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Record W4413467288 · doi:10.1017/s0075426925100311

Sip, don’t suck: defining ‘Greek’ and ‘male’ via beer, wine and sex

2025· article· en· W4413467288 on OpenAlexaff
Jessica M. Romney

Bibliographic record

VenueThe Journal of Hellenic Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMarriage and Sexual Relationships
Canadian institutionsMacEwan University
Fundersnot available
KeywordsWineHistoryArtVisual arts

Abstract

fetched live from OpenAlex

Abstract This article re-examines archaic and classical treatment of beer drinking to argue, contra Nelson, that beer in archaic and classical Greek texts is not primarily feminine nor does it necessarily feminize its drinkers. Rather, a review of sympotic lyric, historiography, ethnography and Athenian drama demonstrates that beer is primarily an ethnic marker with no inherent gendered connotations. At the same time, in contexts where definitions of Greek masculinity are being constructed, beer can gain gendered connotations which enhance the ethnic otherness of the beverage and contribute to the definition of the Greek man. Any gendered implications of beer, furthermore, come not from the beverage itself but from the method of consumption, of sucking through a tube of sorts rather than sipping from a cup. This article thus argues that beer in the Archaic and Classical periods marks non-Greek status first and foremost and only secondarily effeminizes drinkers through associations with oral sex in contexts where ideas of masculinity are in play.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.011

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 studies0.0020.018
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.359
Teacher spread0.311 · 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 designQualitative
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
Published2025
Admission routes1
Has abstractyes

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