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Development models of the cooperative sector in the agro-industrial complex of North American and European countries

2019· article· en· W3137779669 on OpenAlexaboutno aff
Ivan Viktorovich Palatkin, A. Pavlov

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCooperative Studies and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsGlobalizationContext (archaeology)LegislationLegislatureAgricultureWork (physics)State (computer science)Economic globalizationRegional scienceBusinessEconomic geographyPolitical scienceEconomic systemEconomic growthEconomyEconomicsGeographyMarket economyEngineering

Abstract

fetched live from OpenAlex

Abstract The research focuses on the characteristic features of the modern development in the cooperative sector in the agro-industrial complex of North American and European countries, taking into account the existing differences in legislation, national traditions, local differences, and the importance of the cooperative movement to search for effective responses to the new challenges of globalization of the economic space. The purpose of the work is to identify the most significant achievements and features inherent in the cooperative sector in the agro-industrial complex of the USA, Canada, France, and Spain. The paper presents quantitative data characterizing the level of development of cooperation in individual countries and the legislative framework for the functioning of agricultural cooperatives. The areas of activity of the largest cooperatives and measures for state support of the development of the cooperative movement in the USA, Canada, France, and Spain are considered. As a result, conclusions were formulated reflecting the significance of the contribution of cooperatives to the economic and financial stability of countries in the context of globalization, to the creation of jobs and increasing the innovative potential of business.

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)0.000
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 score0.046
Threshold uncertainty score0.548

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 studies0.0000.001
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 head0.033
GPT teacher head0.186
Teacher spread0.153 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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