Anclas para sueños silvestres. Una conversación con Eduardo Kohn
Bibliographic record
Abstract
Following the Spanish publication of the book How Forests Think. Toward an Anthropology Beyond the Human, Eduardo Kohn (Associate Professor of Anthropology at McGill University in Montreal, Canada, and Affiliated Researcher at FLACSO in Ecuador) reflects on the origins and the trajectory of his research in the Ecuadorian Amazon. The conversation dwells on questions of theory and method, on key concepts of this influential work (such as absence, hierarchy, and "emergence"), and, finally, on the new paths that have appeared since the initial publication of this book in 2013. The narrative that takes place in the interview will be helpful for those approaching How Forests Think for the first or umpteenth time, leading us to appreciate the many kinds of stories unfolding between the lines of this fascinating work. A propósito de la publicación en español del libro Cómo piensan los bosques. Hacia una antropología más allá de lo humano (2021), Eduardo Kohn (profesor de antropología de la Universidad de McGill en Montreal, Canadá, e investigador afiliado en la FLACSO de Ecuador) reflexiona sobre los antecedentes y la trayectoria de su investigación en la Amazonía ecuatoriana. La conversación se detiene en cuestiones de teoría y método, en conceptos claves de este influyente trabajo (como la ausencia, la jerarquía y la emergencia) y, finalmente, en los nuevos caminos que han surgido a partir de la publicación inicial de este libro en 2013. Se trata de un recorrido conversado que servirá de apoyo para quienes se aproximen a Cómo piensan los bosques por primera o enésima vez, y que nos lleva a apreciar los muchos tipos de historias que se desenvuelven entre las líneas de esta fascinante obra.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".