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Rights and Wrongs: HIV/AIDS Research in Africa

2005· article· en· W2021108750 on OpenAlexaff
Louise de la Gorgendière

Bibliographic record

VenueHuman Organization · 2005
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsCarleton University
Fundersnot available
KeywordsDignityResearch ethicsHarmContext (archaeology)Informed consentMedical researchHuman rightsHuman immunodeficiency virus (HIV)Political scienceSociologyCriminologyMedicineLawFamily medicinePsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

This paper, which is based on a pilot study in Africa, raises a host of ethical issues in relation to ‘applying’ anthropology and collaborative HIV/AIDS research. The author identi?es major issues related to the reproductive rights of women and the welfare of their infants in the context of HIV/AIDS research in Africa. The account considers the implications of apparently well-intentioned research that fails to safeguard the well being and dignity of the people involved. It exposes serious problems concerning the lack of informed consent in a medical research project on antenatal testing and mother-to-child-transmission of HIV. Furthermore, the study draws attention to the need for repeated screening for new ethical issues in ongoing medical (and other) research projects involving research participants whose rights might be overlooked in outdated ethics considerations. The paper cautions anthropologists (and other researchers) about being “co-opted” by those in authority, and serves as a reminder about the ‘do no harm’ dictum.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.069
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.366

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0690.068
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0260.059
Scholarly communication0.0150.027
Open science0.0010.019
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0050.000

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 head0.057
GPT teacher head0.368
Teacher spread0.311 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2005
Admission routes1
Has abstractyes

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