Oliver

Bibliographic record

VenueAmerican Journal of Community Psychology · 2024
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsWilfrid Laurier University
FundersOntario HIV Treatment Network
KeywordsReproductive healthHuman sexualityThematic analysisGender studiesHealth psychologyPsychologyPublic healthBlack womenFocus groupQualitative researchSociologyPopulationMedicineDemographyNursing

Abstract

fetched live from OpenAlex

In Canada, there is a lack of research that addresses the sexual health and well-being of African, Caribbean, and Black young women. This paper aims to gather perspectives of young Black women to address the social contexts of how young Black women navigate issues related to sex and sexual health. Young Black women experience unique dynamics in navigating their sexualities and sexual healthcare. The nuanced experiences stem from social contexts with historical underpinnings, such as the perception of Black women's bodies, Black identity, gender roles, and sexual double standards. This Community-Based Participatory Research study (N = 24) utilized focus groups to examine young Black women's experiences navigating sexual health. Employing a thematic analysis, participants identified four themes representing their narratives of navigating sexual health. The themes included the perceptions and hypersexuality of Black women's bodies, navigating sexual double standards and gender roles as Black women, diverse Blackness, and migration experiences concerning sexual health and surveillance of Black women's bodies. This paper is intended to add to scholarly discourse and will include practical strategies for use by researchers and community practitioners in sexual health within the Black community.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
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 head0.138
GPT teacher head0.478
Teacher spread0.341 · 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

Citations4
Published2024
Admission routes3
Has abstractyes

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