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Record W31573926 · doi:10.2196/14011

I PROCESSI CONTRO FIDIA ASPASIA ANASSAGORA E L'OPPOSIZIONE A PERICLE

2016· article· en· W31573926 on OpenAlexvenueno aff
Luisa Prandi, I Processi, Contro Fidia, Aspasia Anassagora, Aspasia e Anassagora, ostilit

Bibliographic record

VenueJMIR Mental Health · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

I tentativi finora compiuti dagli studiosi moderni per datare con maggior precisione i processi che nel decennio 440/30 colpirono Fidia, Aspasia e Anassagora, noti personaggi eW entourage pericleo, sono approdati a conclusioni divergenti. Le date pi frequentemente proposte sono il 438/7 e il 432/1, con una certa prevalenza in passato per la seconda, che rappresenta la data tradizionale; ma proprio nelPultimo decennio la datazione pi alta ha trovato attivi sostenitori in studiosi come il Frost, il Kagan, il De Ste Croix. Mi sembra tuttavia che le ipotesi dei moderni, cosi come sono motivate, non trovino sufficienti giustificazioni nelle fonti1 e che pertanto sia necessario discuterle e riesaminare quindi Tintero pro blema. La diversit di opinioni riguardo alla cronolog a dei processi che colpirono gli amici di Pericle con Paccusa di dcce eioc o di ispoauX a deriva dal fatto che le Stesse fonti non sono concordi e precise. Aristofane nella Pace, del 421, facendo spiegare da Ermes ai contadini, che costituiscono il coro, Porigine della guerra del Pelo ponneso, afferma che Pericle, temendo per la propiia posizione pol tica in seguito alPattacco contro Fidia, si sarebbe servito del decreto megarese come pretesto per provocare una guerra tale che coinvolse tutta la Grecia 2. Il commediografo sembra istituire uno stretto rap porto di causa-effetto fra il processo di Fidia, indicato molto vaga mente con Pespressione OeiSioc 7up a xaxco , e le lam ntele dei

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)0.010
metaresearch head score (Gemma)0.028
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: none
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.008
Scholarly communication0.0110.006
Open science0.0010.008
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0160.003

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 head0.030
GPT teacher head0.381
Teacher spread0.352 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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