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Record W4281399342 · doi:10.1136/bmjgh-2022-isph.29

96:oral Equity, justice, and social values in priority setting: a qualitative study of resource allocation criteria for global donor organizations working in low-income countries

2022· article· en· W4281399342 on OpenAlexaff
Lydia Kapiriri, S Donya Razavi, Donya Razavi

Bibliographic record

VenueAbstracts · 2022
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsOperationalizationEquity (law)Health equityEquity theoryPublic economicsQualitative researchPublic relationsBusinessHealth careSociologyPsychologyPolitical scienceEconomicsEconomic growthEconomic JusticeSocial scienceMicroeconomicsLaw

Abstract

fetched live from OpenAlex

<h3>Background</h3> There is increasing acceptance of the importance of social values like equity and fairness in health care priority setting (PS). However, equity is difficult to define; it means different things to different people. How equity is understood in theory, may not align with how it is operationalized. There is limited literature on how development assistance partner organizations (DAP) conceptualize and operationalize equity in their health care prioritization decisions for low-income countries (LIC). We explore whether and how equity is a consideration in DAP’s PS processes. <h3>Methods</h3> A qualitative study involving 35 in-depth interviews with DAPs involved in health-system PS for LICs and review of their respective webpages. <h3>Results</h3> While several PS criteria were identified, direct articulation of equity as an explicit criterion was lacking. However, equity was implied, by some responses, through prioritizing of vulnerable populations. Where mentioned, respondents discussed the difficulties of operationalizing equity, since vulnerability is associated with several, competing factors including gender, age, geography, and income. Some respondents suggested that equity could be operationalized through organizations’ lack of support for programs that reinforce pre-existing inequities. Although several organizations’ webpages identify addressing inequities as a guiding principle, they varied in their discussion its operationalization. While intersectionalities in vulnerabilities complicate its operationalization, if the various organizations explicitly articulate their equity focus, each organization may concentrate on different dimensions of vulnerability. Thus, all organizations will contribute to achieving equity in all the relevant dimensions. <h3>Conclusions</h3> Since most DAPs support some form of equity, we highlight a need for an internationally recognized framework that recognizes the intersectionalities of vulnerability, for mainstreaming and operationalizing equity in DAP priority setting and resource allocation. This framework will support consistent conceptualization and operationalization of equity in global health programs. The degree to which equity is actually integrated in these programs merits further study.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.370

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 integrity0.0000.000
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 head0.038
GPT teacher head0.404
Teacher spread0.366 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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