Young Adult Dystopian Literature. Didactic Benefits of its use in the English Subject Classroom in Norway.
Bibliographic record
Abstract
English:\nThis thesis examines didactic benefits of young adult (YA) dystopian literature when used in the English subject classroom in Norway. More specifically, the study investigates how working with this genre can develop young adult students’ critical thinking skills and their understanding of contemporary society, and how this can influence readers’ personal development and self-growth. Moreover, the thesis looks at the students’ development of reading and digital skills when working with YA dystopian literature in general, and Scott Westerfeld’s trilogy, Uglies (2005a), Pretties (2005b) and Specials (2006), in particular.\nThis study is based on literary theory, mainly traditional and YA dystopian literature, and didactic theory, which is presented in a literature review. The second research method is a close reading of Westerfeld’s Uglies trilogy. The findings from both the close reading and the literature review are discussed in relation to the Common Core and English Subject Curricula, as well as the Framework for Basic Skills.\nWorking with YA dystopia can aid young adults to meet the learning outcomes that are set by the Norwegian Directorate for Education and Training. The qualities of this type of literature make it a viable choice for work in the English subject classroom and with young adults. Nevertheless, further research in this field can consist of testing concrete teaching methods and practical classroom applications in the form of empirical research.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".