What Is a “Right to Have Rights”? Three Images of the Politics of Human Rights
Bibliographic record
Abstract
This article seeks to elucidate some of the difficulties and reversals that afflict human rights by exploring three interpretations of Hannah Arendt's idea of a “right to have rights,” and in particular the images of politics these interpretations presuppose. The first, most conventional interpretation considers this right in terms of the use of power to implement rights; a second, broadly Kantian interpretation understands it in terms of laws and institutions; a third, which I develop through an original reading of Arendt, bases it on the activity of the rights-claimants or -holders themselves. Although each of these conceptions corresponds to different circumstances and speaks to different concerns, the third is especially valuable in helping us understand the problems that plague efforts on behalf of human rights and showing how human rights can best be realized and secured. If it is the most demanding, it alone fully honors human rights' emphasis on autonomy.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.058 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".