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Record W2319597460 · doi:10.1177/0032329213507553

Regulation in the Process of Building Capabilities

2013· article· en· W2319597460 on OpenAlex
Paola Perez-Aleman

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

VenuePolitics & Society · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsMcGill University
Fundersnot available
KeywordsProcess (computing)BusinessSustainabilityProduction (economics)UpgradeIndustrial organizationKnowledge managementProcess managementMarketingEconomicsComputer science

Abstract

fetched live from OpenAlex

To understand how regulation influences competitiveness and upgrading processes, this article focuses on the organizational changes involved in “rewarding regulation.” Through a qualitative study of two clusters in the agrifood industry in Nicaragua, it analyzes two types of regulation and their interaction with small producers’ production organizations: food safety and environmental sustainability. The analysis shows that regulation plays a crucial role in fostering changes in organizational practices and routines. This occurs when local organizations build new knowledge and skills to upgrade products and production processes, while developing new connections among producers and between them to other private and public actors that support economic development. “Rewarding regulation” is part of a process of learning and creating networks that help build local know-how and generate supportive collective resources.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.998

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 communication0.0000.001
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 head0.017
GPT teacher head0.271
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