Bibliographic record
Abstract
Abstract This essay considers ecology in its singular and plural forms. It asks whether and how the knowledge forms generated by practitioners of the singular science of ecology might weave more fully into a robust plural analytic that is grounded in the acknowledgment of multiple ways of knowing, experiencing, and attributing meaning to consequential connections between the human and the more-than-human world. Although Western science, with singular ecology as one of its many descendants, leaves an undeniable imprint, the essay aims to ask whether the contemporary, lived life of ecological science as postpositivist practice might be working in ways that, while imperfect, may be more legible and shared with scholars in the environmental humanities than is usually noted. It describes the knowledge base of the singular science of ecology, which in contemporary theory and practice consists of collections of disparate, complementary, or contradictory models—ecologies—in the plural, thus holding generality and infinite particularity in constant dialogue. The authors, two natural scientists and one social scientist, aim to provoke fresh discussions about the ways ecological analytics circulate in contemporary research and scholarly practice. The authors’ goal is to further the essential work of more direct and clear conversation, translation, and mutual learning between scholars in the environmental humanities and biophysical ecology. They hold this to be essential as transdisciplinary initiatives endeavor to study, and better understand, how social and environmental change coproduce one another.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.045 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| 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".