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Record W2884409853 · doi:10.26565/2076-1333-2018-24-03

Transformation of the agrarian sphere of Ukraine: approaches to study

2018· article· en· W2884409853 on OpenAlexaff
Liudmyla Niemets, Maryna Lohvynova, Yuriy Kandyba, Lyudmyla Klyuchko, Oleksiy Kraynukov

Bibliographic record

VenueHuman Geography Journal · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture Market Analysis Ukraine
Canadian institutionsGLS Industries (Canada)
Fundersnot available
KeywordsAgrarian societyTransformation (genetics)Economic systemPolitical scienceGeographyEconomicsArchaeologyAgricultureBiology

Abstract

fetched live from OpenAlex

The relevance of the study is due to the absence in the scientific literature of an unambiguous definition of the concept of "transformation of the agrarian sphere." In our understanding, the transformation of the agrarian sphere is a socio-geographical process that is characterized by a change in the sectoral, territorial structure and system of the agrarian sphere on different scales, caused by the transformation of the entire economic system or certain of its structural elements. The reasons for significant changes in the agrarian sphere of Ukraine is the change in the socio-political, economic and other spheres, the heterogeneity of natural conditions and the demographic situation. The beginning of the agrarian transformation in Ukraine is considered the period of its independence, since there was a transition from the command-administrative economic system to the market one. However, due to the lack of clear goals of transformation, this process did not bring the expected results.

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)0.001
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: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0040.010
Scholarly communication0.0080.004
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.217
Teacher spread0.170 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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