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Record W400645340

Black Women and HIV / AIDS: Contextualizing their Realities,their Silence, and Proposed Solutions

2001· article· en· W400645340 on OpenAlexvenueaboutno aff
Esther Tharao, Notisha Massaquoi

Bibliographic record

VenueCanadian women's studies · 2001
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsnot available
Fundersnot available
KeywordsAscriptionSilenceDeveloping countryGender studiesPoliticsDiseaseSociologySocial issuesEconomic growthDevelopment economicsPolitical scienceMedicineLaw
DOInot available

Abstract

fetched live from OpenAlex

In the more than 20 years since the emergence of the HIV/AIDS epidemic the disease has become endemic in many developing countries especially in Sub- Saharan Africa and the Caribbean fuelling a fear of the spread of HIV/AIDS across borders. This factor alone has numerous implications for Black women living in Canada and other industrialized nations. Labels cultural meanings and interpretations about the disease formed since its emergence continue to influence both the discourse on HIV/AIDS and the access to programs and services geared to its control for those most vulnerable to or at risk of infection. In the mid-80s as the discourse unfolded we as African women living in Canada were not so much concerned with contracting the HIV virus as we were with the racist undertones of media reports depicting HIV/AIDS as just another tragedy that was plaguing the poor the powerless and those living on the margins of society namely Africans IV drug users and gay men. The total absence of any consideration of the social and political realities that left African people so devastated by this disease coupled with the calculated correlation between the magnitude of the infection rates and the ascription of the exact origins of the disease created an emphasis on the duality of “us” versus “them”—-a discourse informed by centuries of mistrust based on our historical experiences of colonization and slavery. (excerpt)

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.119
GPT teacher head0.365
Teacher spread0.246 · 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

Citations10
Published2001
Admission routes2
Has abstractyes

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