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Record W2786823714

Monserrat, Torres, and Planinc on Voegelin’s Return to the Ancients

2017· article· en· W2786823714 on OpenAlexaff
Ron Srigley

Bibliographic record

VenueThe Political Science Reviewer · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicClassical Philosophy and Thought
Canadian institutionsLaurentian University
Fundersnot available
KeywordsPhilosophyRelation (database)EpistemologyFocus (optics)Order (exchange)PleasurePsychologyPsychotherapist
DOInot available

Abstract

fetched live from OpenAlex

In their paper “Eric Voegelin on Plato’s Philebus,” Monserrat and Torres offer a compelling discussion of Voegelin’s evocative but ambiguous term metaxy, the pedagogical role of pleasure and pain in his thought, and his notion of a Promethean theophany of order. They do so by examining his analyses of these things in relation to a dialogue that Voegelin often cites as a source-text for his findings but rarely discusses in detail: Plato’s Philebus. I think theirs is one of the most fruitful ways of continuing Voegelin’s project. Best to return to the primary sources in the same spirit in which Voegelin did, following up leads and provocative suggestions but also approaching the texts with the same critical focus that characterized Voegelin’s own work. Since time is limited I will focus primarily on their discussion of the metaxy. It occupies the largest portion of their paper and underlies much of their subsequent discussion of Voegelin’s use of the Philebus for his account of pedagogy and theophany.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.012
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.085
GPT teacher head0.321
Teacher spread0.236 · 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 designNot applicable
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
Published2017
Admission routes1
Has abstractyes

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