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“The Greatest Speech-Makers on Earth”

2019· book-chapter· en· W3123159947 on OpenAlexaboutno aff
Céline Carayon

Bibliographic record

VenueUniversity of North Carolina Press eBooks · 2019
Typebook-chapter
Languageen
FieldArts and Humanities
TopicHistorical Linguistics and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousGestureAmbivalenceNonverbal communicationFeelingEmbodied cognitionPower (physics)HistoryAestheticsSociologyArtPsychologyLinguisticsCommunicationSocial psychologyEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

This chapter considers some of the ways in which nonverbal repertoires that had been painstakingly created over two centuries of interaction were creatively mobilized by Indigenous and French individuals in the long seventeenth century to produce culturally-hybrid performances. Opening with the Great Peace of Montreal (1701), the chapter describes the epistemological differences that caused misunderstandings even as Jesuit missionaries and Indian orators skilfully blended visual and verbal metaphors and registers to reach their audiences during religious and diplomatic exchanges. The highly adaptable and multimedia nature of Indigenous verbal art is compared with the efforts of the Jesuits to insert select Indigenous gestures within their orations. Ambivalent feelings towards the unauthentic nature of theatrical performances and competition with Indian <italic>jongleurs</italic> (shamans) limited the missionaries’ ability to harvest the power of Indian oratory. As the French expanded westward and down the Mississippi valley in the second half of the century, they were forced to confront the limits of some of their nonverbal strategies, as demonstrated through the case-study of the calumet. After two centuries of embodied communication, it had become harder to tell “French” apart from “Native” nonverbal devices.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.985
Threshold uncertainty score0.995

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 science0.0000.000
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 head0.029
GPT teacher head0.182
Teacher spread0.153 · 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.

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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