Geografías Latinxs
Bibliographic record
Abstract
Debido al creciente interés por las geografías latinxs, existe una necesidad de una exploración más profunda de cómo los geógrafos latinxs abordan la investigación en sus propias palabras. En este artículo, iniciamos un diálogo sobre geografías latinxs anclado en nuestras múltiples, diferentes y corpóreas experiencias como geógrafos latinxs que se han reunido en los últimos cuantos años para platicar, crear espacios y construir relaciones de cuidado y responsabilidad entre sí. Reflexionamos sobre cómo cada uno de nosotros llegamos a la subdisciplina de las geografías latinxs, que significan para nosotros, como hacemos geografías latinxs y que nos espera en el horizonte. Rechazamos definiciones singulares o impuestas e imaginamos colectivamente una geografía latinx expansiva, matizada y relacional que examine críticamente la diferencia, la conquista, el poder y la liberación a través de Turtle Island y Abya Yala.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".