Bibliographic record
Abstract
Olga Tokarczuk has been one of the most read and popular Polish authors in the Czech Republic for the past quarter of a century. She brings unquestionable values to the Czech cultural and social scene, which are both an inspiration and a challenge for Czech readers. Her fictional worlds reflect her clear personal opinions and views on many problematic phenomena of the contemporary world, which she also declares in her civic attitudes. The cognitive value of her works is comparable to that of great Czech authors (K. Čapek, M. Kundera). The aim of the study is to show the personality of the author and the position of her work in the Czech cultural (translations, critical reception, reader reception) and media context (interviews, informative articles, appearances on television and radio, visits to the Czech Republic). The response in both contexts is growing with each newly translated book, especially noticeable in the period after the Nobel Prize in 2019. Thirteen of her books have been translated into Czech (Petr Vidlák, Iveta Mikešová, Renata Putzlar Buchtová, Barbora Doležalová). Tokarczuk’s personality makes the element of mutual respect, harmony, sharing, crossing the borders of the state and the nation present in Czech-Polish ties. Her work and attitudes convey a deeply human perception of goodness, equality and justice.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".