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Record W330153481

Хозяйственное освоение Томского уезда служилыми людьми в XVIII в

2011· article· ru· W330153481 on OpenAlexaboutno aff
Чурсина Анна Анатольевна

Bibliographic record

VenueВестник Томского государственного университета. История · 2011
Typearticle
Languageru
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsPeasantService (business)GeographyEthnologyQuarter (Canadian coin)AgricultureHistorySocioeconomicsArchaeologySociologyEconomy
DOInot available

Abstract

fetched live from OpenAlex

During the 17th century several agricultural regions appeared on the territory of Tomsk uyezd. The article is concerned with the developing of Podgorodny and Spassky regions by the men of service and their descendants. The region had appeared before the all the rest ones and became the foundation for the further colonization of the uyezd lands. In 1720 Podgorodny region includes 65 farms, 40 of them belonged to the men of service, retired Cossacks and Cossack children. 18 farms belonged to the posadsky people, 5 farms belonged to the widows of the men of service and two ones belonged to the obrochny people. The peasant farms havent been mentioned. The family composition of the men of service was represented with the Arkashevs, the Bazhenins, the Gutovyms, the Grigorivskys, the Kolmogorovs, the Kuznetsovs, the Kuchumovs, the Olovenishnikovs, the Permitinovs, the Petukhovs, the Plotnikovs, the Protopopovs, the Chuskaevs. If in 1720 only 15% of the men of service didnt have any tillage, by 1759 among their descendants there were 73% landless. But only the fifth part of raznochinetz had the tillage in 0,5 1 dessiatina, but only 6% of the descendants of the men of service of Podgorodny region cultivated in 2 dessiatinas. In the first quarter of the 18th century in the composition of Spassky region one managed to determine besides Spassky region the village of Baturino, Verkhnebasandaisky, Ipatova, Vershinino and Kaltaiskaya. The men of service and Cossack children were represented with 23 families. The peasants lived only in Spassky village. By the middle of the century the percent of the uncultivated farms increased. Their quantity composed of 32%, the majority of the farms composed of the lands being cultivated from 0,5 to 2 dessiatinas (45%, 42 farms). Only in the village of Kaltaisky and Vershinino it has been observed the increase of the areas under crops in 2 5 dessiatinas in separate farms of the descendants of the men of service. In spite of the fact that 15% of the peasants didnt have any tillage by the end of the century, as a whole the increase of the areas under crops composed of 1,5 dessiatinas in one farm during the century. In Podgorodny region the raznochinetz of 112 farms were horseless and composed of 28 (25%) masters of the farm, there was only one horse in 40% of the farms. In Spassky region only 10 people (11%) didnt have any horses among 93 masters-raznochinetz, the whole number ran to 198 horses, on average in 2 for one farm. As for the peasants of Spassky region among 67 masters of the farm 10 (15%) of them didnt have any horses, on average there were about 3 horses in one farm. 20 people (35%) had only one horse. Thus the men of service became the first who started to develop the mentioned lands in agricultural meaning. The peasants lived only in Spassky village. The extension of the lands under crops during the 18th century was insignificant. Many descendants of the men of service gave up farming. It has been observed the small but stable increase of the areas under crops in Spassky village, the majority of its inhabitants made up the descendants of the peasants first settlers.

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)0.002
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 score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0040.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.004

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 head0.112
GPT teacher head0.284
Teacher spread0.172 · 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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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