Bodies, Faces, Physical Spaces and the Materializations of Authority
Bibliographic record
Abstract
This chapter presents three perspectives that show what kind of difference bodies, spaces, and other physical aspects make in interaction and how that difference can be analyzed in terms of power and authority. The first perspective, presented by Vincent Denault and Pierrich Plusquellec, consists in considering the human body not only as a subject but also as the object of analysis and reflects on ways in which experimental research on nonverbal communication may complete observation of naturally occurring interaction. The second, presented by Nicolas Bencherki and Alaric Bourgoin, proposes a decentering of analysis towards objects and suggest that it is possible to describe them as communicating without reducing them to tools that are only relevant when they are used by human individuals. Finally, a last perspective, presented by François Cooren and Huey-Rong Chen, bridges the gap between verbal and non-verbal communication and proposes a ventriloquial analysis that embraces the confusion between human and non-human participants rather than seeking to neatly sort them out.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".