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Record W1995687829 · doi:10.4102/hts.v70i1.2698

Dressing down criminals, deviants and other undesirabless

2014· article· en· W1995687829 on OpenAlexaff
Dietmar Neufeld

Bibliographic record

VenueHTS Teologiese Studies / Theological Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInvectiveShameClothingFalse accusationStyle (visual arts)Rhetorical questionArtLawHistoryLiteraturePolitical sciencePolitics

Abstract

fetched live from OpenAlex

Fear of just censure and the sense of shame it produced kept Roman citizens from doing wrong (Cic. Rep. 5.6). Invective functioned socially as a strategy of social sanction. One amongst a number of commonly identified topics of accusation in the Roman tradition of ridicule was unusual appearance, clothing or demeanour. Not surprisingly, John the Baptist emerges from the desert attired distinctly, demoniacs come out of the tombs so fierce that no one would pass by them (Mt 8:28), a man with an unclean spirit lives amongst the tombs and, even though adorned with fetters and chains, cannot be controlled (Mk 5:15–20). Herod pretentiously puts on the royal robes and is eaten by worms and dies (Ac 12:21). A woman uninvited enters a rich man’s dinner party with an alabaster flask of perfume and anoints the feet of Jesus (Lk 7:38). Clearly, in each case, unusual appearance, clothing, and demeanour suggest a lapse from the appropriate, socially acceptable style of deportment and clothing. Oddities in dress and demeanour were equated with oddities in behaviour and provided a powerful rhetorical means of excluding undesirables from society.

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)0.003
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.011
Scholarly communication0.0000.000
Open science0.0010.002
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 head0.275
GPT teacher head0.438
Teacher spread0.163 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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
Published2014
Admission routes1
Has abstractyes

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