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Record W4298001832 · doi:10.3390/women2040030

Being a Black Mother Living with HIV Is a “Whole Story”: Implications for Intersectionality Approach

2022· article· en· W4298001832 on OpenAlexaffabout
Josephine Etowa, Doris M. Kakuru, Egbe B. Etowa

Bibliographic record

VenueWomen · 2022
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsToronto Metropolitan UniversityUniversity of VictoriaUniversity of Ottawa
FundersFlorida International University
KeywordsIntersectionalityGender studiesSociologyEthnic groupParticipatory action research

Abstract

fetched live from OpenAlex

While African, Caribbean, and Black (ACB) mothers living with HIV in Canada are required to follow public health guidelines by exclusively formula feeding their infants, they also face cultural expectations from peers and family members to breastfeed. They face multiple challenges because of their race, ethnicity, gender, class, and geographical location, among other factors. Previously published studies on this subject did not analyze how the intersectionality of these factors impacts Black mothers’ infant feeding experiences. In this article, we discuss the infant feeding practices of Black mothers living with HIV in Ottawa (Canada). We followed a qualitative methods research design that utilized intersectionality and a community-based participatory research approach. We used the intersectionality framework as a lens to analyze the complex mesh of determinants influencing motherhood experiences of ACB women living with HIV. Being a Black/ACB mother while living with HIV is a “whole story” permeated with cutting-across issues such as race, class, gender, socio-political, and cultural contexts. These issues are interwoven and often difficult to unravel. Multiple layers of structural determinants of Black/ACB women’s HIV vulnerability and health are described. Intersectionality is important for an in-depth understanding of societal power dynamics and their impact on women’s health inequities.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.313
Teacher spread0.287 · 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 designNot applicable
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

Citations7
Published2022
Admission routes2
Has abstractyes

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