Abiayalan Pluriverses : Bridging Indigenous Studies and Hispanic Studies
Bibliographic record
Abstract
<div><i>Abiayalan Pluriverses: Bridging Indigenous Studies and Hispanic Studies</i> looks for pathways that better connect two often siloed disciplines. This edited collection brings together different disciplinary experiences and perspectives to this objective, weaving together researchers, artists, instructors, and authors who have found ways of bridging Indigenous and Hispanic studies through trans-Indigenous reading methods, intercultural dialogues, and reflections on translation and epistemology. Each chapter brings rich context that bears on some aspect of the Indigenous Americas and its crossroads with Hispanic studies, from Canada to Chile. Such a hemispheric and interdisciplinary approach offers innovative and significant means of challenging the coloniality of Hispanic studies.</div>
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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; 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".