A COLETA SELETIVA EM UM PROJETO DE PESQUISA PARTICIPATIVA
Bibliographic record
Abstract
A organizacao de sistemas municipais de coleta seletiva, com a inclusao de catadores(as) tem se ampliado, nas ultimas decadas. Na Regiao Metropolitana de Sao Paulo, BR, a coleta seletiva tem apoiadores, mas ha muito a realizar com as equipes tecnicas de governo e, imprescindivelmente para a gestao participativa, com os catadores(as), seu fortalecimento, qualificacao e “empoderamento”. O objetivo desta pesquisa participativa, desenvolvida no interior do Projeto Gestao Participativa de Residuos Solidos (PGPRS- convenio inter universidades - Brasil. Canada) preve acoes educativas, a sistematizacao e analise dessas acoes, com o pressuposto basico do cooperativismo, visando ampliar a autonomia, a identidade etica, saude, auto estima e a busca de solucoes concretas para a comercializacao em rede dos residuos e a inclusao dos catadores(as) nas politicas publicas. A pesquisa enfrenta desafios, pois os envolvidos sao pessoas extremamente sofridas, da camada mais espoliada da pirâmide social, que tem como modelo (valores e relacoes interpessoais) do modo capitalista de producao, onde a hierarquia e a competicao predominam, antagonicamente ao cooperativismo, exigencia fundamental na construcao de outra logica. A preocupacao atual do Projeto e o entendimento da Nova Lei da Coleta Seletiva, aprovada em 2010.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".