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Record W3196741465 · doi:10.32920/ryerson.14660724.v1

HIV stigma, psychological distress and social support and their relationship to fertility intentions amongst HIV positive (HIV+) women

2021· preprint· en· W3196741465 on OpenAlexaffabout
Anne Catherine Wagner

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsToronto Metropolitan University
FundersStrong
KeywordsFertilityEthnic groupSocial supportStigma (botany)ModerationHuman immunodeficiency virus (HIV)MedicineDemographySocial stigmaPsychologyGerontologyPopulationPsychiatryFamily medicineSocial psychologyEnvironmental healthPolitical scienceSociology

Abstract

fetched live from OpenAlex

The current study examined the relationship of demographic and psychological predictors to fertility intentions in HIV+ women in Ontario. 326 HIV+ women between the ages of 18 and 52 were recruited through 28 AIDS service organizations, 8 HIV clinics and 2 community health centres across the province. 58.6% of the sample intended to become pregnant. African ethnicity, living in Toronto, high social support for having a child, and high perceived HIV stigma were associated with higher fertility intentions. Higher age, and European, Canadian and British ethnicity were all associated with lower fertility intentions. No moderation effects were found in multiple regression analyses, but main effects were found for African ethnicity, lower age, living in Toronto, high perceived HIV stigma and high social support for having a child. The majority of the sample intended to become pregnant, suggesting the need for effective health care support for HIV+ women in Ontario.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.757

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.054
GPT teacher head0.368
Teacher spread0.314 · 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 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

Citations1
Published2021
Admission routes2
Has abstractyes

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