Mulan's Great Upward Drive Toward Androcentrism in Mulan in Disney Beloved Tales by Jane Brierly, Robyn Bryant and Stephanie Werner
Bibliographic record
Abstract
This paper seeks to outline the representation of woman character specifically in using her drive in responding to androcentrism in Mulan in Disney Beloved Tales. It is one of short stories written by Jane Brierly, Robyn Bryant and Stephanie Werner and published in 2001 in Canada. The androcentrism undergone by woman main character will be discussed. The great upward drive will be discussed and related to the woman main character's response to androcentrisms. This will be placed in the context of woman representation in literary works. The approaches used in this discussion are feminist and psychological approach. Feminist approach is used to know the woman character's position in the story and how she is represented. Psychological approach is used to know the psychological state and the response of the main character toward the androcentrisms in the story . The method of the study used in this thesis is deductive method from the general discussion to the specific discussion. The data are collected through library and cyber research. The result of the research shows that Mulan, the main woman character experiences three kinds of androcentrisms namely woman for reproduction, ethical concept and warfare. She uses her great upward drive in responding the three androcentrisms. The representation of Mulan is made very positively that gives good values about woman character in the literary work. Keywords: great upward drive, tales, Mulan, feminist critique, androcentrism, patriarchy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".