Bibliographic record
Abstract
It is noteworthy—and at the same time a bit disappointing in a what-took-so-long sort of way—that a recent innovation in the study of human rights should involve a focus on the lives of the people directly affected by them. To explain this delay of the obvious would probably call for a review of the persistent influence of Kantian transcendentalism, the quasi-utopian search for ideal justice, and the inherently abstract nature of law in its quest for impartiality. A similar effort could be applied toward fully understanding the changed circumstances that encouraged the shift toward practical realism. It would have to take into account the surprisingly late elaboration and popularization of human rights instruments, the proliferation of transnational NGOs that act on new opportunities to exercise moral and political influence, and the growing reach of new technologies of information and communication (necessary tools for the emergence of transnational NGOs). All of these developments have raised the prominence of legal issues and strategies among those once considered isolated and, in varying degrees, uncivilized. But whatever the dominant trends might once have been, and whatever new, enabling circumstances have recently emerged, there can be little doubt that over the last several decades a shift has taken place in the study of human rights toward practical or applied realism, with a focus on ordinary actors.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.017 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| 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".