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“Many Friendly Signs”

2019· book-chapter· en· W3125221658 on OpenAlexaboutno aff
Céline Carayon

Bibliographic record

VenueUniversity of North Carolina Press eBooks · 2019
Typebook-chapter
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousEmpireColonialismNarrativeHistoryGestureDiplomacyEmperorCreole languageHumanitiesArtLiteraturePolitical scienceAncient historyLinguisticsLawArchaeology

Abstract

fetched live from OpenAlex

In early America, French and Indians communicated more by doing than saying. This chapter focuses on sixteenth-century encounters and the signs that mediated them, as foundational in shaping lasting mutual perceptions and expectations among the groups in colonial America. While acknowledging misunderstandings and language barriers, most early French visitors to the New World reported adequate successes in communicating and obtaining desired information through alternate media. This chapter compares Jacques Cartier’s encounters with the peoples of the Saint Lawrence Valley in Canada with the experience of French Huguenots who founded Charlesfort and Fort Caroline among the Timucua of Florida. Within each section, colonial narratives and visual sources are critically revisited to reconstruct Indigenous practices and meanings and understand the role of touch, place, and gestures in diplomacy and spiritual exchanges. A more complicated understanding of these early communications and Indian expressions of “joy” emerges. The chapter concludes with a look at how different Indigenous signs encountered across the Americas were selected and homogenized by Marc Lescarbot in his Histoire de la Nouvelle France (1609) to provide a conceptual and practical foundation for the budding French empire.

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: Other · Consensus signal: Other
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.010
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0180.004

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 head0.027
GPT teacher head0.172
Teacher spread0.145 · 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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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Same venueUniversity of North Carolina Press eBooksSame topicHistorical Studies and Socio-cultural AnalysisFrench-language works237,207