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Record W1969469446 · doi:10.1080/13691058.2010.525665

Managing stigma in adolescent HIV: silence, secrets and sanctioned spaces

2010· article· en· W1969469446 on OpenAlexafffundabout
Sarah J. Fielden, Gwenneth E. Chapman, Susan Cadell

Bibliographic record

VenueCulture Health & Sexuality · 2010
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversité du Québec à MontréalWilfrid Laurier UniversityUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsSilenceStigma (botany)Context (archaeology)OppressionNarrativeSocial psychologySociologyGender studiesPsychologyPsychiatryPolitical scienceAestheticsHistoryPoliticsLaw

Abstract

fetched live from OpenAlex

HIV is conceived as a disease that combines stigma elements of perceived contagion and socially undesirable behaviours. Drawing on in-depth interviews with professional adolescent service providers from Australia, Canada, the UK and the USA, this paper explores HIV stigma and stigma management in the lives of HIV-positive young people. Findings elucidate how additional layers of stigma relating to 'adolescent rights' and 'embodied innocence' are added to HIV stigma as it is more usually conceived. This study suggests that managing this stigma entails managing silence in the context of the social worlds of the young person, the family and the service provider. Silence emerged as a key theme in the participant narratives and was embedded in the descriptions of young people's lived experiences. Crucially, silence is a product of oppression and inequity but is also a tool for resistance. Silence defends secrets and exists in the spaces, both physical and social, that are created for them in order to manage the stigma in young people's lives. Silences associated with HIV therefore need to be exposed if we are to better understand what HIV truly means to seropositive young people and how 'silences' may minimise or exacerbate their experience of HIV stigma inside and outside the context of programmes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.374
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.042
GPT teacher head0.398
Teacher spread0.357 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations80
Published2010
Admission routes3
Has abstractyes

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