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Record W7027148873

The author and protagonist in Demons : similarities in communication style and functions

2006· dissertation· en· W7027148873 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2006
Typedissertation
Languageen
FieldSocial Sciences
TopicRussian Literature and Bakhtin Studies
Canadian institutionsnot available
FundersMcGill University
KeywordsIdeologyStyle (visual arts)HEROMerge (version control)PoliticsCriticismPolitical communication
DOInot available

Abstract

fetched live from OpenAlex

Fedor Dostoevskii and Petr Verkhovenskii, the author and one of the main protagonists of the novel Demons, exhibit the same communication style and pursue similar propagandistic purposes in their public communication. Both figures function in the framework of public relations, employing mass communication for the sake of publicizing their political messages to broad audiences. In the process of their public communication, the author and the hero of the novel merge literature and journalism, fictional and factual discourse, subvert a critical analysis of their respective messages and encourage an unconditional, if unwarranted, acceptance of their communication. Relying on the theoretical findings of John Austin, Jurgen Habermas, as well as using the theoretical models of mass communication, the present study shows the underlying bond between Dostoevskii and Petr Verkhovenskii in terms of their communication style despite the ideological gulf that separates the two seemingly irreconcilable sides.

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)0.006
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.009
Scholarly communication0.0060.004
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.016
GPT teacher head0.277
Teacher spread0.261 · 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
Published2006
Admission routes1
Has abstractyes

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