Bibliographic record
Abstract
Multiculturalism started as a national policy of Canada. It spread later to other countries, but almost no country in the world has adopted it as a national policy. In Japan, it was transmitted in 1990's, but it has been taken for a campaign motto rather than a real policy. Few know what it is. As for the Koreans, their government has taken it seriously since the moment that more than 10 percent of the population are foreigners, but just like the Japanese, they do not believe in multiculturalism. The myth of one single ethnic nation is as strong in Korea as in Japan. The myth may be useful for maintaining the national unity, but it tends to lead people to exclusivism toward other peoples residing in their homeland. From a multicultural point of view, the influence of such a myth should be attenuated. The Japanese should recognize the Archipelago has at least three different cultures: Ainu culture in Hokkaido, Yamato culture all over the Archipelago and South-Western Islanders' one. The same can be said about the Koreans. They should recognize they have at least three different cultures coming from the ancient kingdoms of Kogryo, Baekje and Shilla. The merit of being aware of the multicultural aspect of one's country is enormous. It will allow one to see his or her country is not an isolated entity but a dot on the worldwide and transnational cultural network.
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 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".