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Record W2900803533 · doi:10.1017/ann.2018.4

Rome, Carthage, and Numidia: Diplomatic Favouritism before the Third Punic War

2018· article· en· W2900803533 on OpenAlexaff
Colin Bailey

Bibliographic record

VenueAntichthon · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsMacEwan University
Fundersnot available
KeywordsHostilityPeriod (music)Spanish Civil WarArbitrationLawHistoryPolitical sciencePhilosophyPsychology

Abstract

fetched live from OpenAlex

ABSTRACT This article examines Rome’s diplomatic relations with Carthage and Numidia in the period between the Second and Third Punic Wars. Polybius’ suggestion that Rome consistently decided against Carthage in territorial disputes with Numidia in the aftermath of the Second Punic War (Polyb. 31.21.5-6) has often been taken up in explanations of the origins of the Third Punic War. Many ancient and modern accounts accept the implication of a policy of hostility against Carthage, assuming that Rome permitted and even encouraged Masinissa to infringe upon and seize Carthaginian territory. This paper, however, argues that the results of Roman arbitration between Carthage and Numidia do not show a consistent policy intended to undermine Carthage. Rather, Rome sought to maintain the territorial division which was imposed at the end of the Second Punic War throughout the inter-war period; several of its decisions were actually in favour of Carthage. The Third Punic War should not be seen as a culmination of a half-century of Roman hostility towards Carthage.

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)0.002
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 score0.010
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.021
Scholarly communication0.0060.002
Open science0.0000.003
Research integrity0.0010.003
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 head0.019
GPT teacher head0.305
Teacher spread0.286 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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