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Civil Disobedience and Conscientious Refusal

2025· book-chapter· en· W4417466277 on OpenAlexaff
Kimberley Brownlee, Chong‐Ming Lim

Bibliographic record

VenueOxford University Press eBooks · 2025
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCivil disobedienceCivil libertiesAsideArgumentativePower (physics)Economic JusticeRelation (database)Civil law (Civil law)Element (criminal law)

Abstract

fetched live from OpenAlex

Abstract In A Theory of Justice, John Rawls produced what remains the most influential account of civil disobedience and, to a lesser extent, conscientious refusal. Engaging with Rawls’s account and seeking to deploy it to evaluate real-world cases are, however, undertakings beset with difficulties. In relation to civil disobedience, first, Rawls defines “civil disobedience” so narrowly (as a conscientious, nonviolent breach of law undertaken with fair notice, fidelity to the system, and acceptance of the consequences to bring about policy change) that no paradigm example from Gandhi to Rosa Parks satisfies it. Second, Rawls’s three conditions for morally justified civil disobedience—that it be undertaken (1) in response to violations of the principles of justice, (2) as a last resort, and (3) in coordination with other dissenters so as not to overburden the majority’s sense of justice or risk lasting injury to a just constitution—impose extreme restrictions on civil disobedience. In relation to conscientious refusal, Rawls’s approach is equally narrow: he sets aside refusals that would be grounded in persons’ private commitments and focuses instead on refusals grounded in public considerations; his central case is selective pacificism grounded in a respect for equal basic liberties (Rawls’s first principle of justice). This chapter acknowledges the argumentative power and lasting influence of Rawls’s treatment of civil disobedience and conscientious objection, while detailing how his account must be refined—and in some ways radically altered—to address real-world concerns.

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)0.009
metaresearch head score (Gemma)0.021
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: Other
Teacher disagreement score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.035
Scholarly communication0.0030.004
Open science0.0010.005
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.038
GPT teacher head0.264
Teacher spread0.226 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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