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Record W1883310234

MEDICIÓN DE LA POBREZA EN EL S.I.P.O. : DESARROLLO DEL MÉTODO DE PUNTAJE

2001· article· es· W1883310234 on OpenAlexaff
José Rafael Elizondo Agüero, Jorge Poltronieri Vargas, William Villalobos Alfaro

Bibliographic record

VenueAmericanae (AECID Library) · 2001
Typearticle
Languagees
FieldSocial Sciences
TopicRegional Development and Innovation
Canadian institutionsActua
Fundersnot available
KeywordsHumanitiesMedicinePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

El Sistema de Información de la Población Objetivo, que funciona en el Instituto Mixto de Ayuda Social de Costa Rica, cuenta con tres métodos de calificación de la condición socioeconómica de las familias que están registradas en este sistema. Estos métodos son: Línea de Pobreza (LP), Medición Integrada de Pobreza (MIP) y Método de Puntaje. El método LP se basa en el ingreso económico del grupo familiar; el método MIP considera además del ingreso, otras cuatro variables relacionadas con las necesidades básicas de las familias. Por su parte, el Puntaje se basa en 16 variables ponderadas, cuya combinación ofrece un indicador resumen por familia, expresando de forma cuantitativa el grado de pobreza de la misma.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.300
Teacher spread0.291 · 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 teacher head, not a consensus.

Study designObservational
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

Citations1
Published2001
Admission routes1
Has abstractyes

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