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Record W1907622175

연해주 韓人의 중앙아시아로의 강제이주와 정착 그리고 사회ㆍ경제적 현황

2007· article· ko· W1907622175 on OpenAlexaboutno aff
전신욱

Bibliographic record

Venue통일문제연구 · 2007
Typearticle
Languageko
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsEmigrationChinaPolitical scienceEconomic historyHistoryLaw
DOInot available

Abstract

fetched live from OpenAlex

When we think about the history of emigration, we are always reminded of the severe sufferings. In our history of emigration, the one to Russia and China is truly a path of hardships. This year(2007) is the 70th anniversary that Stalin deported forcibly our Koreans from Maritime Territory to Central Asia in september 1937. The forced emigration policy by Stalin was a tragic event that Koreans were terribly suffered and tried. There is no case that had been deported like such a thing by anothe person's will in our history of emigration. The emigration or move to Maritime Territory, Hawaii and all countries of the world had been realized by their own will. In order to break through the gathering clouds of a crisis as affairs at home and abroad and as part of the program to rearrange dispersively a minority race at that time, the Soviet Union had expelled our Koreans to a bleak, windswept moor. Also, creating a terror atmosphere the Soviet Union had killed a lot of korean intellectuals and leaders. As doing a compulsory execution for emigration, Koreans were not treated as a human being and died from hunger and severe cold. As long times had gone, Koreans of Central Asia had achieved economic stability with perseverance which is intrinsic to Korean people. Under a fever searching for education, their children could have taken high -level education. After that, they could have a various headworking occupations. Also, they introduced an agricultural production know-how like a private farming, or 'gobonzil'(a seasonal agriculture). But Independent States of Central Asia had shifted to their country-oriented policies. Therefore, Koreans were faced with various difficulties. After all, according to self country-oriented language policy, they compelled to use only an aboriginal language at all public sectors. So, Koreans had to learn it. They had a lot of difficulties to learn it, to overcome an economic poverty and to choose an occupation. There-by, many Koreans have intention to move to other countries, and regions (for example, Maritime Territory, United States, Canada, and so on).

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)0.005
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 score0.020
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.011
Scholarly communication0.0090.015
Open science0.0010.003
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0200.005

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 head0.031
GPT teacher head0.312
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

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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