MétaCan
Menu
Back to cohort
Record W2086189563 · doi:10.5539/ass.v10n23p168

Mechanism of Rural Entrepreneurship Development on the Base of Micro-business

2014· article· en· W2086189563 on OpenAlexvenueno aff
Tatiana A. Zabaznova, Svetlana E. Karpushova, Elena V. Patsyuk, Olga A. Surkova, Галина Хмелева

Bibliographic record

VenueAsian Social Science · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigitalization and Economic Development in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsEntrepreneurshipMechanism (biology)Subordination (linguistics)BusinessAgricultureAgribusinessGovernment (linguistics)Industrial organizationScope (computer science)Process managementEconomic systemEconomicsComputer scienceFinance

Abstract

fetched live from OpenAlex

The author analyzes the essence of rural business development strategy, is a model of strategic management ofagricultural entrepreneurship, and defines the basic components of the major actions to ensure theimplementation of strategies for the development of agricultural entrepreneurship, aimed at selection of optimaldirections and priorities of development of the territory. The author develops and justifies the mechanism ofdevelopment of agricultural entrepreneurship, based on micro-businesses; it allocates system mechanisms for theimplementation of strategies, and analyzes its key components. The author is an agricultural business model ofmotivation and mechanism of changes in strategy. The author defines the space program-target method in themechanism of external control of strategic management of agribusiness takes application. The author defines thesystem of normative legal acts that have a logical connection and subordination and regulating the use of specificmethods and tools of government regulation necessary for the successful combination of marked intra andexternal strategic activities for the development of agricultural 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.014
GPT teacher head0.195
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueAsian Social ScienceSame topicDigitalization and Economic Development in AgricultureFrench-language works237,207