The importance of an integrating framework for achieving the Sustainable Development Goals: the example of health and well-being
Bibliographic record
Abstract
The 2030 Agenda for Sustainable Development came into force in January 2016 as the central United Nations (UN) platform for achieving 'integrated and indivisible' goals and targets across the three characteristic dimensions of sustainable development: the social, environmental and economic. We argue that, despite the UN adoption of the Sustainable Development Goals (SDGs), a framework for operationalising them in an integrated fashion is lacking. This article puts forth a framework for integrating health and well-being across the SDGs as both preconditions and outcomes of sustainable development. We present a rationale for this approach, and identify the challenges and opportunities for implementing and monitoring such a framework through a series of examples. We encourage other sectors to develop similar integrating frameworks for supporting a more coordinated approach for operationalising the 2030 Agenda for Sustainable Development.
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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 | 0.033 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.063 |
| Scholarly communication | 0.020 | 0.025 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".