Bibliographic record
Abstract
Localization is spurring unprecedented, dynamic interaction among globalization and local economies and cultures. The future requires a new vision to mediate the issues of cultural barriers and differences among the world`s peoples. Canada, created by immigrants, with no absolute majority in its society from the beginning, had to overcome differences and achieve social integration through the political brokerage of varied demographic interests. Through this historical process, Canada became the world`s first nation to declare multiculturalism its policy in 1971. While not constitutionally specifying the separation of religion and state in contrast to the USA, Canada has supported minority religious rights. Indeed, the separation of religion and state in Canada is, in practice, stricter than in the USA. While Korean discussions of multiculturalism remain at the level of very basic minority rights, multiculturalism, broadly speaking, is a concept which aims to integrate society through the equal participation of all citizens and removal of social barriers. Canada`s support for minority religions, as well as minorities within religions, expresses this philosophy. This article analyzes the relationship between religions and multiculturalism, and how the phrase, Diversity is our strength, embraces not only new ethnicities but also the older, more established ones in Canadian society.
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 | 0.008 | 0.007 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".