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Record W2895743259

Деградация семьи в романе В.П. Аст Афьева «Печальный детектив» и романе Р. Сенчина «Елтышевы»

2018· article· ru· W2895743259 on OpenAlexaboutno aff
Aldona Borkowska

Bibliographic record

VenueRepoS (Uniwersytetu Przyrodniczo-Humanistycznego w Siedlcach) · 2018
Typearticle
Languageru
FieldSocial Sciences
TopicSocial and Behavioral Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutionVariety (cybernetics)Quarter (Canadian coin)SociologySocial institutionLawWork (physics)Total institutionHistoryPolitical scienceSocial scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

The aim of this article is comparative analysis of prose by Victor Astafiev and Roman Sienchin. \nThe protagonists of both novels are policemen who have completed their work and try to find them selves in the new reality. The lives of their families are somehow suspended between town and country, which is no longer the mainstay of moral values, work ethic, and contact with nature. \nThe two novels are separated by a quarter of a century. “Sad Detective” by Astafiev is a record of the downfall of Soviet society in the era of the approaching change, for which there is no sanctity and authority. Astafiev saw the rescue for Russia only in the institution of the family in her patriarchal variety. Roman Sienchin’s “The Eltyshevs” can be interpreted as one of the possible variants of the fate of a society that does not comply with Astafiev’s recommendations. The family as the fundamental social institution did not meet the desirable expectations. Suffering numerous “diseases” it is not able to fulfill its eternal functions. Unlike Astafiev, Sienchin does not judge his characters and does not give them advice for the future. It \nis hard not to agree with the opinion of one of the researchers who defines the work as “a novel-diagnosis”. Diagnosis is given, but there is no prescription

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)0.003
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 score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0060.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.004

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 head0.059
GPT teacher head0.353
Teacher spread0.294 · 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
Published2018
Admission routes1
Has abstractyes

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