Bibliographic record
Abstract
The aim of this diploma thesis called Three significant trends in young adult literature is to analyse this literary category in the Czech Republic; to describe the publishing houses focusing on this type of literature and to determine, if there are any trends - and if so to describe them. The first chapter states different definitions of so called YA literature and its understanding abroad and in the Czech Republic among the publishers. In the next chapter I characterise the main trends in YA literature that already exist and also those that could emerge, according to literary agents and publishers. In the next part of this thesis I describe three chosen genres: urban fantasy, fairy tale retellings and dystopian novels and I analyse four series determined as typical for respective genres: The Bone Season by Samantha Shannon, The Lunar Chronicles by Marissa Meyer, The Hunger Games by Suzanne Collins and Divergent by Veronica Roth. Each analysis is followed by the description of media response to the chosen series. The thesis also includes the interviews with editors from chosen publishing houses focusing on YA literature: Tereza Pecáková from CooBoo, Jakub Šedivý from Fragment, Lucie Kučová from Egmont and Eva Sedláčková and Jiří Štěpán from Host. This practical part is preceded by a theoretical...
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".