Bibliographic record
Abstract
This paper is about ethnic minority education and builds on theories, principles and practices of multicultural education – a term we apply to summarize some of the more essential contributions in the field. First, we introduce to the background of multicultural education and the implications such term has for the understanding of the relation between the ‘majority’ and ‘minority’ groups. Second, key-concepts that surround and relate to multicultural education are defined, culture, ethnic minority, religion, language, diversity, integration, assimilation, inclusion- exclusion. Third, we identify the aims and objectives of multicultural education while the fourth section in as introduction to six essential dimensions of multicultural education. The fifth section includes examples of multicultural education and/or bilingual education from different countries in different parts of the world; Canada, New Zealand South Africa, , Nepal and Denmark. Canada represents a country that has been seen as a leader in a proactive approach to developing multicultural and multilingual education for ethnic minority groups. Like Canada, New Zealand has practiced immersion education supporting amongst other the Maori ethnic group in education and in maintaining and preserving languages at risk for disappearing. South Africa is interesting, since language particularly after Apartheid has become an educational as well a political challenge – education is a question of literacy and reconciliation. The Nepalese example - a typical 3rd world country with a highly linguistically and ethnically diverse population - provides lessons learned from bilingual education programmes that reach out for children from different ethnic groups. Finally Denmark is an example of a European welfare-state challenged by processes of globalization – and migration to a country which according to the self-perception of the majority of the population through out the history has been culturally and ethnically homogenous. We add examples of immersion education from Danish minority education in Germany.
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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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.038 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".