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Record W2890211210 · doi:10.1080/21598282.2018.1506261

Human Rights as Hinge Principles

2018· article· en· W2890211210 on OpenAlexaff
Jeff Noonan

Bibliographic record

VenueInternational Critical Thought · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Economy and Marxism
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsHuman rightsInterpretation (philosophy)OppressionCitizenshipSociologyLawFundamental rightsInternational human rights lawLiberalismLaw and economicsDemocracyHuman rights movementCapitalismRight to propertyPolitical sciencePoliticsPhilosophy

Abstract

fetched live from OpenAlex

The standard interpretation of human rights models them on the constitutional rights of citizenship familiar from the history of liberalism. Human rights are, in this view, universalizations of nationally particular liberal rights of citizenship. This interpretation invites a Marxist critique. Like the rights of citizenship, human rights fail to address the deep causes on inequality, domination, and social violence: market forces that drive states into conflict over scarce resources and capitalists to intensify the exploitation of labour. I agree with this critique, but argue that it does not necessarily apply to human rights as such, but only to the standard interpretation. I conclude by excavating from major human rights documents a different interpretation. This counter-reading focuses on the life-value of human rights: their potential to expose the life-destructive forces that drive capitalism. Read in this way, human rights can serve as hinge principles that legitimate mass democratic struggle against capitalist oppression and violence. On their own human rights under any reading cannot solve the problems supporters think they can solve. But as hinge principles they can help legitimate the mass struggles that can solve those problems.

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)0.005
metaresearch head score (Gemma)0.006
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: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.046
Scholarly communication0.0100.011
Open science0.0010.004
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0090.002

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 head0.057
GPT teacher head0.416
Teacher spread0.359 · 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
GenreEmpirical

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

Citations2
Published2018
Admission routes1
Has abstractyes

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