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Record W3137804110 · doi:10.1111/theo.12307

Deontic Concepts and Their Clash in Mīmāṃsā: Towards an Interpretation

2021· article· en· W3137804110 on OpenAlexaff
Elisa Freschi, Matteo Pascucci

Bibliographic record

VenueTheoria · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicClassical Philosophy and Thought
Canadian institutionsUniversity of Toronto
FundersVienna Science and Technology Fund
KeywordsDeontic logicNormativeEpistemologyInterpretation (philosophy)PhilosophyRendering (computer graphics)Presentation (obstetrics)SociologyComputer scienceLinguisticsArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract The article offers an overview of the deontic theory developed by the philosophical school of Mīmāṃsā, which is, and has been since the last centuries BCE, the main source of normative concepts in Sanskrit thought. Thus, the Mīmāṃsā deontics is interesting for any historian of philosophy and constitutes a thought‐provoking occasion to rethink deontic concepts, taking advantage of centuries of systematic reflections on these topics. Some comparison with notions currently used in Euro‐American normative theories and metaethical principles is offered in order to show possible points of contact and deep divergences. In more detail, after an introduction explaining the methodology and aims of our work, we discuss how Mīmāṃsā authors distinguished and defined some fundamental deontic concepts, such as different types of prescriptions and prohibitions. We then discuss how Mīmāṃsā authors approached the problem of conflicts among commands without jeopardising the validity of the normative text issuing them. In the second part of the article we introduce our formal apparatus, which is construed around the main taxonomic and conceptual distinctions used in the first part. Our formal rendering captures the most important features of the Mīmāṃsā theory and can thus serve as a concise and rigorous presentation of it for scholars working in deontic logic.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.803

Codex and Gemma teacher scores by category

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

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 head0.026
GPT teacher head0.269
Teacher spread0.244 · 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 teacher head, 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

Citations6
Published2021
Admission routes1
Has abstractyes

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