Bibliographic record
Abstract
Taking a fresh look at the first two centuries of French colonialism in the Americas, this book answers the long-standing question of how and how well Indigenous Americans and Europeans communicated with each other during colonial encounters. French explorers and colonists in the sixteenth century noticed that Indigenous peoples from Brazil to Canada used signs to communicate. The newcomers, in response, quickly embraced the nonverbal as a means to overcome cultural and language barriers throughout French America. Céline Carayon's close examination of French accounts, combined with her multidisciplinary methodology, enables her to recover these sophisticated Native practices of embodied expression. In a colonial world where communication and trust were essential but complicated by the multiplicity of Indigenous languages, intimate and sensory communications ensured that colonists and Indigenous peoples understood each other well. Understanding, in turn, bred both genuine personal bonds and violent antagonisms. Nonverbal communication shaped Indigenous resistance to colonial pressures across the Americas just as it fueled the French imperial imagination and strategies. Challenging the notion of colonial America as a site of misunderstandings and insurmountable cultural clashes, Carayon shows that Natives and newcomers used nonverbal means to build relationships before the rise of linguistic fluency--and, crucially, well afterward.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".