MétaCan
Menu
Back to cohort

The Intelligentsia and the October Revolution

2017· article· pt· W2735053687 on OpenAlexaff
David R. Mandel

Bibliographic record

VenueAmericanae (AECID Library) · 2017
Typearticle
Languagept
FieldSocial Sciences
TopicSoviet and Russian History
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsIntelligentsiaAlienationDemocratic revolutionDemocracyPolarization (electrochemistry)SociologyPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

Este artigo examina a atitude da intelligentsia “democrática”, de orientação de esquerda, para com as revoluções de 1917. Documenta e analisa sua crescente alienação posterior em relação às classes populares, operários e camponeses, ao longo de 1917. Essa alienação é explicada no marco do aprofundamento da polarização da sociedade russa, um processo cujas raízes podem ser encontradas na revolução de 1905, e até mesmo antes dela, mas que alcançou seu ápice em 1917, na Revolução de Outubro. Essa revolução se revelou um evento exclusivamente plebeu, diante do qual a intelligentsia de orientação de esquerda foi bastante hostil, situação esta que preocupou profundamente os ativistas operários.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.014
Scholarly communication0.0090.003
Open science0.0000.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.019
GPT teacher head0.276
Teacher spread0.257 · 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 designTheoretical or conceptual
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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAmericanae (AECID Library)Same topicSoviet and Russian HistoryFrench-language works237,207