Accelerating achievement of the sustainable development goals
Bibliographic record
Abstract
A game changer in global health In September 2015, nearly 200 nations adopted the 17 sustainable development goals (SDGs) as a transformative, universal framework to address three interwoven dimensions of our global existence—people, planet, and prosperity.1 They are predicated on the notion that sustainability is not just an aspiration but a necessity. However, by substantially expanding on the scope and targets of their predecessors (the millennium development goals), the SDGs have set a high bar. To achieve them, we will need collective action to create new knowledge, share and broker knowledge, and implement insights through working with many sectors and diverse global health policy stakeholders. With this in mind, 60 global health policy think tanks from around the world met in Geneva in November 2015 to explore the role that think tanks and academic institutions have in implementing the SDGs. Although only SDG3 focuses primarily on health, many other development goals, including those that relate to the environment, nutrition, hunger, sustainable production and consumption, agriculture, and education, also have a big effect on health. To achieve progress on human health, countries will therefore need to commit to a broad agenda of sustainable development that acknowledges and exploits the links between different goals and targets. This provides an opportunity for systems thinking: applying an ecological perspective and implementing an …
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.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".