Bibliographic record
Abstract
In the age of globalization, scholars in every country face the issue of dualism; how they acquire new knowledge while maintaining their own cultural identities. The multicultural and multi-racial context in Canada offers us great opportunities to observe this phenomenon. At a personal level, wakon-yosai 和魂洋才 also has been an increasingly important and unavoidable issue that begs investigation as to what constitutes my wakon 和魂 after so many years of yosai 洋才 experience both in Japan and overseas. Yukio Mishima’s 三島 由紀夫 suicide in 1970 was a real shocker in Japanese intellectuals’ wakonyosai tradition. He tried to resurrect bushido 武士道, however anachronistic his action was considered to be by many people. Bushido and its Japanese national epic Chushingura 忠臣蔵 still seem to touch a chord in many Japanese hearts. Several variations of wakon-yosai have been coined. Some scholars claim, for example, that after 1945, Japan adopted wakon-beisai 和魂米才 “Japanese spirit, American learning”, and now it is mukon-musai 無魂無才 “no spirit, no learning”. Wakon-wasai 和魂和才 “Japanese spirit, Japanese learning” and wakon-mansai 和魂満才 “Japanese spirit, all learning” are discussed in a global context.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".