Confrontation and support in bonobo-human discourse
Bibliographic record
Abstract
As part of a program to explore the communicative abilities of bonobo apes within the human-ape culture at the Language Research Center at Georgia State University, we made two complementary analyses of a conversation between Sue Savage-Rumbaugh and Kanzi. We made both a conversation analysis and a lexico-grammatical analysis of their interaction. The conversation analysis revealed the participants negotiating the interpersonal meanings of confrontation and support, while the lexico-grammatical analysis revealed the ideational domain of the confrontation and support. Although many of the contributions of both participants did not fully express all the relevant meanings, both participants interpreted each others contributions in terms of their relevance to the patterns of interpersonal and ideational meanings being expressed in the conversation. We conclude that Kanzis considerable language abilities have been underestimated. First, Kanzi (despite his limited syntax) and Sue jointly construe a recognizable social world through discourse. Second, in exchanging discourse roles with Sue, Kanzi negotiates the asymmetrical power relation between himself and Sue. Finally, Kanzis accomplishment suggests that discourse semantics is a powerful motivation for the evolution of both interpersonal and ideational grammar.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".