Bibliographic record
Abstract
Ethnic minorities varies according to the sojourn and acculturation period, and there are between different ethnic minority’s variant degrees of access to the majority’s culture. The concept of ethnic minority includes as well as the new incoming immigrant groups as the old people groups living for hundred years on the territory like the native American Indians or the Australian aboriginals (they are in fact the original native country habitants). The population in western industrialized countries became multi-ethnic, due to the work market industrialization and to the subsequent frontiers opening. Contrary to the folk’s beliefs, the migration increase is not a new phenomenon; it had had different forms during centuries – from the growing need of work force in countries like England or France, to the colonization of the USA, Canada and Australia. It did exist also a refugee migration, running from hostilities and seeking politic asylum in countries like Sweden or USA. In the countries where they are received, the immigrants are located in the poorest city wards and they usually have a lower social status. They have a lower living standard reflected into the less fortunate accommodation and health conditions. The WHO (World Health Organization)’s objective, “Health for all by 2000”, suggests that it should be taken care so that ethnic minorities could have equal access to healthcare services,
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 | 0.005 | 0.008 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".