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Record W2990832993 · doi:10.3138/mous.16.3.008

On Olympic Victors, Ancient and Modern

2019· article· en· W2990832993 on OpenAlexvenueno aff
Stamatia Dova

Bibliographic record

VenueMouseion Journal of the Classical Association of Canada · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsGloryExtant taxonVictoryMedalHistoryArtAncient historyClassicsArt historyPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

During the 2016 Olympic games in Rio, the dialogue between the ancient and modern Olympics was enriched by the comparison between Leonidas of Rhodes (crowned 12 times at Olympia from 164 to 152 bc in the stadion, diaulos, and hoplitodromos) and the internationally acclaimed U.S. swimmer Michael Phelps (winner of 13 individual Olympic gold medals from 2004 to 2016). Decided by medal count, the two most decorated Olympic victors of all time seemed to abridge a cultural distance of 2168 years. After reviewing all extant sources about Leonidas of Rhodes, this paper examines three other exempla of Olympic victors, Diagoras of Rhodes (boxing, crowned 464 bc), Ladas of Argos (dolichos [5 km], crowned 460 bc), and Spiridon Louis (Marathon race, 1896 Athens Olympics), with special emphasis on the reception of their victories. In the cases of Diagoras and Ladas, my analysis identifies the analogies between a death sealed by Olympic glory and the paradigms of Tellos and Kleobis and Biton in Herodotos 1.31. The significance of Spiridon Louis’ victory for the nascent modern Greek state is discussed within the framework of the first Marathon race. By revisiting societal attitudes towards distinguished athletic winners then and now, this paper also engages in a discourse on the relationship between the ancient and modern Olympics.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.007
GPT teacher head0.225
Teacher spread0.218 · 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 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
Published2019
Admission routes1
Has abstractyes

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