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Record W2567622053 · doi:10.1017/s0003055416000393

Tongue-Tied: Rawls, Political Philosophy and Metalinguistic Awareness

2016· article· en· W2567622053 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Political Science Review · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsMcGill University
Fundersnot available
KeywordsPoliticsPolitical philosophyNormativeEpistemologyPolitical communicationSociologyDemocracyAgency (philosophy)LinguisticsPolitical sciencePhilosophyLaw

Abstract

fetched live from OpenAlex

Is our moral cognition “colored” by the language(s) that we speak? Despite the centrality of language to political life and agency, limited attempts have been made thus far in contemporary political philosophy to consider this possibility. We therefore set out to explore the possible influence of linguistic relativity effects on political thinking in linguistically diverse societies. We begin by introducing the facts and fallacies of the “linguistic relativity” principle, and explore the various ways in which they “color,” often covertly, current normative debates. To illustrate this, we focus on two key Rawlsian concepts: the original position and public reason. We then move to consider the resulting epistemic challenges and opportunities facing contemporary multilingual democratic societies in an age of increased mobility, arguing for the consequent imperative of developing political metalinguistic awareness and political extelligence among political scientists, political philosophers, and political actors alike in an irreducibly complex linguistic world.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
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 score0.966
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.027
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.417
Teacher spread0.344 · 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