O Ritmo de Queda na Desigualdade no Brasil é Adequado? Evidências do Contexto Histórico e Internacional
Bibliographic record
Abstract
The following study uses two approaches to judge whether inequality in Brazil is falling fast enough. The first is to compare the variation of the Gini coefficient in Brazil with what was observed in several countries that today belong to the Organisation for Economic Co-operation and Development (OECD) - France, Netherlands, Norway, Spain, Sweden, United Kingdom, and United States - while they built their social welfare systems during the last century. The second approach is to calculate for how long Brazil must keep up the fall in the Gini coefficient to attain the same levels of inequality of three OECD countries that can be used as a reference: Canada, Mexico, and the United States. The data indicate that the Gini coefficient in Brazil is falling 0.7 point per year and that this is superior to the rhythm of all the OECD countries analyzed while they built their welfare systems but Spain, whose Gini fell 0.9 point per year during the 1950s. The time needed to attain various benchmarks in inequality are: six years to Mexico, twelve to the United States and 24 to Canadian inequality levels. The general conclusion is that the speed with which inequality is falling is adequate, but the challenge will be to keep inequality falling at the same rate for another two or three decades.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.042 |
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; both teacher heads agree on what is shown here.
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".