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Record W2267600253

Method, Madness, Magic: Plato's Phaedran Dialectics in Politics and Understanding

2010· article· en· W2267600253 on OpenAlexaff
Nina Valiquette Moreau

Bibliographic record

VenueSSRN Electronic Journal · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicClassical Philosophy and Thought
Canadian institutionsMcGill University
Fundersnot available
KeywordsDialecticSoulRationalityPhilosophyIrrational numberPoetryMAGIC (telescope)EpistemologyMythologyIrrationalityLiteratureAestheticsArtTheology
DOInot available

Abstract

fetched live from OpenAlex

Our modern understanding of the autonomy of human reason is always being read into the “old quarrel between philosophy and poetry” identified in the Platonic dialogues. On this understanding, philosophy itself assumes a self-evident distinction from “fiction” (poetry, myth, religion), and anything that cannot be circumscribed by its rationality is simply madness. But consider what is said in the Phaedrus vis-a-vis philosophy’s dialectical method. Here, this supra-rational method is first applied to an investigation of the emotional and irrational, namely love and madness, and ultimately uncovers the truth that god-given madness is better than human sobriety. Second, dialectic here reaches its own methodological limit, transposing itself from the sensible to the intelligible as a type of “vision of the soul.” This move from method to vision is manifest in the dialogue as a move from discursive analysis to myth: the philosophical enquiry at hand is completed by an act of poetry. There is no quarrel. Platonic philosophy, Phaedran dialectics indicate, is in fact an opening up of the soul to the vision of reality that obviates the distinction between rational and irrational as they are tied to human understanding. And in their highest form, philosophy and poetry are not only indistinguishable, but mediate the dynamic interrelationship Plato envisaged between the individual and society.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
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 score0.421
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.003
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 head0.038
GPT teacher head0.268
Teacher spread0.230 · 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.

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

Citations0
Published2010
Admission routes1
Has abstractyes

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