Bibliographic record
Abstract
The master's thesis examines the meaning of the past tenses used by Albert Camus in his novels The Stranger and The Fall and the possibility of their transfer to Czech. The present thesis takes a theoretical and empirical approach. The theoretical part provides an overview of the French past tenses and their meanings and deals with their functions within the narrative text. It also attempts to express the specific use of French past tenses in Camus's works analysed. The thesis does not omit describe the possibilities that the Czech language has to express the past. The empirical part is devoted to the analysis of the existing Czech translations of the novels The Stranger and The Fall with an emphasis on capturing the meanings of the past tenses defined in the theoretical part. Using the Czech translations, it seeks ways of creating equivalent effects in Czech and compares the translators' approaches. Key words: the role of the past tenses in the narrative text, passé composé, passé simple, imparfait, plus-que-parfait, Albert Camus, The Stranger, The Fall
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.072 | 0.024 |
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".