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Record W1927223616

Un modelo mexicano de enseñanza del trabajo de campo

2014· article· es· W1927223616 on OpenAlexaboutno aff
Marisol Pérez Lizaur

Bibliographic record

VenueAmericanae (AECID Library) · 2014
Typearticle
Languagees
FieldAgricultural and Biological Sciences
TopicLatin American rural development
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtCartographyGeography
DOInot available

Abstract

fetched live from OpenAlex

os artículos que conforman la sección "Saberes y razones" de este número de la revista Desacatos fueron presentados como ponencias en la mesa "Fieldwork Training in the Field: The Global Legacies of a Mexican Model" -"La enseñanza del trabajo de campo: los legados globales de un modelo mexicano"-en la Reunión 110 de la American Anthropological Association (aaa) el 19 de noviembre de 2011, en Montreal, Canadá.En 2010, en la Reunión 109 de la aaa en Nueva Orleans, Frances Rothstein me invitó a presentar una ponencia sobre el curso de antropología mexicana que imparto en la Universidad Iberoamericana (uia) en una sesión de la Comisión de Antropologías del Mundo.Se presentaron varias ponencias sobre las formas de enseñar la antropología en distintas partes del mundo, mas la sesión no despertó el interés de los estadounidenses.Esta circunstancia nos motivó a discutir a Frances Rothstein, Gustavo Lins Ribeiro y a mí sobre el escaso interés de los antropólogos estadounidenses en los aportes de las antropologías de otros países.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.065
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0050.005
Scholarly communication0.0080.007
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0290.003

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 head0.006
GPT teacher head0.187
Teacher spread0.181 · 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 designTheoretical or conceptual
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
Published2014
Admission routes1
Has abstractyes

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