Bibliographic record
Abstract
Latin American migration to the USA and Canadian labor markets has been historically determined by economic factors as the USA pays higher salaries compared to Latin American countries. However, since 2007, increases in violence, organized crime, insecurity, political intolerance and environmental disasters in Latin America, Africa and Asia have increased the number of forced displacements of large population groups of migrants from the Global South who have migrated to Latin America looking to cross the US border. The strengthening of the border controls has limited their aspirations and countries like Brazil and Mexico are now countries of transit and also of residence for migrants. The article adopts a methodology of integrative review of migration, colonization, slavery, eugenics and racism in Latin America to analyze how the history of colonization, racism and eugenics in the region is reproduced against large population groups of Black immigrants from Haiti and Africa, who are compelled to escape a second time due to the xenophobia and racism historically reproduced in these societies. Results indicate that eugenics, racism, and xenophobia have intersected in Latin America since the formation of national states, with the acceptance of the population miscegenation and homogenization, through population engineering projects of “The Cosmic Race” in Mexico and “Racial democracy” in Brazil, which are reproduced until current days with explicit xenophobia and racism against Black migrants and refugees.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".