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Record W4413253141 · doi:10.1017/s0075435825100683

Money and mid-republican Rome

2025· article· en· W4413253141 on OpenAlexaff
Marleen K. Termeer, Fleur Kemmers, Seth Bernard, Marion Bolder-Boos, Andrew Burnett, Lucia F. Carbone, Federico Carbone, Moritz Hinsch, Melissa Ludke, Charles Parisot-Sillon, Liv Mariah Yarrow

Bibliographic record

VenueThe Journal of Roman Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsUniversity of Toronto
FundersFritz Thyssen StiftungNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsState (computer science)Period (music)Roman EmpireFormative assessmentOrder (exchange)HistoryPrincipal (computer security)Late AntiquityAncient historyRoman historyEconomyArtSociologyEconomicsAesthetics

Abstract

fetched live from OpenAlex

Abstract Rome’s mid-republican period is back in the centre of attention. Roman money and coinage, however, are largely absent from the debate. As this field has seen important developments in recent years, this paper surveys recent research in order to explore how numismatic sources can contribute to our understanding of this formative period in Roman history. First, we present an overview of these new developments, which we then contextualise in the framework of the Roman economy, Roman state formation and the development of a distinct Roman identity. We argue for a development from coinage irregularly commissioned by individual Roman magistrates to a regular Roman state coinage; from haphazard production often outside Rome to large-scale and more regular coordinated production clearly institutionalised within the Roman state, with a distinct Roman appearance. We propose to recognise two principal moments of acceleration in this process: around 240 and, above all, 210 b.c.e. , and show how these insights relate to broader debates on mid-republican Rome.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.027

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 studies0.0020.005
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.043
GPT teacher head0.367
Teacher spread0.324 · 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 designObservational
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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