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La desigualdad en perspectiva histórica

2022· article· es· W4289654817 on OpenAlex
José Miguel Martínez Carrión

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBoletín del Instituto de Historia Argentina y Americana Dr Emilio Ravignani · 2022
Typearticle
Languagees
FieldSocial Sciences
TopicHistory and Politics in Latin America
Canadian institutionsnot available
FundersPrinceton UniversityTrent UniversityUniversity of OxfordUniversity of ChicagoHarvard UniversityUniversity of CambridgeYale University
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Se destacan las principales contribuciones de Jorge Gelman sobre la desigualdad desde la perspectiva histórica argentina y latinoamericana, una de sus más fecundas líneas investigadoras. Fueron varias las rutas de investigación que abrigó desde hace cuatro décadas, pero en los últimos tiempos destinó una gran parte de su energía a la reflexión e investigación sobre la desigualdad en el ingreso y la riqueza. Los problemas distributivos relacionados con el crecimiento económico y los niveles de vida habían formado parte de sus preocupaciones hacía tiempo, pero fueron en la última década cuando salieron a la luz los hallazgos más consistentes. Con su inestimable equipo de investigadores del Ravignani pudo formular hipótesis originales en torno a nuevos proyectos sobre la desigualdad en el contexto de la historiografía internacional.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0060.004
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.016
GPT teacher head0.305
Teacher spread0.289 · 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