Immigrant students in the Chilean school system: Interculturality and inclusion
Bibliographic record
Abstract
According to current estimates, there are 244 million migrants worldwide, corresponding to 3.3% of the world’s population. In the Americas, the number of migrants increased by 36% during the year 2015. The purpose of this bibliographic study was to explore and describe the state of the art of social inclusion of immigrant students in the Chilean school system. The method in this article was a review of scientific evidence updated out in the main databases available MedLine and The Cochranre Library Plus (PubMed, Lilacs, Scielo, EBSCO, Google Scholar), without date restriction, in Spanish, Portuguese and English. There were no restrictions regarding the type of study, without a date limit), 62 articles were selected. The increase of the foreign population in short periods of time exposes the migrant population to difficulties such as living in disorganization, and the need to adapt to the culture and customs of the host society, as well as traumatic events like abuse, discrimination, difficulties in access to health, educational and social services, lack of support networks and social articulation, which can have an impact on the physical and mental health of migrant populations. In Chile, it is still necessary to work to achieve intercultural education; indigenous people are still related to bilingual intercultural education. In conclussion, the diversity is a natural fact, therefore in this context it is suggested to create a vision of a culture of relations between diverse groups. Likewise, topics such as nationalism, identity, institutionalized attitudes of discrimination, xenophobia and racism, that still exist in the national culture, should be addressed.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".