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Record W2139642768 · doi:10.1177/0191453714545340

Rebooting discourse ethics

2014· article· en· W2139642768 on OpenAlexaff
Joseph Heath

Bibliographic record

VenuePhilosophy & Social Criticism · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Theory and Philosophy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsUniversalizationArgument (complex analysis)EpistemologyDiscourse ethicsSociologySubject (documents)Transcendental numberRebootNormative ethicsPhilosophyComputer sciencePsychologySocial psychology

Abstract

fetched live from OpenAlex

In this article I argue that the conception of discourse ethics that Jürgen Habermas advances in his seminar paper, ‘Discourse Ethics: Notes on a Program of Philosophical Justification’, is subject to significant revision in later work. The central difference has to do with the status of the universalization principle and its relationship to the ‘rightness’ validity claim. The earlier view is structured by a desire to provide a weak-transcendental defense of the universalization principle. The later revision, however, essentially undercuts the basis of this argument, because it severs the conception of practical discourse from the analysis of speech acts. As a way of responding to the difficulties this creates, I propose a ‘reboot’ of the discourse ethics program. This involves reverting to the earlier, more Durkheimian and less Kantian, formulation of the theory. The result is a program that is no longer encumbered by sterile debates about the correct formulation of the universalization principle, but can plausibly claim to provide insight into the role that language-dependence plays in the development and entrenchment of increasingly pro-social behavior patterns within our institutions.

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)0.038
metaresearch head score (Gemma)0.042
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 score0.038
Threshold uncertainty score0.201

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.001
Science and technology studies0.0110.078
Scholarly communication0.0170.028
Open science0.0030.014
Research integrity0.0140.021
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 head0.112
GPT teacher head0.430
Teacher spread0.318 · 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

Citations242
Published2014
Admission routes1
Has abstractyes

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