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Charivaris

2016· other· en· W4239209350 on OpenAlexaff
Pauline Greenhill

Bibliographic record

VenueThe Wiley Blackwell Encyclopedia of Gender and Sexuality Studies · 2016
Typeother
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsSpouseSensibilityVariety (cybernetics)SociologyMoralityCriminologyGender studiesHistoryPolitical scienceLaw

Abstract

fetched live from OpenAlex

Charivari traditions have been documented in parts of Europe and North America from the Middle Ages to the present, with cognate customs found across the world. Historically, they involved a raucous, parading, house visit usually incited by weddings or relationships a community deemed problematic. They conventionally dramatized popular objections to weddings between two older people; between an older and a younger person; involving a widow and/or widower – especially too soon after the previous spouse's death; and/or involving a racially mixed or religiously diverse couple. Charivariers often sought to exact a price – money, cigarettes, food, and/or drink, especially alcohol – for the couple's transgression of traditional expectations that marriage should be between two previously unmarried, fertile young people with common ethnoracial and religious heritages. Charivari has also been used to describe a number of noisy parading performances traditionally directed toward a variety of offenders against community morality and sensibility, including unpopular politicians, officials, employers, and public servants. Currently, charivari is practiced primarily in rural areas and is instead a community welcome. However, progressive social protest groups often use charivari's historic noisemaking modes, including pots and pans beaten with wooden spoons, to draw attention to their causes, demonstrating the tradition's malleability.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.193
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.002
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1930.069

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 head0.057
GPT teacher head0.344
Teacher spread0.287 · 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
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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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