Connecting the sustainable development goals by their energy inter-linkages
Bibliographic record
Abstract
The United Nations' Sustainable Development Goals (SDGs) provide guide-posts to society as it attempts to respond to an array of pressing challenges. One of these challenges is energy; thus, the SDGs have become paramount for energy policy-making. Yet, while governments throughout the world have already declared the SDGs to be 'integrated and indivisible', there are still knowledge gaps surrounding how the interactions between the energy SDG targets and those of the non-energy-focused SDGs might play out in different contexts. In this review, we report on a large-scale assessment of the relevant energy literature, which we conducted to better our understanding of key energy-related interactions between SDGs, as well as their context-dependencies (relating to time, geography, governance, technology, and directionality). By (i) evaluating the nature and strength of the interactions identified, (ii) indicating the robustness of the evidence base, the agreement of that evidence, and our confidence in it, and (iii) highlighting critical areas where better understanding is needed or context dependencies should be considered, our review points to potential ways forward for both the policy making and scientific communities. First, we find that positive interactions between the SDGs outweigh the negative ones, both in number and magnitude. Second, of relevance for the scientific community, in order to fill knowledge gaps in critical areas, there is an urgent need for interdisciplinary research geared toward developing new data, scientific tools, and fresh perspectives. Third, of relevance for policy-making, wider efforts to promote policy coherence and integrated assessments are required to address potential policy spillovers across sectors, sustainability domains, and geographic and temporal boundaries. The task of conducting comprehensive science-to-policy assessments covering all SDGs, such as for the UN's Global Sustainable Development Report , remains manageable pending the availability of systematic reviews focusing on a limited number of SDG dimensions in each case.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.010 | 0.017 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".