Bibliographic record
Abstract
Este artigo reflete sobre a decolonização como resposta ao fenômeno de desumanização manifestado no período de pandemia. O imbróglio que pautou essa análise foi: em que medida a decolonialidade contribui para o enfrentamento da desumanização evidenciada no período da pandemia da Covid-19? O referencial teórico está fundamentado em Laval (2004), Freire (1967; 2011; 2018) e Ballestrin (2013). Os objetivos são: (i) apresentar o impacto da pandemia da Covid-19 na educação brasileira; (ii) descrever práticas de dominação, explicitadas no período pandêmico, as quais fortaleceram a manutenção de subjetividades colonizadas; (iii) enfatizar o papel da perspectiva decolonial como dispositivo de enfrentamento da realidade opressiva. Como resultados da pesquisa, demonstramos a desigualdade social presente na educação e a cultura desumanizadora vigente; logo, a proposição decolonial é viável para a reestruturação de valores.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".