Gregory Bateson’s Contribution to Understanding the Linguistic Roots of the Ecological Crisis
Bibliographic record
Abstract
The five core ideas of Gregory Bateson discussed here challenge a widely held orthodoxy taken for granted by many academics, including western philosophers. Namely, that language functions as a neutral conduit in a sender receiver process of communication. This assumption sustains the idea of a culture-free rational process, and objective information and data. It also hides the linguistic colonization of the present by the past, which is critical to understanding why we continue to rely upon the same mind-set that is contributing to the ecological crisis to fix it. Bateson’s five key ideas––the recursive nature of our guiding epistemologies, the disconnect between our conceptual maps (metaphorical interpretative frameworks constituted in the distant past) and today’s cultural/ecological realities, how the difference which make difference is the most basic source of information circulating through both cultural and natural ecologies, the nature of double bind thinking, and the need to move to Level III learning––provide a conceptual framework for understanding the difference between ecological and individual intelligence, and why so little attention is given by environmentalists and philosophers to the linguistic roots of the ecological crisis.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| 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".