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Record W3046592309 · doi:10.1002/sd.2107

Sustainable development goal interactions: An analysis based on the five pillars of the 2030 agenda

2020· article· en· W3046592309 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

VenueSustainable Development · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsProsperityGeneral partnershipSustainable developmentSustainabilityOrder (exchange)Coherence (philosophical gambling strategy)Political scienceProcess managementComputer scienceBusinessBiologyEcologyFinance

Abstract

fetched live from OpenAlex

Abstract The 2030 Agenda calls for a change in thinking in order to implement sustainable development goals (SDGs) and targets as a system. To achieve this goal, the 2030 Agenda established five pillars (“5 Ps”): people, planet, prosperity, peace and partnership. Here, we present a classification of these SDGs and their targets based on the five pillars. Our aim is to improve our understanding of interactions by assessing whether potential synergies and trade‐offs are related to the classification of the targets. We surveyed 30 people and asked them to associate the content of target labels with the pillars. We classified SDG and targets according to an original quantification system. We determined whether the interactions were linked to similar or different classifications of the targets. We observed that the more similar the targets were in terms of classification, the more positive the interactions. We also noted that synergies exist between targets of different classifications. Our findings are useful for applying a systemic approach for policy coherence in sustainability analysis.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.019
GPT teacher head0.237
Teacher spread0.218 · 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