ELLAS: Uma plataforma de dados abertos com foco em lideranças femininas em STEM no contexto da América Latina
Bibliographic record
Abstract
Os países da América latina e Caribe sofrem com a sub-representação de mulheres nas áreas de STEM e para resolver esse problema iniciativas, políticas e ações são criadas com frequência por diversos órgãos, sejam eles públicos ou privados. Porém, dados e informações de iniciativas, políticas e ações, não estão abertos, concentrados em algum local e nem sempre estruturados. Para reduzir esse problema e facilitar pesquisas que utilizam dados sobre mulheres em STEM, a rede de pesquisa internacional ELLAS foi criada e executa um projeto. O intuito do projeto é a criação de uma plataforma com tecnologias baseada em Web Semântica para estruturar e concentrar os dados do Brasil, Peru e Bolívia, inicialmente. Assim, esse artigo tem por objetivo apresentar as estratégias adotadas para o desenvolvimento desta plataforma.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".