PROBLEM SEMANTIS DAN SOLUSI PEMAHAMAN MULTIKULTURALISME, INTERKULTURALISME, DAN CROSS-CULTURAL
Bibliographic record
Abstract
A semantic problem arises around the terms Multiculturalism, Interculturalism, and Cross-Cultural. The first two terms are involved in intensive discussion, while the last term tends to be in the realm of praxis. Semantic problems begin with Multiculturalism as a term that has many meanings. This problem received a response in the form of multiculturalism as an approach to the clarity of its features. In the development of perspectives, a multiculturalism problem occurs when dealing with the term Interculturalism as a comparative approach. There are two perspective arguments; arguments that support Multiculturalism and responsive arguments. Discussion of the problem increases when “interculturalism†is used to show a specific model of “managing cultural diversity†in Quebec which is articulated in explicit opposition to Canadian multiculturalism, but differs from important respect from the European interculturalism model. The two approaches contain indications of strategic advantages in the shift to the term “interculturalism†because the term “multiculturalism†is seen as being politically tarnished over the past decade. At the height of the discussion there was criticism of the flow of Multiculturalism studies which almost completely ignored the contributions of primary disciplines, especially anthropology and social psychology, especially contact theory. Finally, three points of understanding solutions can be proposed; (1) Multiculturalism is a holistic concept and an ideological basis of recognition of cultural differences, (2) Interculturalism is a model of managing cultural differences according to different regional cultural bases, (3) Cross-cultural interaction patterns, action programs, skills, and conflict management instruments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".