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Record W2069519959 · doi:10.1177/1527154408329312

Building Global Alliances in a World of Health Care Inequities

2008· article· en· W2069519959 on OpenAlexaboutno aff
Stephen Lewis

Bibliographic record

VenuePolicy Politics & Nursing Practice · 2008
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyFamineFace (sociological concept)Economic growthPandemicDeveloping countryPolitical scienceEconomic shortageNursingHealth careDevelopment economicsMedicineBusinessPublic relationsCoronavirus disease 2019 (COVID-19)SociologyEconomicsGovernment (linguistics)

Abstract

fetched live from OpenAlex

Nurses are at the heart of any effective response to the ongoing HIV/AIDS pandemic in Africa and internationally. Without nurses, we will be unable to provide treatment for the growing numbers of people with HIV/AIDS and victims of violence, famine, and poverty. As countries such as the United States and Canada face nursing shortages, they are looking elsewhere to find nurses. But poaching nurses from other countries, especially those from countries that are struggling for survival, is reprehensible and immoral. If we put our resources in the appropriate places, we can sustain the professional disciplines in the country where they are trained. We need to take an advocacy stance to demand rational policies that will support sustainable health systems.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.050
GPT teacher head0.438
Teacher spread0.388 · 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 designTheoretical or conceptual
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

Citations4
Published2008
Admission routes1
Has abstractyes

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