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Record W1481372458

The Market for Philosophers: An Interpretation of Lucian's Satire on Philosophy

2004· article· en· W1481372458 on OpenAlexaff
George Bragues

Bibliographic record

VenueSSRN Electronic Journal · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsUniversity of Guelph-Humber
Fundersnot available
KeywordsCharacter (mathematics)Interpretation (philosophy)EmpireQuality (philosophy)Variety (cybernetics)EpistemologyPhilosophyLawPolitical scienceComputer scienceMathematics
DOInot available

Abstract

fetched live from OpenAlex

Richard Posner's recent book, Public Intellectuals: A Study of Decline, is not the first attempt to economically analyze the intellectual marketplace. Eighteen hundred years ago, Lucian applied the same framework to the market for philosophers in the Roman Empire. Though widely seen as a satirist of limited philosophical acumen, Lucian's writings contain enough substance, at least when supplemented with the insights of contemporary economists, to generate an economic theory of philosophy. While much research is still necessary to fully test the theory, it holds promise in explaining key features of philosophic activity. Factors affecting demand and supply are identified in the theory. Also underlined is the risky character of philosophy in forcing consumers to choose among the available schools of thought by using quality indicators, such as the character, education, and commitment of philosophy suppliers. Reflecting a behavioral model, Lucian concludes that consumers take inordinate risks and that the philosophy market fails to produce truth. However, the philosophy market succeeds by generating a variety of world-views reflecting people's distinctive preferences.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.010
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0060.039
Scholarly communication0.0090.014
Open science0.0010.004
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0100.001

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 head0.022
GPT teacher head0.325
Teacher spread0.304 · 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

Citations5
Published2004
Admission routes1
Has abstractyes

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