Genre, history, fiction: vocabularies of resistance in The Hunger Games trilogy
Bibliographic record
Abstract
This thesis examines Suzanne Collins‘ use of “arena fiction” conventions and historical social reform movements in The Hunger Games trilogy (THG) to encourage reflection on the means of subverting the intended effects of spectacle, but also to consider the cost of consuming or using children in social reform. My thesis argues that THG is an arena story which explores the mechanics of social reform through powerful visuals while also exploring the personal cost, especially on children, of becoming a visual symbol of resistance. I show how THG is rooted in historical social reforms and why these are so useful for Collins to generate visual resistance literacy in her readers and push her use of arena fiction deeper into exploring child bodies. Finally, through a close reading of the subversions in THG, I argue that Collins uses both arena fiction and history to further reflection on children‘s participation in reform movements.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.027 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".