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Record W1992184018 · doi:10.1080/14636778.2012.662051

Knowledge, place, and power: geographies of value in the bioeconomy

2012· article· en· W1992184018 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

VenueNew Genetics and Society · 2012
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsYork University
Fundersnot available
KeywordsValue (mathematics)CapitalismArgument (complex analysis)SociologyPower (physics)Intersection (aeronautics)Knowledge productionEnvironmental ethicsSocial sciencePolitical scienceEpistemologyPoliticsKnowledge managementGeographyBiologyLaw

Abstract

fetched live from OpenAlex

The idea that there is an emerging “bioeconomy” characterized by the capture of the latent value found in biological material (e.g. cells, tissues, plants, etc.) has become a popular policy agenda since the mid-2000s. A number of scholars have also written about this intersection between the life sciences and capitalism, often drawing on anthropological and sociological perspectives to conceptualize the new socialities, subjectivities, and identities brought about by new biotechnologies. While these studies are undoubtedly a fruitful academic enterprise, they have also left a gap in our understanding of the bioeconomy because they have not discussed knowledge or knowledge production. This article focuses on this immaterial side of the bioeconomy, exploring the geographies of value in the bioeconomy that are constituted by intangible and immaterial resources and labor. The core argument is that value in the bioeconomy is created from geographical processes that both embed immateriality in particular places and, at the same time, abstract it in global standards and regulations.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.140

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.285
Teacher spread0.268 · 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