A comparison of female representations in award- winning children's literature from China and North America, from the 2000s to present
Bibliographic record
Abstract
Children's literature can be been seen as evidence to reflect cultural gender expectations.This study started with examining gender-based research approaches in children's literature in North American and Chinese scholarship, demonstrating the need for a cross-cultural comparison in female representation in children's books.The goal of this comparative research has been to identify and compare female representations in children's literature using Chinese and North American sources.Fifty-four award-winning picture books were analyzed whereby four aspects pertaining to female characters were examined: the amount of times female characters was presented as main characters; their physical appearances; occupations and family roles; and activities and behavioral characteristics.Using content analysis, this study found that the female characterization in the books illustrated some different gender expectations between Chinese and North American cultures.However, overall, Chinese and North American children's literature often demonstrated similarities when depicting female characters.Particularly, female characters from these two cultures were seen conforming to traditional gender stereotyping and challenging the stereotyping at the same time.This co-existence of traditional gender stereotypes and nontraditional characterizations in female characters reflect the complex gender expectation for women in both Chinese and North American society nowadays.The outcomes of this research
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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 | 0.013 | 0.010 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".