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Record W3167510332 · doi:10.1017/s0009838821000227

NUMA AND JUPITER: WHOSE SMILE IS IT, ANYWAY?

2021· article· en· W3167510332 on OpenAlexaff
Lindsay G. Driediger-Murphy

Bibliographic record

VenueThe Classical Quarterly · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMythologyInterpretation (philosophy)IdeologyLiteratureCharacter (mathematics)Meaning (existential)HistoryPhilosophyAestheticsEpistemologyPoliticsArtLawLinguistics

Abstract

fetched live from OpenAlex

Abstract This article examines the Roman tradition that Numa once negotiated with Jupiter about human sacrifice. Complete versions of the myth survive in Ovid, Plutarch and Arnobius (citing Valerius Antias). Previous studies of this tradition have proposed four main interpretations of it, which have done important service in modern reconstructions of the character of Roman religion. These scholarly treatments raise several questions. First, are they actually supported by, or the most convincing way of reading, the surviving ancient sources? If so, have they been correctly attributed? Why might a specific ancient author present the myth of Numa and Jupiter in a manner which suggests one interpretation rather than another? What ideological and theological work does the story do for Ovid, for Plutarch and for Arnobius? Finally, can this myth, in whatever version, support the weight of the implications put on it for the character of Roman religion? This article seeks to enhance our understanding of this myth in its surviving versions, not just by analysing the evidence for each of the modern interpretations, but also by considering why ancient authors tell the myth of Numa and Jupiter the way they do. It is argued that their choices illustrate best not one meaning of the myth nor one Roman way of piety but the richness and diversity of religious reflection in antiquity.

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)0.004
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.018
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.002
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 head0.037
GPT teacher head0.324
Teacher spread0.287 · 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
Published2021
Admission routes1
Has abstractyes

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