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Record W1970142087 · doi:10.5539/res.v7n8p156

Traditional Values of Eastern Finno-Ugrians as Evidenced in Proverbs and Sayings

2015· article· en· W1970142087 on OpenAlexvenueno aff
Natalia Glukhova, Raisiya А. Kudryavtseva, Rodion I. Chuzaev, Galina E. Shkalina

Bibliographic record

VenueReview of European Studies · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Philosophical and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupFolkloreLinguisticsMetalanguageValue (mathematics)AxiologyOrder (exchange)Computer scienceEpistemologySociologyMathematicsAnthropologyStatisticsPhilosophy

Abstract

fetched live from OpenAlex

The objective of the article is to reveal and describe the value systems of the Komis, Maris, Mordvins and Udmurts as reconstructed from the folklore genres of proverbs and sayings of the ethnic groups under discussion. The authors apply a complex technique to 13820 proverbs taken from specialized dictionaries published in the four corresponding republics. The strategy involves the use of semantic analysis as well as quantitative evaluation carried out with the help of a linear correlation coefficient. The algorithm of the investigation consists of several steps. The most important stage includes the process of discerning values, called “factors”, from proverbs and sayings with the help of componential and contextual types of analysis. Statistical methods revealed the most important eight values common to the four eastern Finno-Ugrian ethnic groups which are arranged in a descending order of their number and frequency of occurrence. The findings of an investigation into traditional axiology are also presented with the help of graphical metalanguage—as the tabulated data and in the form of diagrams.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.755
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.357
GPT teacher head0.322
Teacher spread0.034 · 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 teacher head, 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

Citations1
Published2015
Admission routes1
Has abstractyes

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