WHO PLAYS THE HUNGER GAMES: ARTEMIS OR PERSEPHONE? THE MYTH OF PERSEPHONE IN SUZANNE COLLINS’S TRILOGY THE HUNGER GAMES
Bibliographic record
Abstract
This study focuses on Persephone myth as reflected in the popular trilogy Hunger Games by Suzanne Collins. The novelist uses the frame of this myth, with its implicit motifs of descent to the underworld and abuse, in order to reveal the anxieties of an adolescent girl, Katniss Everdeen, in her search for an authentic identity. The aim of this study is to show that Suzanne Collins also makes use of Artemis myth in her trilogy, but her eventual insistence on Persephone myth in her narrative reveals that the novelist’s purpose goes beyond the depiction of private experience of coming of age inherent in this myth, extending its function to issues related to the discovery of a social identity. The most important reason for using the mythemes of the popular myth of Persephone in her work is to represent the anxieties about societal collapse, expressed by the novelist through the images of panem et circens, hunger and predatory behaviour of eating and being eaten, which is characteristic to contemporary world. The mechanism of the cyclical death and rebirth, integral to the myth, contributes to the creation and validation of some social customs and beliefs. Therefore, Katniss Everdeen’s journey and her traumatic experience could be read as an attempt to transmit the fears of anarchic existence, the anxieties concerning politics of authority and power, but, at the same time, the hope in the emergence of a new social identity which would be built on some newly acquired and acknowledged values, such as hunger for justice, compassion and nourishment.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.032 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".