Applying critical race theory to multicultural children's books : race and racism in Korean-Canadian children's books
Bibliographic record
Abstract
The metaphor of Canadian society as a “mosaic” had been used to describe Canada’s diverse society, even before Canada’s adoption of the Multicultural Act in 1988, with the government policy “to recognize all Canadians as full and equal partners in Canadian society.” The government’s aims suggest comfortable integration, but racism is a part of Canada’s history and remains a problem, though this has been overlooked since Canadians have clung to the vision of Canada as a tolerant society. Canadian children’s books reflect some of the racial oppression that certain cultures endured but they do not overall serve well in representing distinct cultural groups in Canada and their diverse racial experiences. The year 2002 was a milestone for Korean-Canadian children’s literature with Janie Jaehyun Park’s The Tiger and the Dried Persimmon earning a place as a finalist for the prestigious Canadian Governor General’s Literary Award for Illustration and winning the Elizabeth Mrazik-Cleaver Picture Book Award. Canada has not seen an abundance in the publication of Korean-Canadian children’s books as America has seen with Korean American children’s books, but there have been a handful of books that involve Korean Canadian characters and culture, most of which have not been written by Korean-Canadian authors. This observation led to my research questions: “Are there any observable biases in the books that have been published about Koreans and Korean Canadians?” Also, “How does the racial identity of the authors or illustrators shape their views when writing books for children?” I discovered that the sample size of Korean-Canadian books is very small (only 10 published thus far), as I undertook research to qualitatively determine racial biases through the application of key principles from Critical Race Theory. In looking at Korean-Canadian children’s books and their background, I outlined not only the history of Korean immigration and social history in Canada, but China’s history of racism in Canada, which acted as a precursor toracial sentiments that contributed to stereotyping of Asians to this day. And, since a common mistake among people is the grouping of all Asians as Chinese, I determined to show that Korean culture has not been treated as distinct. Investigation of the Korean-Canadian books published so far shows that a very limited range of experiences is represented for child readers, and that crucially missing are the voices from the Korean-Canadian community to tell their stories for children.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.027 | 0.029 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".