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Record W2269198251 · doi:10.4324/9781315252629-15

Private Order and Public Justice: Kant and Rawls

2017· book-chapter· en· W2269198251 on OpenAlexaff
Arthur Ripstein

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEconomic JusticePublic reasonOrder (exchange)Political scienceMoral orderLaw and economicsSociologyLawEconomicsSocial sciencePoliticsDemocracy

Abstract

fetched live from OpenAlex

This chapter lies at the intersection of two larger projects, one on Immanuel Kant’s legal and political philosophy, and the other on the relation between private law and distributive justice. It uses the Kantian idea of private ordering to explain the place of private law in what John Rawls has described as the “division of responsibility” between society and the individual. The chapter explains why private law is an essential part of what, for Rawls, is the fundamental subject of justice — the coercive structure of society. It argues that private law is only a system of reciprocal limits on freedom, provided that those limits are general in the right way. The chapter also argues that the best way to think about Rawls&s;s emphasis on public provision of adequate rights and opportunities is in parallel terms: they are essential conditions to the very possibility of enforceable rights, because they are the moral prerequisites for a shared public sphere.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.009
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.030
Scholarly communication0.0080.010
Open science0.0010.003
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.115
GPT teacher head0.358
Teacher spread0.243 · 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

Citations70
Published2017
Admission routes1
Has abstractyes

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