Sustainable development goal interactions: An analysis based on the five pillars of the 2030 agenda
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".