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Deportations, “Repatriations,” and Other Types of Forced Migration as Aspects of Security Policy

2010· book-chapter· en· W769459418 on OpenAlexaff
Alexander Statiev

Bibliographic record

VenueCambridge University Press eBooks · 2010
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSoviet and Russian History
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer securityBusinessComputer science

Abstract

fetched live from OpenAlex

Nado vyselit' s treskom! [Kick them out!] – Stalin's note on the proposal of the Southern Front Headquarters to deport ethnic Germans For centuries, states have expelled parts of their populations to other regions within their borders or abroad, seeking to remove from areas threatened by a foreign or internal enemy those whose loyalty they questioned, to facilitate unpopular policies, or to seize lands for more favored groups. Mass deportations differ in principle from the exile of convicts. Convicts are sentenced for certain crimes to specific terms of exile after routine court procedures, whereas deportations are often preemptive, targeting not individuals but groups of potential troublemakers defined on the basis of ethnicity, race, religion, or class, and victims usually are exiled forever by emergency decrees. Depending on the objectives and nature of the state, deportation could be more or less painful to its victims. In the nineteenth century, it was a routine colonial practice, and during World War I, many states exiled or interned citizens who shared ethnicity with enemy nations. Germany deported many Poles and Jews and planned to remove all Slavs from eastern frontier regions, Austria-Hungary expelled Serbs from occupied lands, and Canada interned recent immigrants from Austria-Hungary. In 1915, the Ottomans deported the Armenians who escaped slaughter from the Russian border to Syria. In the 1920s, Greece, Bulgaria, and Turkey exchanged diaspora populations to forestall security problems, and in the 1930s, the Nazis expelled Jews from Germany.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.017
Scholarly communication0.0060.006
Open science0.0010.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicSoviet and Russian HistoryFrench-language works237,207