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Record W2076279362 · doi:10.1080/08941920120686

Industrial Dynamics and the Problem of Nature

2001· article· en· W2076279362 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSociety & Natural Resources · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Economy and Marxism
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIndustrialisationProduction (economics)AnalogyContrast (vision)Set (abstract data type)Industrial organizationNeoclassical economicsEconomicsBusinessEconomic systemComputer scienceEpistemologyMicroeconomicsMarket economyArtificial intelligence

Abstract

fetched live from OpenAlex

Existing literature suggests that food, fiber, and raw material sectors differ from manufacturing in significant ways. However, there is no analytical basis for engaging the particular challenges of nature-centered production, and thus the distinct ways that industrialization proceeds in extractive and cultivation-based industries. This article presents a framework for analyzing the difference that nature makes in these industries. Nature is seen as a set of obstacles, opportunities, and surprises that firms confront in their attempts to subordinate biophysical properties and processes to industrial production. Drawing an analogy from Marxian labor theory, we contrast the formal and real subsumption of nature to highlight the distinct ways in which biological systems - in marked contrast to extractive sectors - are industrialized and may be made to operate as productive forces in and of themselves. These concepts differentiate analytically between biologically based and nonbiologically based industries, building on theoretical and historical distinctions between extraction and cultivation.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.261
Teacher spread0.251 · 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