MétaCan
Menu
Back to cohort
Record W2810232353 · doi:10.20381/ruor-22065

Are the Sustainable Development Goals Realistic and Effective: A Qualitative Analysis of Key Informant Opinions

2018· article· en· W2810232353 on OpenAlex
Annalise Mathers, Raywat Deonandan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueuO Research (University of Ottawa) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSustainable developmentThematic analysisPolitical sciencePublic relationsCorporate governanceGlobal healthFocus groupQualitative researchPsychologyManagement scienceBusinessHealth careSociologyEconomicsSocial scienceMarketing

Abstract

fetched live from OpenAlex

The UN Sustainable Development Goals (SDGs) were devised in part to help define the international development funding agenda for future decades. This study sought to explore the challenges and strengths of the SDGs, with respect to their ability to effectively address current and future global health issues. Active researchers and opinion leaders in global health research were interviewed about their opinions on the future of global health, with particular attention to the likely impact of the SDGs on individual research programs. According to thematic analysis, respondent felt that the SDGs should focus more on the development of good governance structures, address corruption and tax systems to develop more comprehensive health structures and financing and embody a more holistic approach to global health.

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.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
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 head0.076
GPT teacher head0.415
Teacher spread0.339 · 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