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Record W4405757455 · doi:10.15688/jvolsu4.2024.5.5

Villages of the Black Earth Region of European Russia in the 17th – First Third of the 18th Centuries

2024· article· en· W4405757455 on OpenAlexaboutno aff
Denis Lyapin, A. R. Melnikova

Bibliographic record

VenueVestnik Volgogradskogo gosudarstvennogo universiteta Serija 4 Istorija Regionovedenie Mezhdunarodnye otnoshenija · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
FundersRussian Science Foundation
KeywordsGeographyQuarter (Canadian coin)Human settlementArable landWork (physics)CensusLand reclamationRegional scienceHistoryEconomic geographyArchaeologyPopulationAgricultureDemographySociologyEngineering

Abstract

fetched live from OpenAlex

Introduction. In the 17th century, in the south of European Russia, in the Black Earth districts, the process of economic development of vast fertile lands took place. The effectiveness of this process was associated with the increase in the number of Russian settlers to work on arable land. Economic success played an important role in the confrontation between Russia and the Crimean Khanate. The war between the two states lasted throughout the 17th century. In recent decades, the study of the history of the development of black earth districts in Russia has continued in various directions, but the problem of economic development of new territories remains relevant for study. Methods and materials. The authors of the article use data on the number of villages as a criterion for assessing the process of reclamation of empty lands. The authors focus on the villages of the three largest regions of the Black Earth region – the Belgorod, Voronezh, and Yelets regions. Materials from the Kozlov region are used as additional information. The materials for the work were mass sources – census books of the 17th – first quarter of the 18th centuries. Results. As a result of the study, an increase in the number of rural settlements and changes in their internal structure were recorded in favor of the increase in large villages. All this testifies to Russia’s economic success in the region and allows us to understand some of the features of this process. There is also no doubt about the steady demographic growth throughout the 17th century. These factors played an important role in the struggle for the annexation of the Black Earth Strip to Russia during periodically escalating military conflicts and political confrontations. Contribution of the authors of the article: D.A. Lyapin – concept development, writing of the introduction, analysis of the results. A.R. Melnikova – processing of materials for the article, writing of the section “Materials and methods,” design of the article. D.A. Lyapin – 50%, A.R. Melnikova – 50%. Funding. The research was carried out at the expense of a grant from the Russian Science Foundation (project No. 24-68-00011, https://rscf.ru/project/24-68-00011/) on the basis of Bunin Yelets State University.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0040.001
Research integrity0.0000.001
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 head0.223
Teacher spread0.205 · 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.

Study designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueVestnik Volgogradskogo gosudarstvennogo universiteta Serija 4 Istorija Regionovedenie Mezhdunarodnye otnoshenijaSame topicRegional Socio-Economic Development TrendsFrench-language works237,207