Global Latin(X) AmericanXs: Charting new ontological and epistemological cartographies beyond US LatinX studies
Bibliographic record
Abstract
This article examines how situating our academic inquiry from geographic vantage points outside of the United States allows scholars to recast epistemological and ontological assumptions in the field of US Latina/o Studies. It asks how, from a global reorientation of the cognitive map of US Latina/o Studies, we might reconsider the experience of the Latin American and Caribbean diaspora and the notion of Latinidad in places such as Jordan, Spain, and Canada. This analysis places Latina/o Studies and Latin American and Caribbean Studies into conversation by reconsidering their status as traditionally isolated epistemic sites of US ethnic and area studies. In addition, it explores how new “Latino” and diasporic identities are forged through hybrid ethnic interactions among minoritized populations in the Global South.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.008 | 0.028 |
| Scholarly communication | 0.018 | 0.012 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".