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Record W4283155707 · doi:10.1038/s41893-022-00909-5

Scientific evidence on the political impact of the Sustainable Development Goals

2022· article· en· W4283155707 on OpenAlex

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

VenueNature Sustainability · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsUniversity of Toronto
FundersBundesministerium für Bildung und ForschungUniversity of Cambridge
KeywordsSustainable developmentNormativePoliticsTransformative learningPolitical scienceCorporate governanceLegislatureBusinessSociologyLaw

Abstract

fetched live from OpenAlex

Abstract In 2015, the United Nations agreed on 17 Sustainable Development Goals as the central normative framework for sustainable development worldwide. The effectiveness of governing by such broad global goals, however, remains uncertain, and we lack comprehensive meta-studies that assess the political impact of the goals across countries and globally. We present here condensed evidence from an analysis of over 3,000 scientific studies on the Sustainable Development Goals published between 2016 and April 2021. Our findings suggests that the goals have had some political impact on institutions and policies, from local to global governance. This impact has been largely discursive, affecting the way actors understand and communicate about sustainable development. More profound normative and institutional impact, from legislative action to changing resource allocation, remains rare. We conclude that the scientific evidence suggests only limited transformative political impact of the Sustainable Development Goals thus far.

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)0.006
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.355
Teacher spread0.333 · 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