Bibliographic record
Abstract
Water is life. For millennia, the Rio Grande/Rio Bravo has nourished many Indigenous peoples along its 1,255 mile length, from it's source in the San Juan Mountains to the Gulf of Mexico. The river is the lifeline, read as a map between the interrelated communities. Colonization turned the Rio Grande/Rio Bravo into an international border between the United States and Mexico, and in the last 40 years, our river/border has become heavily militarized. This project engages a practice of Indigenizing/decolonizing the Rio Grande/Rio Bravo as ancestral waters to various local Indigenous peoples, drawing from the collective memory of intergenerational indigenous fronterizxs (border residents) to examine the relationships between people of the Laredo/Nuevo Laredo community and the Rio Grande/Rio Bravo. To do this, I theorized a new theoretical framework called an Indigenous Fronterizx Cosmography, which braids Indigenous epistemologies, Xincanx ontologies, and borderland positionalities. This way, first-hand accounts are understood as intellectual traditions that revitalize, restore, and restory the holistic ancestral knowledges of the land and river. Next, I created a culturally-centric research methodology, named Fronterawork, drawing from Indigenous methodologies, oral history/testimonio sharing, and witnessing to document the lived experiences of 25 community elders and knowledge-keepers in/of/with/near/over/across the river's waters. Participants shared their knowledge of the Rio Grande/Rio Bravo, as well as their perspectives of how the river has changed over their lifetimes. Their testimonios were examined holistically, and in-context as embodied and emplaced situated knowledges of the river. When considered in conversation with each other, themes and subthemes emerged, suggesting two major approaches to understanding: river-as-water (Water Thinking) and river-as-border (Border Thinking). In response, I created a Pedagogy of Water that builds on the collective memory of community elders in order to teach the next generations about our river. This pedagogy interrupts dominant forms of displacement and violence against the diverse Indigenous peoples of the river/border communities, while revitalizing the ancestral relationships between the Indigenous peoples and the Rio Grande/Rio Bravo. Our collective memory serves as foundation from which to revitalize and honor the Rio Grande/Rio Bravo as part of the sacred landscape of what is today called south Texas.
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 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".