Bibliographic record
Abstract
Yann Martels bestseller novel Life of Pi tells a story about an Indian boy who drifted with a Bengal tiger for 227 days. Academic studies dealt with this novel for two parts –an event and the interpretation of an event –mainly in the light of literary theory, psychoanalysis, postcolonialism, postmodernism.\nThis study uses Kabbalah as an interpretive tool, which is hidden in the text and tries to find out that religious tradition could be an effective frame for literature.\nPis three names(Piscine-Pissing-Pi) has a distinct connection with Kabbalistic theosophy and the doctrine of creation. It represents the ultimate god as Ein Sof (Pi) and gods attributes(Piscine/Pissing). Piscine can be read as a divine soul in every human being. In this perspective, Richard Parker, who originally has a name thirsty can be animal part in the human soul. So Pi and Richard Parker make a pair of a soul and their castaway story is a spiritual journey that the divine soul transcends over the animal soul.\nThe spatial structure of the story (India, Pondicherry –the Pacific – Canada) also could be read as a metaphor for the spiritual process in Kabbalistic thought. In this reading, the traumatic events that a ship named tsimtsum wrecked and people died can be transformed as a universal condition of humanity. And the change of relationship between Pi and Richard Parker, cannibalistic island and the arrival at the Mexico beach turns into a transformation and a return to the essence of a soul.\nThe relationship between reality and story, storytelling and interpretation, speaker and listener also show similarity in the Kabbalistic view about language, text, story and god. Literature and religion have been effected human in a form of story and both can contain holiness in them. So understanding religious tradition can be an effective tool for an interpretation of literature as the case of Life of Pi.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".