The theme of aging in the books The Old King in the Exile by Geiger and House of Turtles by Pent
Bibliographic record
Abstract
VORLOVÁ, Kateřina: The theme of aging in the books The Old King in the Exile by Geiger and House of Turtles by Pent. [Bachelor thesis]. UK. Faculty of Education; Department of German Studies. Leader: Mgr. Eva Markvartová, Ph.D. Degree of professional classification: bachelor; Place of defense: Faculty of Education, 2020. 46 p. The bachelor thesis focuses on the topic of dementia occurring in German-written literature. Specifically, two books are described and compared - House of Turtles by Annette Pehnt and The Old King in the Exile by Arno Geiger These mutually different works have their main theme in common - senility and dementia. In the books changes not only the attitudes of sick people towards life and their loved ones, but also the course and consequences of the disease of individual protagonists and the environment. The authors present their experiences with dementia and Alzheimer's disease, personal or otherwise acquired knowledge, and their heroes bring readers closer to the joys and sorrows of their daily lives. The first chapter deals with the problems of senility and related dementia. It contains information on how the disease arises, progresses and how its manifestations can be alleviated. The second part is devoted to the motif of old age in literature in general, as well as in the...
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".