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Justice in Ideal Theory: A Refutation

2007· article· en· W2112170319 on OpenAlexaff
Colin Farrelly

Bibliographic record

VenuePolitical Studies · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEgalitarianismIdeal (ethics)Ideal theoryLaw and economicsEconomic JusticeSociologyPolitical philosophyPoliticsLawPolitical scienceMathematics

Abstract

fetched live from OpenAlex

In this article I argue that theorizing about justice at the level of ideal theory is inherently flawed and thus has impoverished liberal egalitarianism. Ideal theorists (falsely) assume that a political philosopher can easily determine (or has privileged access to) what constitutes the ‘best foreseeable conditions’. Furthermore, by assuming full compliance, ideal theorists violate the constraints of a realistic utopia. More specifically I argue that liberal egalitarians who function at the level of ideal theory adopt a cost-blind approach to rights and a narrow view of possible human misfortune. The former issue leads liberal egalitarians to give priority to a serially ordered principle of equal basic liberties or to treat rights as ‘trumps’; and the latter to a stringent prioritarian principle (Rawls' difference principle) or luck egalitarianism. Taken together, the cost-blind approach to rights, coupled with the narrow view of human misfortune, mean the liberal egalitarian theories of justice cannot address the issue of trade-offs that inevitably arises in real non-ideal societies that face the fact of scarcity. This makes liberal egalitarianism an ineffective theory of social justice.

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)0.014
metaresearch head score (Gemma)0.029
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 score0.014
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0060.049
Scholarly communication0.0070.014
Open science0.0030.008
Research integrity0.0090.016
Insufficient payload (model declined to judge)0.0070.002

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 head0.215
GPT teacher head0.488
Teacher spread0.273 · 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

Citations619
Published2007
Admission routes1
Has abstractyes

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