Did the right to health get across the line? Examining the United Nations resolution on the Sustainable Development Goals
Bibliographic record
Abstract
Since the new global health and development goal, Sustainable Development Goal (SDG) 3, and its nine targets and four means of implementation were introduced to the world through a United Nations (UN) General Assembly resolution in September 2015, right to health practitioners have queried whether this goal mirrors the content of the human right to health in international law. This study examines the text of the UN SDG resolution, Transforming our world: the 2030 Agenda for Sustainable Development , from a right to health minimalist and right to health maximalist analytic perspective. When reviewing the UN SDG resolution’s text, a right to health minimalist questions whether the content of the right to health is at least implicitly included in this document, specifically focusing on SDG 3 and its metrics framework. A right to health maximalist, on the other hand, queries whether the content of the right to health is explicitly included. This study finds that whether the right to health is contained in the UN SDG resolution, and the SDG metrics therein, ultimately depends on the individual analyst’s subjective persuasion in relation to right to health minimalism or maximalism. We conclude that the UN General Assembly’s lack of cogency on the right to health’s position in the UN SDG resolution will continue to blur if not divest human rights’ (and specifically the right to health’s) integral relationship to high-level development planning, implementation and SDG monitoring and evaluation efforts.
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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 | 0.031 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.011 | 0.043 |
| Scholarly communication | 0.021 | 0.023 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.014 | 0.019 |
| Insufficient payload (model declined to judge) | 0.005 | 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".