Crossing Over the Genkan: Learning About Japanese Schooling From a Canadian Teacher Perspective
Bibliographic record
Abstract
Abstract The author examines the experiences of learning about Japanese elementary education from the perspective of a Canadian teacher. She suggests through a year-long study in a Japanese third grade classroom that the teaching practices and philosophies underlying curricular and pedagogical decisions made by teachers are shaped by the culture and society of which schools are part, such that learning about Japanese schooling highlights the influence of social, societal, cultural, linguistic factors outside, as well as inside, school. In line with narrative inquiry research practices, the author also acknowledges her own stance as a certified elementary level teacher who was educated and certified in Canada, in contributing to shaping her analysis of teacher knowledge of her teacher participants. She argues that the process of learning about schooling in a country or culture different from the one in which an individual was educated and learned to teach, involves immersing oneself into the research context to learn about the experience from the perspective an insider. Realization of the extent to which this expansive interweaving of school and society is apparent in many aspects of schooling in Japan, in turn, reinforces the idea that this interconnection may also underlie schooling in other societies as well, such that one's experiences in one's own culture may form the foundation for understanding and interpreting knowledge gained about schooling in another culture or community. The notion of cross-cultural teacher knowledge, then, may be grounded in personal and professional experience of teaching and being taught in one's own culture.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.054 | 0.024 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".