O crescimento econômico e o direcionamento pró-pobres: uma análise das curvas de incidência de crescimento para os estados do Nordeste do Brasil no período de 1995 a 2005
Bibliographic record
Abstract
After the implantation of the Real plan, Brazil has looked for to define politics being aimed at to effectively reduce the indices of poverty and inequality. In this work are traced the Growth Incidence Curves, defined for Ravallion and Chen (2003), for all the states of the Northeast region. The objective is to verify if the aiming of the economic growth occurrence in the region, after Real plan, has been for the percentiles monetarily less favored of this population. For in such a way, they are used given on per capita familiar income of the National Research for Samples of Domiciles - PNAD considering itself the years of 1995 the 2005. From the analysis of the behavior of the curves, it was verified that, in a general way, the states of Northeast had presented a common trend of performance, characterized for a economic growth effectively directed to poor.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".