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Record W2078630073 · doi:10.5539/res.v7n3p158

Russian Historical Science in the New Paradigm Conditions

2015· article· en· W2078630073 on OpenAlexvenueno aff
И. А. Гатауллина, Olga Mikhailovna Gilmutdinova

Bibliographic record

VenueReview of European Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsnot available
Fundersnot available
KeywordsEpistemologyObjectivity (philosophy)Context (archaeology)PostmodernismSociologyPost-industrial societyParadigm shiftMilestoneInterpretation (philosophy)Social sciencePolitical scienceHistoryPhilosophyLaw

Abstract

fetched live from OpenAlex

Based on the review of the methodological transformation in the world humanitaristics, which occurred in the last century, the paper discusses the peculiarities of the development in Russian historical science at the edge of the XX-XXI centuries. The spotlight is the actual problems of history and attempts of the Russian science to “embed” into the context of the new approaches. The paper highlights the civilizational approach and simplification of its understanding, as well as the interpretation of the complexity of “modernism” and “postmodernism” concepts in the sociocultural studies. The central problem is the problem of objectivity of historical knowledge in the glocalization stage and ways to its solution it in the context of the transition from the industrial to the postindustrial society. The scale of its value system is analyzed as a new milestone, which significantly modifies the methodological strategies of the historical science in particular, and the humanitaristics in general. Transdisciplinarity is presented as a new research base in the conditions of a changing paradigm.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.998
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0020.011
Scholarly communication0.0060.006
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.198
GPT teacher head0.441
Teacher spread0.242 · 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.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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