Bibliographic record
Abstract
Edward R. Howe, PhD Introduction Multicultural Japan — It’s not merely an oxymoron or a term used only by academics opposing the longstanding myth of racial, ethnic and cultural homogeneity asserted by politicians, the media and nihonjinron literature. In this paper, I illustrate significant changes in Japanese education and society, indicating a gradual shift to transculturalism. However, before describing the emergence of transcultural education in Japan through a reflexive ethnography chronicling two decades of noteworthy experiences, I analyze the broader concept of multiculturalism within the contested cultural context of Japan, juxtaposed with Canada. Since 1990, the Japanese government has cautiously accepted immigration as an official policy, in light of the ageing society and significant labour shortages. Subsequently, kyousei shakai (a symbiotic society in which people live together harmoniously) has become the catchphrase rhetoric to deal with increasing diversity. But kyousei shakai doesn’t adequately describe the current reality. Perhaps it’s more appropriate to use transcultural Japan. I draw on Willis and Murphy-Shigematsu’s (2008) seminal work for clarification: While we will continue to use the words multicultural and multiculturalism as they describe the realities of present-day Japan, we also choose at the same time to use the words transcultural and transculturalism and they describe even more explicitly what is happening, indicating movement across time, space, and other cultural boundaries. When we realize that multiculturalism is not simply the old concept of culture multiplied by the number of ethnic groups, but a new and internally plural “praxis of culture” within oneself and others, in other words transculturalism, then we begin to make progress toward understanding the deeper workings of Japanese and other societies (Banks, 2006, 2004). (p.9) Reflexive ethnographic approaches show great promise to better understanding
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".