Sjećanje kao pokušaj odbrane od zla u romanu Filipa Davida „Kuća sećanja i zaborava”
Bibliographic record
Abstract
U ovome radu predmet naše analize bit će usmjeren na kategoriju sjećanja i njegovu funkciju u istraživanju povijesti, koja će odrediti junakovu sudbinu u djelu Filipa Davida Kuća sećanja i zaborava. Budući da je roman strukturiran od odvojenih priča koje povezuje ista sudbina, pokušaćemo da opišemo na koji način sjećanje utiče na glavnog junaka Alberta Vajsa, da li ono izobličuje njegovu ličnost ili je zarobljava u povijesti.Introspektivnim tehnikama unutrašnjeg monologa i naglašenom psihološkom motivacijom analiziraćemo likove trojice Albertovih prijatelja (Solomon Levi, Miša Volf i Urijel Koen) kako bismo definirali funkciju pojmova sjećanja i zaborava. Pokušat ćemo objasniti naslovnu sintagmu romana i tako dati odgovore na pitanje da li je sjećanje put izbavljenja ili odbrana od zla. Dramski elementi, emocionalni naboj, fantazmagorične slike i košmari, samo su neke od specifičnosti romana. S obzirom na to da se Albert Vajs odriče mogućnosti da zaboravi i prepušta svojoj sudbini, na kraju dolazimo do zaključka da je sjećanje povezano s identitetom i povijesti, jer postaje svjedočanstvom našega bitisanja.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 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".