La ciudad astuta, potencias de la metis y la mentira
Bibliographic record
Abstract
Se estudia la ciudad como el cumulo de juegos y disputas entre las intenciones reguladoras del espacio y las respuestas de los usuarios; la ciudad topológica y tropológica en interminable interacción. La Metis, astucia, siempre en resolución del duelo entre las tácticas y las estrategias como manifestaciones urbanas. No se trata de estudiar la ciudad desde una dualidad, se intenta analizar los comportamientos de distintas fuerzas, ordenadoras y evasivas, -astucias ambas-en la configuración del espacio urbano y las distintas apropiaciones que se hacen de él. Medellín ejemplifica la ciudad ideal para el estudio de las potencias de la metis y la mentira, dadas las condiciones de intención ordenadora y las fugas que se proponen a estos controles. Se presentan distintos ejemplos de la presencia de la astucia urbana: retóricos, dramáticos, expuestos, ocultos, en movimiento y mutación; que terminan por sugerir un aspecto recurrente de apropiaciones astutas en las ciudades latinoamericanas./Abstract. City is studied as a bunch of games and disputes between arreging intentions of the space and the users answers. Metis, astuteness, always resolves the duel between tactics and strategies as urban manifestations. This is not about to study the city from a duality. This is an attempt to analyze the configurations and appropriations of the urban space from the behavior of different forces, like controllers and evasives, -both astuteness. Medellín is an ideal example to study the metis and lie potencies, because in one hand, there is a control intention and in the other, there is a trick to scape. Different examples appear in this text, all them about the urban astuteness. And they suggest a recurrent aspect that is present in almost all Latin American cities
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".