Current Status and Prospect of Canadian Children’s Literature Research in Korea: Archiving Academic Journal Papers (1991-2022)
Bibliographic record
Abstract
Canadian children’s literature has established itself as Canada’s national literature in a relatively short period of about 170 years. While Canada establishing its national identity, national writer and literature represented by Lucy Maud Montgomery’s Anne of Green Gables was born. The process of birth and growth of Canadian children’s literature has been in line with such context of the nation. Understanding the history and current status of Canadian children’s literature requires a macroscopic view of geographical, human, and cultural factors that have shaped the present Canada. Then, what about Canadian children’s literature ‘reserch’ in Korea? What development has Canadian children’s literature research made in Korea? What is the current status? These questions come from the awareness that Canadian children’s literature is still an unfamiliar area in domestic English literature research, and that the research itself is insufficient in quantity and quality. Responding to the questions, this study examines the development and current status of Canadian children’s literature research in Korea, focusing on research papers published in domestic academic journals from 1991 to 2022. Both quantitative analysis of the papers and qualitative analysis of the contents and timely topics covered by the papers will be carried out together. As a conclusion, this study will diagnose the challenges and future prospects left by the current Canadian children’s literature research in Korea.
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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 | 0.021 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.051 | 0.110 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.021 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".