Character Development of Peter in J.M Barrie "Peter and Wendy" Novel
Bibliographic record
Abstract
Character development is the transformation process of the character from bad character to good character or the opposite that influenced by intrinsic elements. That is why the researchersused the guide from intrinsic elements and used the structuralism theory from Seymor Chatman. In this research, the researchers focused on the development of Peter, the main character. The researchers also used characterization theory from Rimmon Kenan to characterized Peter. This research used qualitative content analysis as the research design. The result of the research showed that even though many says that Peter is a flat character that impossible to change, the researcher found that the influence of Wendy towards Peter, she changed him into a better version of himself, appreciated the lost boys, and even though his thought about parents was not good, he still let the lost boys to leave and have their own parents. The researchersalso found influence of intrinsic elements on Peter’s character development. First, plot showed his condition from the beginning until the ending events. Second, setting showed his background in Neverland, the place where he lived.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".