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Record W4211259383 · doi:10.1017/cco9781139015356.010

Character types

2014· book-chapter· en· W4211259383 on OpenAlexaff
Ian Ruffell

Bibliographic record

VenueCambridge University Press eBooks · 2014
Typebook-chapter
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCharacter (mathematics)Computer scienceMathematicsGeometry

Abstract

fetched live from OpenAlex

In a famous fragment of Antiphanes’ Poetry (fr. 189), a character compares the resources available to tragedy and comedy in terms of inherited characters and stories. Mention Oedipus and the audience knows what will happen to him and who the other main characters are; comedy needs to invent everything – names, back-story, situation, crisis. ‘If some Chremes or Pheidon leaves any one of these out, he's whistled off stage’ (20f.). The main focus here is plot, but embedded in this are claims about the use of recurring characters, the audience's knowledge of those characters, their stories and associations. Comedy supposedly lacks these advantages and is forced to rely on its own devices. This is, at best, a half-truth. Middle Comedy, the period of Antiphanes, was a time when Greek comedy was increasingly rooted in typical or ‘stock’ characters – the use of Pheidon and Chremes as shorthand for comic characters is itself an indication. The trend develops further into the strongly type-based drama of Menander and his contemporaries, where stock characters were married to a relatively circumscribed set of plots in which love and/or paternity were a central element, with the overcoming of personal and social barriers the main concern. Such stock characters have been held to be either directly or indirectly, spiritually or actually, the ancestor of character types in one broad strand of popular Western comedy, through Roman comedy on into commedia dell’ arte into (among other things) modern British pantomime and Punch and Judy shows (and other European puppet traditions). Analogies have also been drawn with domestic situation comedy on television.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.885
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.236
Teacher spread0.202 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations7
Published2014
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicClassical Antiquity StudiesFrench-language works237,207