MétaCan
Menu
Back to cohort
Record W4240471921 · doi:10.4324/9780203569320-11

Performing the Noble Savage

2006· book-chapter· en· W4240471921 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAsian American and Pacific Histories
Canadian institutionsnot available
Fundersnot available
KeywordsHistory

Abstract

fetched live from OpenAlex

In the French court, as in its Spanish and English counterparts, there existed a fascination with the nation’s exotic colonial Others. Throughout the sixteenth century, a dazzling array of masques and pageants depicting encounters between Frenchmen and the indigenous peoples of Canada were performed both in France and in the New World. As we have seen in the previous chapter, these performances (whether theatrical or textual, as was the case with Fontenelle’s putative dialogue between Montezuma and Cortés) underwent a marked transformation at the end of the seventeenth century, with the locus of discursive (and consequently political and cultural) authority hotly disputed between the Old World and the New. In this chapter, in order to contexualize the emergence 3 4 5 6 7 8 9 1011 1 2 3111 4 5 6 7 8 9 20111 1 2 3 4 5 6 7 8 9 30111 1 2 3 4 5 6 7 8 9 40111 both by Huguenot writers such as Marc Lescarbot and by the Jesuits to articulate and reinforce the notion of France’s Atlantic empire. I then look at one of the most influential performative texts in New World writing, Baron Lahontan’s Dialogues with Adario, and its construction of the Noble Savage. Finally, I analyse French playwright Louis-François de la Drevetière Deslisle’s drama Harlequin Sauvage, which draws heavily on Lahontan’s ideas and casts the Noble Savage as one of the characters in the genre of the commedia dell’arte.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0160.015
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.002

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 head0.015
GPT teacher head0.242
Teacher spread0.227 · 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
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicAsian American and Pacific HistoriesFrench-language works237,207