Where bonds become binds: The necessity for Bateson’s interactive perspective in biosemiotics
Bibliographic record
Abstract
The paper examines important discrepancies between major figures influencing the intellectual development of biosemiotics. It takes its perspective from the work of Gregory Bateson. Unlike C. S. Peirce and J. von Uexküll, Bateson begins with a strong notion of interaction. His early writings were about reciprocity and social exchange, a common topic among anthropologists of the time, but Bateson’s approach was unique. He developed the notion of meta-patterns of exchange, and of the “abduction” of these metapatterns to a variety of other phenomena, in both biology and in game theory. Later, Bateson’s concept of ecology of mind, the product of interactive phenomena, was modified by a non-purposive cybernetics. Biosemiotics has yet to adopt Bateson’s interactive stance, which is absent from Peirce’s approach to communication, of Uexküll’s functional cycles, and of Hoffmeyer’s discussion of the relation between culture and environment. Rather than pursuing notions of appropriate “subjectivity” through changed ethical response to ecological conditions (Hoffmeyer’s discussion of empathy), the paper discusses the advantages of an approach that continues to focus on conditions of paradox and pathology. Specifically, Bateson’s resolution of the relation between culture and environment arises from situations of blocked communication where ecological bonds become binds.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.061 |
| Scholarly communication | 0.014 | 0.022 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".