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Record W4386203269 · doi:10.31518/2618-9100-2023-4-9

State Policy to Create a New Migration Model in the Russian Empire in the Second Half of the 19th – Early 20th Centuries

2023· article· en· W4386203269 on OpenAlexfundno aff
Sergey V. Vinogradov, Yuliya G. Yeshchenko

Bibliographic record

VenueHistorical Courier · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
FundersRussian Science FoundationQueen's UniversityMcGill University
KeywordsPeasantSerfdomEmpireState (computer science)Political scienceDebtEconomyGeographyEconomic historyEconomicsLawFinance

Abstract

fetched live from OpenAlex

The article analyzes the main components of migration policy implemented in the Russian Empire in the second half of the 19 th -early 20 th centuries.Within the framework of the concept of three stages of the migration process the authors characterize the migration model that developed during the period under study, which implied planning (development of the main directions of state migration policy); organization of the movement of labor resources (creation of appropriate management and administrative structures); consolidation and adaptation of migrants (providing benefits to migrants, debt forgiveness, loans for the initial settlement).Before the peasant reform, the main task of the government, which defended in its domestic policy the interests of, primarily, the landowning nobility, was the retention of peasants in the landed estates through the system of serfdom.Under these conditions, internal migration developed poorly and the vast peripheral territories that entered the Russian Empire in the seventeenth and nineteenth centuries were developed and populated very slowly.The main sources of settlement in the new lands were: 1) "free migration", consisting of runaway serfs, former soldiers and representatives of free estates, such as merchants, Cossacks, etc.; 2) peasant migration, which implied the resettlement to new lands of state peasants, who were forced to do so on a mandatory basis by the state authorities.But these sources, given the vastness of the developed territories, were clearly insufficient.The development of a new migration model was due to a change of vector in the socioeconomic development of the country.Its difference from the previous model was the emergence of the labor market and, accordingly, an increase in migration flows to the outskirts in the context of a shortage of agricultural land and the relative overpopulation of villages in the old agrarian areas.In the emerging new system of socio-economic relations, the state, interested in the rapid development of the peripheral territories, had to regulate the movement of migration flows, setting * Сергей Вадимович Виноградов, доктор исторических наук, профессор, Астраханский государственный университет им.В.Н.Татищева, Астрахань, Россия,

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.300
Teacher spread0.260 · 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 designTheoretical or conceptual
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
Published2023
Admission routes1
Has abstractyes

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