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What's Wrong with Rights?

2020· book· en· W3134313711 on OpenAlexaboutno aff
Nigel Biggar

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceLaw and economicsLawSociology

Abstract

fetched live from OpenAlex

Abstract Are natural rights ‘nonsense on stilts’, as Jeremy Bentham memorably put it? Must the very notion of a right be individualistic, subverting the common good? Should the right against torture be absolute, even though the heavens fall? Are human rights universal or merely expressions of Western neo-imperial arrogance? Are rights ethically fundamental, proudly impervious to changing circumstances? Should judges strive to extend the reach of rights from civil Hamburg to anarchical Basra? Should judicial oligarchies, rather than legislatures, decide controversial ethical issues by inventing novel rights? Ought human rights advocates to learn greater sympathy for the dilemmas facing those burdened with government? These are the questions that What’s Wrong with Rights? addresses. In doing so, it draws upon resources in intellectual history, legal philosophy, moral philosophy, moral theology, human rights literature, and the judgements of courts. It ranges from debates about property in medieval Christendom, through Confucian rights-scepticism, to contemporary discussions about the remedy for global hunger and the justification of killing. And it straddles assisted dying in Canada, the military occupation of Iraq, and genocide in Rwanda. What’s Wrong with Rights? concludes that much contemporary rights-talk obscures the importance of fostering civic virtue, corrodes military effectiveness, subverts the democratic legitimacy of law, proliferates publicly onerous rights, and undermines its own authority and credibility. The solution to these problems lies in abandoning rights-fundamentalism and recovering a richer public discourse about ethics, one that includes talk about the duty and virtue of rights-holders.

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 imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0080.060
Scholarly communication0.0130.027
Open science0.0020.004
Research integrity0.0100.014
Insufficient payload (model declined to judge)0.0130.003

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.

Opus teacher head0.062
GPT teacher head0.321
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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