Physics Education from a decolonial perspective: a case study with Brazilian curriculum
Bibliographic record
Abstract
Abstract The educational process is characterized as a set of pedagogical actions developed for a particular social group and provided with intentionality. In this sense, every pedagogical action involves an intention, which transfers and reproduces cultural patterns that materialize in social values and traditions. In this context, the postmodern decolonial thinking discussed by Quijano (2019), Mignolo and Walsh (2018), and Abdi (2011) are inserted, as well as the epistemological aspects given by Santos (2020). Thus, with this paper, we seek to present a case study developed in Brazil about the colonial influences that manifest themselves in the science curriculum of the State of São Paulo, Brazil, taking Physics Education as the context for analysis. For that, we used as a method of analysis the Discourse Analysis given by the France perspective about the ideological construction of the discourse. As preliminary results, we identified that the absence of an original Brazilian structure for the construction of the analyzed curriculum corroborates the perspectives of a form of colonization characterized by us as at the primary level, that is, epistemic. With the investigation, we hope to contribute to understanding which the cultural lens that act as a colonizing operator on the set of scientific standards and Brazilian scientific representativeness.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".