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Record W7015888576

Tramas socio-territoriales tras la política vial: Aportes desde una mirada microanalítica (mediados del siglo XX)

2024· article· es· W7015888576 on OpenAlexaboutno aff

Bibliographic record

VenueConicet · 2024
Typearticle
Languagees
FieldSocial Sciences
TopicArgentine historical studies
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)HypocrisyProduction system (computer science)
DOInot available

Abstract

fetched live from OpenAlex

El trabajo se propone trascender el análisis de la política vial desde una visión estatalista y triunfalista hacia otra que coloque el foco en las disputas de las poblaciones situadas en los territorios donde se ejecuta la intervención. ¿Qué lugar ocupaban y cómo se pronunciaban las iniciativas de quienes no formaban parte del Estado? ¿Qué intereses y expectativas estaban comprometidos en las complejas y variadas formas de diseño, uso y pavimento de caminos en el medio rural? ¿Qué consensos, conflictos e impactos territoriales generaron los trazados? Para responder estos interrogantes se abordará un estudio de caso: el debate sobre el emplazamiento y la subsiguiente pavimentación del camino Brandsen-Ranchos (provincia de Buenos Aires), a mediados del siglo XX. La potencialidad del enfoque microanalítico reside en la posibilidad de complejizar y profundizar las interpretaciones historiográficas hegemónicas sobre la temática vial. En este sentido, la reconstrucción de las tramas socio-territoriales particulares –a partir de la triangulación de fuentes documentales (prensa local, informes técnicos, actas y planes gubernamentales, mapas)– demostrará que la obra vial expresa y forja una relación de fuerzas desigual en el medio rural, debido a la incidencia de la accesibilidad en la actividad productiva y la vida cotidiana.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.010
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.022
GPT teacher head0.336
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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