"There Is a Target On Us": The Impact of Anti-Black Racism on African Migrants at Mexicos Southern Border
Bibliographic record
Abstract
Each year, Africans continue to flee their countries of origin in order to find safety and survival. As immigration to Europe has become more difficult, particularly since the continent began externalizing its immigration policy in 2015, many Africans have been forced to take an alternative route – flying to South America and making the harrowing journey through jungles and rivers to reach Mexico and travel onward to the United States or Canada. This has led to an increase in African migration into Mexico, including from Cameroon, the Democratic Republic of the Congo, Eritrea, Ghana, and Somalia, over the same period.In this Report, the Authors situate interviews with 20 migrants, and African migration to Mexico in general, within a broader discourse of anti-Black racism in the country. The Report begins with an overview of how discrimination on the bases of race and skin color impacts Afro-Mexicans, Black migrants, and other peoples of African descent. Next, the Report describes the recent migration of Africans to and through Mexico, including the causes of migration out of Africa and through Latin America. The Report then highlights how African migration through Mexico has been impeded by the current Mexican Administration's restrictive immigration enforcement. Within this context, the Report outlines the findings from BAJI's interviews and additional interviews that the Authors conducted with a leader of the Assembly as well as service providers, including about the intersectional discrimination faced by African women in Mexico. Finally, the Authors recommend some steps to address the impact of Mexico's anti-Black racism on African migrants, as well as other Black migrants, at the country's southern border.African migrants rarely form part of the narrative of migration through Latin America, or in Mexican society in general. This Report is a partial response to that failure of public discourse and policy analysis, and points to the need to address that void in a systemic way. The current context in Mexico – like the current global anti-Black racism movement – demands and creates an opening for this work.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.015 |
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; both teacher heads agree on what is shown here.
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".