Biocentric Work in the Anthropocene: How Actors Regenerate Degenerated Natural Commons
Bibliographic record
Abstract
Abstract As natural commons vital to selves, organizations, and institutions collapse under cumulative anthropogenic pressures, can human agency still reverse some of the damage already done? This article explores how emerging forms of social symbolic work regenerate degenerated natural commons. Using a five‐year multi‐sited immersive ethnography of natural commons that had collapsed, we explain how actors (re)turn to the biophysical roots of socio‐ecological systems to take care, work with, and care for nature. We show how actors’ comprehension develops over time by connecting their social‐symbolic construction of natural commons post collapse with three sets of practices we label biomanipulation, biofacilitation, and bioaffiliation. We inductively theorize biocentric work as a processual form of social‐symbolic work that connects three cycles of material abduction, relational intercession, and discursive grounding. Our tri‐cyclical process model underscores the biophysical foundations of social‐symbolic work in the Anthropocene by explicitly and iteratively situating self, organizations and institutions in the states and dynamics of natural commons.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.032 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".