The United Nations Sustainable Development Goals 2030 Vision: Backsliding, Illiberalism, and the Unlikelihood of the Agenda’s Success
Bibliographic record
Abstract
The United Nations 2030 Sustainable Development Goals (SDGs) Agenda has been derailed by various events (e.g., COVID-19, economic crises, democratic backsliding, economic illiberalism, decreasing regard for human rights, and war). These events have diverted attention from the Agenda, and consumed precious limited financial resources that could be used to advance the SDGs. With only five years remaining, this initiative is at serious risk of not achieving its desired objectives and impact. Internal contradictions between the goals, challenges to the funding mechanism, and power imbalances within a country, regionally, and globally need to be addressed. This paper will examine the myriad challenges that countries face in trying to implement the Agenda post COVID-19, including those linked to the actions of developed countries, and explore how important changes to the Agenda could be undertaken all while helping to protect a country’s own policy space.
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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 | 0.017 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".