Bibliographic record
Abstract
RESUMO Examina, a partir de Sobrados e mucambos, de Gilberto Freyre, o fenômeno da mestiçagem brasileira, ressaltando que, no Brasil, nunca houve acentuado preconceito de cor, mas, sim, de classe social. Em abono de suas reflexões, recorre igualmente a autores como Joaquim Nabuco, Darcy Ribeiro e José Antônio Gonsalves de Mello. ABSTRACT The Mongrel Landscape in The mansions and the shanties. v. 28, n. 1, p. 63-72, jan./jun. 2000. Analyses the phenomenon of miscigenation in Brazilian society as it appears in Gilberto Freyre’s Sobrados e mucambos (The mansions and the shanties). Points out that never was a strong color prejudice, but, instead, class prejudice in Brazilian society. Appeals to Joaquim Nabuco, Darcy Ribeiro, and José Antonio Gonçalves de Mello´s arguments to reinforce that idea. RÉSUMÉ Le paysage métis dans “Sobrados e mucambos”. v. 28, n. 1, p. 63-72, jan./jun. 2000. Il examine à partir de “Sobrados e mucambos” le phénomème du métissage brésilien, en insistant sur le fait qu’il n’y eut jamais au Brésil de préjugé très fort de couleur mais plutôt de classe sociale. Pour appuyer ses réflexions, il recourt également à des auteurs comme Joaquim Nabuco, Darcy Ribeiro et José Antônio Gonsalves de Mello.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".