The Identity of the Main Character in Life of Pi novel by Yann Martel (Psychology of Literature)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The objective of this research was to understand comprehensively the identity of the main character in the novel of by Yann Martel. It was a qualitative research with content analysis conducted in Jakarta, from June to August 2013. The data were collected through comprehensive reading to the novel, some relevant books, and articles review in internet. Then, it was analyzed through the psycho-analysis theory. Since this is a qualitative research and the researcher himself is the instrument, most of activities were conducted by the study of literature. It was done by tracing relevant data in novels which showed the developmental phases of the main character from childhood to his teenage in order to know his personality, conflicts, the factors which affect the search for identity, and the efforts made by the main character in his search of identity. Results of this research showed that the main character in the novel Life of Pi by Yann Martel is extrovert, intelligent, earnest and energetic. He is a devout adherent of three religions: Hinduism, Christianity, and Islam. He is also a lecturer at the University of Toronto, and an animal lover.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it