Bibliographic record
Abstract
This article assesses the cornucopian theory of the mastery of plastic nature. Serious deficiencies are found, especially the theory's complacent faith in economic rationality and its underestimation of nature's capacity for unexpected emergent disturbances. Conclusions about the real state of the world and realistic expectations for the future must take into account not only present trends, but also the findings of research into disasters and societies that have collapsed. Learning from the analysis of such discontinuities and breaking points will help to avoid simplistic presumptions of safety based on extrapolating time-series trends of present well-being in wealthy societies into the distant future. It is precisely disaster research and studies of collapsed societies that can teach us about failures of foresight concerning nature's dynamics, about the material consequences of such errors, about the uncertainties involved in foreseeing nature's emergent dynamics, and about social barriers to learning from the prompts of nature. Although apologetics for business-as-usual, full-steam-ahead practices that masquerade as realism should be rejected, a deeper realism that has learned to expect the unexpected from nature is necessary. Such a critical realist perspective for investigating prompts from nature has been elaborated in this article.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".