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Record W2758253606 · doi:10.7202/1039354ar

« Danser sur ses bas ». Rémanence d’une sanction populaire dans le rituel du mariage franco-ontarien

2017· article· fr· W2758253606 on OpenAlexaffvenueabout
Jean-Pierre Pichette

Bibliographic record

VenueCahiers Charlevoix Études franco-ontariennes · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Sudbury
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Jean-Pierre Pichette s’intéresse à un rituel du mariage très vivant et coloré en Ontario français, la « danse sur les bas », connu dans le Sud-Ouest dans une variante, la « danse dans l’auge ». Pour cerner les principales manifestations et saisir l’évolution d’une pratique rarement rapportée au Canada français et qui n’avait jamais été étudiée en Ontario avant cette étude, il a ordonné une enquête et fait appel à de nombreux collègues et à des collaborateurs étudiants. La comparaison des centaines de témoignages réunis, franco-ontariens et canadiens-français, lui permet de décrire les formes particulières et régionales du rituel ‒ la danse dans l’auge, dans une cuve et sur ses bas ‒, de suivre leur évolution et d’apprécier leur degré de vitalité dans les milieux minoritaires. L’examen des conditions historiques qui ont soutenu cette coutume ‒ connue au temps des Papineau ‒, et du climat culturel favorisant sa durée et son expansion met en évidence la nécessité en ethnologie d’un terrain permanent, qui, en plus d’enrichir la connaissance, participe à l’abolition des préjugés.

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)0.001
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: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.466

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.006
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.012
GPT teacher head0.213
Teacher spread0.201 · 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

Citations0
Published2017
Admission routes3
Has abstractyes

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