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Record W4380575256 · doi:10.1017/9781800108820.007

Isaak Shklovsky, ‘In the Russian Quarter’

2022· other· en· W4380575256 on OpenAlexaboutno aff
Anna Vaninskaya

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicSoviet and Russian History
Canadian institutionsnot available
Fundersnot available
KeywordsHomelandEmigrationPeasantAncient historyQuarter (Canadian coin)HistoryGenealogyUkrainianFlockGeographyEthnologyArchaeologyPolitical scienceLawMedicine

Abstract

fetched live from OpenAlex

In late May of 1903, a huge cargo steamer named the Blücher set out from Hamburg to London. There were horses and people on the ship. Horses are an extremely valuable cargo and quite susceptible to seasickness, from which they suffer greatly, and for this reason they were allocated the best spot on the Blücher . People also suffer from seasickness, but the Blücher passengers belonged to a class one does not make a fuss over. They were mostly the natives of Northwestern shtetls, cowed, small, plain, very poorly clad, marked with the seal of centuries-long chronic malnutrition. The burly sailors shouted at them as they drove them into the black depths of the hold. Men, women and children crawled in obediently, dragging behind them huge bundles and dirty flock-mattresses. Of course, none of them could have said why they had brought along these dirty and worthless rags to their new homeland. Among the scrawny, curly-haired, hook-nosed natives of the Northwestern Krai one could discern emigrants from a different region of Russia, mostly fair-haired ones, and veritable giants by comparison with the Lithuanian starvelings. Jews predominated here, but there were also quite a few Estonians and Poles. Some had already parted with their national caftans and ‘suknyas’ at the border or in Hamburg, but a few proved obstinate conservatives. Among their number was a tall, broad-shouldered Ukrainian in an astrakhan hat, a black peasant overcoat girt with a colourful belt and a pair of enormous boots. This passenger seemed especially bewildered when the emigrants were being driven into the hold in Hamburg. ‘Tell me, are we going?!’ he questioned the sailor desperately. ‘ Vorwärts! Schneller! ’ the sailor shouted. ‘But I need to know if we’ll go soon?’ the passenger kept repeating. Instead of replying, the sailor gave the Ukrainian a shove in the neck. The latter grew furious, threw down the sack he was holding, ground his teeth, quickly turned around and took a swing with his huge heavy fist. But at that moment, somebody grabbed the Ukrainian by the hand and spoke quickly. ‘Let them be! don't raise a ruckus! He didn't understand you. I’ll ask for you. Upon my soul, it's better if you calm down! come! we’ll lie down together,’ said a puny, very nervous and fidgety young man. The Ukrainian sighed, picked up his sack and descended into the hold.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.242
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.2430.001

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 head0.286
Teacher spread0.271 · 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; both teacher heads agree on what is shown here.

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
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicSoviet and Russian HistoryFrench-language works237,207