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Record W4391530519 · doi:10.1080/08985626.2024.2305648

Human-animal mutualism in regenerative entrepreneurship

2024· article· en· W4391530519 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEntrepreneurship and Regional Development · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInnovation, Sustainability, Human-Machine Systems
Canadian institutionsnot available
FundersLinnéuniversitetetInternational Development Research Centre
KeywordsMutualism (biology)EntrepreneurshipEconomic geographyBusinessEconomicsBiologyEcology

Abstract

fetched live from OpenAlex

In this paper, we explore the micro-interactions through which a regenerative enterprise engages with proximate natural ecosystems in its attempt to repair and protect them. Through an ethnographic study of a regenerative farming enterprise in rural Southern Patagonia -Fundo Panguilemu -we discover a reciprocal relationship between the enterprise and animals, central to their regenerative efforts. This relationship is formed and actively maintained by the founders through three practicesjoint rewilding, ambivalent relationality, and task interdependence. We leverage nature relatedness to conceptualize the relationship between these practices as human-animal mutualism in regenerative work. We advance regenerative entrepreneurship research by revealing novel human-nature interactions formed and fostered by a rural enterprise in the pursuit of local regeneration and expand our understanding of microlevel phenomena in rural entrepreneurship.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.043
GPT teacher head0.341
Teacher spread0.298 · 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