Assessing the sustainable development goals from a human rights perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Though they improve upon the millennium development goals (MDGs), the new sustainable development goals (SDGs) have important draw-backs. First, in assessing present deprivations, they draw our attention to historical comparisons. Yet, that things were even worse before is morally irrelevant; what matters is how much better things could be now. Second, like the MDGs, the SDGs fail to specify any division of labor to ensure success. Therefore, should progress stall, we won't know who is responsible to get us back on track. We won't “end poverty in all its forms everywhere” without an agreement on who is to do what. Third, although the SDGs contain a goal calling for inequality reduction, this goal is specified so that the reduction need not start till 2029. Such delay would cause enormous death and suffering among the poor and enable the rich to shape national and supranational design in their own favor.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it