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Record W2568497482 · doi:10.1134/s1019331616060174

A historical picture of German resettlement to Kazakhstan (End of the 19th Century–Beginning of the 20th Century)

2016· article· en· W2568497482 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHerald of the Russian Academy of Sciences · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsKazakhGovernorGermanHuman settlementEmpireSteppeGeographyAncient historyQuarter (Canadian coin)Economic historyEthnologyHistoryEconomyPolitical scienceArchaeology

Abstract

fetched live from OpenAlex

Each nation living in Kazakhstan has its own history of resettlement to the Kazakh steppes. Germans are no exception. In the last quarter of the 19th century, they started to relocate from the Volga region to Akmola and Semipalatinsk oblasts of the Governor-Generalship of the Steppes, Syr Dar’ya oblast of the Turkestan Governor-Generalship, and Turgai and Ural oblasts of the Russian Empire, i.e., preferentially to the north of Kazakhstan, where they founded a host of settlements. The settlers managed to organize their economy and everyday life, strictly followed national traditions, and preserved their religion and culture. The authors investigate the causes of German resettlement to Kazakhstan, the places where they settled, their sociocultural and living conditions, and economic activities.

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.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.313
Teacher spread0.281 · 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