Poverty Rates in Venezuela: Getting the Numbers Right
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".