Bibliographic record
Abstract
In his play Happy Days, Samuel Beckett portrays against a wilderness of modern world an optimistic woman—Winnie, who has strong nerves and fights against overwhelming nothingness in various forms on her own. Arguing that she is a lonely fighter against nothingness, this essay is dedicated to Winnie and focuses itself on answering following questions: Since the world in Happy Days is surrounded and incessantly eroded by nothingness, what forms are they in and how do they work.; as an extremely deprived person, why could Winnie be called nothingness-fighter and in what ways does she succeed in struggling along. Key words: Winnie, nothingness, fighter, fighting means, identity Resume: Dans le theatre Oh les beaux jours, Samuel Beckett a campe une femme dynamique et optimiste luttant contre le monde moderne desert— Winnie. Douee d’un courage exceptionnel, elle lutte seul contre le neant irresistible sous de diverses formes. L’essai present analyse le personnage de Winnie et repond aux questions suivantes. Puisque le monde dans la piece est entoure et devore par le neant, le neant apparit sous quelle forme ? quel est son role ? Puisque privee de tout, pouquoi elle peut encore etre consideree comme « lutteuse contre le neant » ? comment survit-elle difficilement dans l’interstice d’avec le neant ? Mots-Cles: Winnie, neant, lutteuse, moyen de lutte, statut
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".