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Record W2889700571 · doi:10.5325/chaucerrev.53.3.0308

“An irous man”: Anger and Authority in the <i>Summoner's Tale</i>

2018· article· en· W2889700571 on OpenAlexaff
Marc B. Cels

Bibliographic record

VenueThe Chaucer Review · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicMedieval Literature and History
Canadian institutionsAthabasca University
Fundersnot available
KeywordsAngerLegitimacyTheme (computing)LiteratureLawSociologyHistoryPhilosophyPsychologyArtSocial psychologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Abstract The theme of wrath in the Summoner's Tale is revisited in light of the medieval moral tradition disseminated through pastoral commonplaces. Although it was counted among the Deadly Sins, anger was considered virtuous when used for correcting sin. Friar John's discourse on anger and his conversations with other characters in the tale revolve around the relationship of social status to the legitimacy of anger, or zeal for correction. Previous studies have shown that the vicious anger of Friar John undermines the authority of mendicants. Here it is argued that the right ordering of anger by aristocratic characters at the manor hall legitimizes their authority. They practice the virtues opposed to wrath and employ pastoral remedies against John's ire. Finally, Jankyn punishes the friar with his witty and courtly solution to dividing Thomas's fart. Aristocratic authority over other social estates is dramatized at the expense of undermining mendicant and clerical pretenses.

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)0.002
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: none
Teacher disagreement score0.010
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0040.013
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.276
Teacher spread0.233 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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