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Record W2058752204 · doi:10.2190/ee0q-6xyf-wwgr-9lrx

Poverty Rates in Venezuela: Getting the Numbers Right

2006· article· en· W2058752204 on OpenAlexaboutno aff
Mark Weisbrot, Luís Eduardo Sandoval, David Rosnick

Bibliographic record

VenueInternational Journal of Health Services · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicIncome, Poverty, and Inequality
Canadian institutionsnot available
FundersCentre for Economic Policy Research
KeywordsPovertyQuarter (Canadian coin)NewspaperPoverty rateGovernment (linguistics)Development economicsPolitical scienceDemographic economicsEconomic growthEconomicsGeographyLaw

Abstract

fetched live from OpenAlex

This article looks at household and individual poverty rates in Venezuela over the past seven years. For more than a year, the statement that poverty in Venezuela has increased under the government of President Hugo Chávez has appeared in scores of major newspapers, on major television and radio programs, and even in publications devoted to foreign policy. There are no data to support such statements, and in fact the available data show a decline in poverty for both individuals and households over the seven-year period: the percentage of people in poverty declined from 50 percent in the first quarter of 1999 to 43.7 percent in 2005. Further, there is no evidence to suggest any change in the methodology for measuring poverty during this period, as has been alleged in a number of reports. The article also examines briefly the impact of significant changes in non-cash benefits such as free health care, which are not taken into account in the measured poverty rate, on poor people in Venezuela. Finally, the authors look at how the mistakes in reporting on Venezuela's poverty rate were made; an appendix gives examples of mistakes in major media and foreign policy publications.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.360
Teacher spread0.343 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2006
Admission routes1
Has abstractyes

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