Cultivating Positive Health, Learning, and Community: The Return of Mesoamerica’s Quetzalcoatl and the Venus Star
Bibliographic record
Abstract
For more than 3500 years, since Olmec times (1500–400 BC), the peoples of Mesoamerica have shared with one another a profound way of living involving a deep understanding of the human body and of land and cosmology. As it stands, healing ways of knowing that depend on medicinal plants, the Earth’s elements, and knowledge of the stars are still intact. The Indigenous Xicana/o/xs who belong to many of the mobile tribes of Mesoamerica share a long genealogical history of cultivating and sustaining their Native American rituals, which was weakened in Mexico and the United States during various periods of colonization. This special edition essay sheds light on the story of Quetzalcoatl and the Venus Star as a familial place of Xicana/o/x belonging and practice. To do so, we rely on the archaeological interpretation of these two entities as one may get to know them through artifacts, monuments, and ethnographic accounts, of which some date to Mesoamerica’s Formative period (1500–400 BC). Throughout this paper, ancestral medicine ways are shown to help cultivate positive health, learning, and community. Such cosmic knowledge is poorly understood, yet it may further culturally relevant education and the treatment of the rampant health disparities in communities of Mesoamerican ancestry living in the United States. The values of and insights into Indigenous Xicana/o/x knowledge and identity conclude this essay.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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 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".