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Urban Outpost Nursing: The Nature of the Nurses' Work in the AIDS Prevention Street Nurse Program

2001· article· en· W2040936038 on OpenAlexaffabout
B. Ann Hilton, Ray Thompson, Laura Moore‐Dempsey, Kylie Hutchinson

Bibliographic record

VenuePublic Health Nursing · 2001
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
FundersCenters for Disease Control and Prevention
KeywordsNursingContext (archaeology)MedicineHealth careHealth promotionWork (physics)Public healthPolitical science

Abstract

fetched live from OpenAlex

The AIDS Prevention Street Nurse Program in Vancouver, Canada focuses on HIV and sexually transmitted diseases (STD) prevention within a context of harm reduction and health promotion targeted at marginalized, hard to reach, high-risk populations. As part of a large evaluation project that included interviews with street nurses, clients, and other service providers together with document analysis, the nature of the street nurses' work and its fit within the provision of health care were described. The street nurses' work reflected the following themes: reaching the marginalized high-risk populations for HIV/STDs; building and maintaining trust, respect, and acceptance; doing HIV/AIDS and STD prevention, early detection, and treatment work; helping clients connect with and negotiate the health care system; and influencing the system and colleagues to be responsive. The findings and their implications for community health nursing practice are examined.

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)0.003
metaresearch head score (Gemma)0.004
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: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.005
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.001
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 head0.074
GPT teacher head0.473
Teacher spread0.399 · 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

Citations17
Published2001
Admission routes2
Has abstractyes

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