“Peter Pan Syndrome” or Psychological Therapy: Fairy Tales and Self-Maturity in Joy Kogawa’s Obasan
Bibliographic record
Abstract
Fairy tale as a special literary genre is gaining much attention in recent decades. Apart from serving as a popular material for postmodern rewriting, it also can be interpreted from the perspective of children’s psychological development. In Joy Kogawa’s novel Obasan, Naomi, a silence Japanese Canadian girl exiled during WWII, is constantly intoxicated in fairy tales and folklores like Momotaro, Peter Rabbit, Snow White, Goldilocks, and Three bear and other stories. By re-narrating the relentless world as a little fairy tale-teller, she once attempted to evade in the imagery bubble when encountering sexual molestation, vicious racial discrimination, identity conundrum and traumatic experiences of evacuation from coastal Vancouver to ghost town Slocan and Baker farm Graton during the WWII. Nevertheless, in each story Naomi absorbs the nutrition from imagination as an alternate facet of reality and experiences self-maturity. Therefore, whether the fairy tale serves as an unrealistic utopia for the escapist “Peter Panner”, or a dose of therapeutic potion to sooth her anxieties and despair rooted in the historical hardships is open to investigating.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".