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Record W4396645276 · doi:10.1111/joms.13080

Biocentric Work in the Anthropocene: How Actors Regenerate Degenerated Natural Commons

2024· article· en· W4396645276 on OpenAlexaff
Laura Albareda, Oana Branzei

Bibliographic record

VenueJournal of Management Studies · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsWestern University
Fundersnot available
KeywordsAnthropoceneCommonsEnvironmental ethicsWork (physics)Natural (archaeology)Environmental resource managementSociologyPolitical scienceEcologyGeographyBiologyEnvironmental sciencePhilosophyArchaeologyEngineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.535
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.286
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2024
Admission routes1
Has abstractyes

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