Educação para o futuro: uma abordagem sobre novas possibilidades de carreiras / Education for the future: an approach to new career possibilities
Bibliographic record
Abstract
O presente artigo pretende dialogar sobre evolução do trabalho e novas possibilidades de carreiras, que surgem com o advento da tecnologia tanto pela evolução de determinadas funções quanto pelo redesenho de atividades que acabam se tornando mais multidisciplinares, como no reflexo na formação requerida para a realização de novos tipos de trabalho profissional. Neste contexto, a formação oferecida pelas universidades e faculdades são endossadas pela aprendizagem nas organizações, seja como programa de desenvolvimento interno ou até como programa aberto de troca de conhecimento. Neste cenário de olhar para o futuro, pretende se trazer para a discussão em que sentido a educação e o surgimento de novas possibilidades de carreira andam conjuntas.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.010 | 0.021 |
| Scholarly communication | 0.019 | 0.018 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".