Bibliographic record
Abstract
In this paper, we enrich feminist theorizing on care by tracing more-than-human relationalities that are grounded in place but also stretch across México, the United States, and Canada. In three brief vignettes, we outline how geopolitical conditions of im/mobility intersect with specific material, semiotic, and affective relations of care involving Sonoran Desert soils, berries, toxins, and human bodies. In line with Indigenous theorizing on the myriad ways borders have colonized our political imaginaries, we suggest that more-than-human care is relational, not territorial—not contained by borders. Resumen En este artículo, enriquecemos la teoría feminista sobre el cuidado al rastrear relaciones más-que-humanas que están arraigadas al lugar pero que también se extienden a lo largo de México, los Estados Unidos de América y Canadá. En tres breves viñetas, describimos cómo las condiciones geopolíticas de in/movilidad se entrelazan con diferentes aspectos del cuidado, desde sus relaciones materiales, semióticas y afectivas hasta las más específicas que involucran los suelos del desierto de sonora, frutos rojos, toxinas y humanos en movimiento. En línea con la teoría indígena sobre las formas en que las fronteras han colonizado nuestros imaginarios políticos, sugerimos que el cuidado más-que-humano es relacional, no territorial. No está contenido por fronteras.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.039 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".