Pontos e contrapontos das aulas de orçamento corporativo no ensino remoto emergencial: um olhar reflexivo
Bibliographic record
Abstract
No cenário de educação distanciada que desenrolou com a pandemia da Covid-19 e que de forma abrupta os professores tiveram que se adaptar as emergências escolares, uma pergunta inevitavelmente se impôs: Quais as variáveis intervenientes nos efeitos positivos e negativos no formato do modelo remoto emergencial de Orçamento Corporativo? Dada especificidade e singularidade do objeto de pesquisa trata-se de um estudo de caso único com forte natureza qualitativa. Do ponto de vista metodológico se adotou a observação participante em que o próprio pesquisador é parte do contexto e análise de conteúdo decorrente dos artefatos documentais gerados: o blog de campo e as vídeoaulas gravadas. Os procedimentos analíticos foram baseados nos contrastes teóricos e esquemas. Para validar recorreu-se aos pesquisadores de Educação. A janela temporal contemplou 11 semanas entre junho e agosto de 2020. Pode-se evidenciar as seguintes variáveis indutoras de efeitos positivos: a) ações reflexivas, b) curiosidade instantânea, c) autoavaliação, e d) interação com os pares. Já as negativas salientaram: a) a distância; b) autonomia e c) ressignificação.
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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 | 0.025 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".