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Record W2807623990 · doi:10.2105/ajph.2018.304433

AIDS, Sexual Health, and the Catholic Church in 1980s Ireland: A Public Health Paradox?

2018· article· en· W2807623990 on OpenAlexaff
Anne Nolan, Shane Butler

Bibliographic record

VenueAmerican Journal of Public Health · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsTrinity College
Fundersnot available
KeywordsIrishPublic healthAllianceHealth policyGender studiesSociologyLawMedicinePolitical scienceCriminologyNursing

Abstract

fetched live from OpenAlex

Our aim was to explore the paradoxical role of the Catholic Church during the early AIDS era in establishing a policy network committed to the principles of public health, even in instances in which these principles contradicted Catholic moral teaching. This article is rooted in a study that explored the transformational effects of AIDS on Irish sexual health policy during the initial decade of the epidemic; that is, as it unfolded in Ireland between 1982 and 1992. Our source material, consisting of 20 documents that had been unexplored for more than 25 years, was obtained from the Dublin AIDS Alliance Ltd., an Irish civil society organization that supports HIV-positive people. Our archival research was supported by 18 semistructured key informant interviews with contemporaneous politicians, representatives of the Catholic Church, clinical personnel, and AIDS activists. We examined the critical role of a Catholic priest in developing a coherent national policy response that reflected the public health principles advocated by the World Health Organization at a time when the moral authority of the Roman Catholic Church had a significant influence on successive Irish governments. (Am J Public Health. 2018;108:908-913.).

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)0.009
metaresearch head score (Gemma)0.014
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.280

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0080.021
Scholarly communication0.0080.006
Open science0.0010.006
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.070
GPT teacher head0.341
Teacher spread0.271 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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