Afro-Latinx, Hispanic, and Latinx Identity: Understanding the Americas
Bibliographic record
Abstract
Abstract This article argues that (C) the term “Afro-Latinx” is more apt than “Hispanic” or “Latinx” in a significant number of cases. Three premises support this conclusion. The first premise (P1) is that use of “Afro-Latinx” provides subjects with understanding of how certain events depend on anti-Black racism, US society’s racially unjust structure, and US colonial policy. The second premise (P2) is that neither the term “Hispanic” nor the term “Latinx” provides subjects with this understanding of how certain events depend on anti-Black racism, US society’s racially unjust structure, and US colonial policy. The third premise (P3) is that the term “Afro-Latinx” provides subjects with more understanding of these events than the terms “Hispanic” and “Latinx.” To motivate the argument, the article presents the case of Jose “Kiko” García’s murder by the New York City police and the uprising that ensued.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| 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".