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Record W2913952706 · doi:10.35296/jhs.v2i0.12

Raising an Athlete for Christ: Saint John Chrysostom and Education in Byzantium

2018· article· en· W2913952706 on OpenAlexaff
Theodore Michael Christou

Bibliographic record

VenueAkropolis Journal of Hellenic Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsQueen's University
Fundersnot available
KeywordsJohn ChrysostomHomilyContext (archaeology)SAINTArgument (complex analysis)SoulRhetoricVirtueEpithetPhilosophyTheologyLiteratureClassicsArtSociologyHistoryArt historyArchaeology

Abstract

fetched live from OpenAlex

This article examines the homily titled Address on Vainglory, and the Right Way for Parents to Bring up their Children, concentrating upon the educational vision it expresses. The text is attributed to John Chrysostom, Christian saint and fourth century Patriarch of Constantinople. Uncertainty regarding the manuscript’s authenticity led to the exclusion of “Address on Vainglory” from most collections of John Chrysostom’s writings, which had seminal influence in a context when the church was united, and the homily has consequently received very limited attention. Chrysostom earned the epithet "The Golden Mouthed” primarily by virtue of his training in rhetoric and his ability to translate the classical sources that he read into his own, Christian, context. He argues that education must not only cultivate all the faculties of the student’s mind, but also prepare the child to live and act ethically in the world. Chrysostom reconfigures this argument using the striking imagery of an Athlete for Christ, who cultivated not only the faculties of his mind, but also exercised those of the soul.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.009
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.057
GPT teacher head0.390
Teacher spread0.333 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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