Traditional Values of Eastern Finno-Ugrians as Evidenced in Proverbs and Sayings
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".