Niedzwiedzia Przysluga?Bear’s Favor? Hidden Garden behind the Concrete Proverbs: Cognitive-Semantic Analysis of Proverbs in Persian, Polish and Spanish
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Proverbs help us understand how the society works at large and what are the main concerns regarding the environment, people-to-people exchange and notions of liberty, freedom and values. In some cultures such as the Iranian one, the way one uses proverbs depends on the generation one finds herself in. Generation-gap provides opportunity to transfer some abstract and complicated concepts, not available in modern life, through the use of proverbs. From childhood, by hearing proverbs from parents and grand-parents, children begin grasping some important national and even religious concepts. In order to represent a rather international, holistic view and not language-specific, we analyzed further Polish, French and Spanish proverbs, whenever deemed necessary. The present paper through cognitive-semantic and content analysis aims to reveal the implied systems of value, ethics and morality realized through proverbs. The results clearly indicate that proverbs cover different systems of values through elements such as artifacts, animals, human body parts and even imaginary, nature-derived elements.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it