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Record W3105968372 · doi:10.6000/1929-4409.2020.09.113

The Problem of Own and Alien in Dovlatov's Cycle “Suitcase”

2020· article· en· W3105968372 on OpenAlexvenueno aff
Sara Mahbobzadh, Liliya Harisovna Nasrutdinova, Girish Munjal

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSociopolitical Dynamics in Russia
Canadian institutionsnot available
FundersKazan Federal University
KeywordsAlienHEROIdeologyOpposition (politics)AppealCharacter (mathematics)Value (mathematics)LiteratureSociologyAestheticsHistoryLawPolitical scienceArtPoliticsComputer science

Abstract

fetched live from OpenAlex

The article deals with various aspects of the reception of the concepts "Own" and "Alien" in S. Dovlatov's "Suitcase" cycle: material, ideological, philosophical, socio - and ethnocultural, etc. Special attention is paid to the reception of the categories of Soviet and official as not-Own. An important component of the problem of Own and Alien in the "Suitcase" cycle is also the attitude of the hero-narrator to Soviet and American culture. Widely articulated desire to associate his biography and professional activities allows us to conclude about the hero’s attempt to position himself as a person outside the Soviet system. The appeal to the realities of culture helps the author to identify their value orientations and express their attitude to people and the world. Certainly, the significance of the problem of the correlation of Own and Alien in the literary heritage of S. Dovlatov is predetermined by his status as a dissident writer and an immigrant writer. However, the writer is not characterized by a tendency toward the antithetic character of creating an opposition between Own and Alien. In the art world of S. Dovlatov, there are no types of "stigmatized Alien" and "hostile Alien". Moreover, the model of his interaction with the world is defined as "Own among your Own".

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)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.019
Scholarly communication0.0070.003
Open science0.0010.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.054
GPT teacher head0.368
Teacher spread0.313 · 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
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
Published2020
Admission routes1
Has abstractyes

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