DISCURSOS E ESCRITAS ACERCA DA EQUIDADE, DESIGUALDADE ESCOLAR E MERITOCRACIA NA BASE NACIONAL COMUM CURRICULAR (2017 E 2018)
Bibliographic record
Abstract
The analyses recorded in this study are the result of the readings, debates, incursions initiated in the Group of Studies and Research School Culture Observatory (SCO), accompanied by/in the line of studies “History, Politics, Education” in/from the Post-graduation Program in Education of the Federal University of Mato Grosso do Sul. Privileged spaces for the construction of knowledge about the curricular texts/documents produced for formal basic education space. In this context, we have chosen as source and object the National Common Curriculum Base (2017; 2018), its speeches and its writings on equity, school inequality and meritocracy. In addition we insert productions published in magazines like e-Curriculum Magazines (Catholic University Pontifical from São Paulo), Curriculum without Borders (Federal University of Pelotas) and Curriculum Space (Federal University of Paraíba) by building a state of critical knowledge, and those seized on the website of the non-governmental and non-partisan network of persons and institutions, Movement for Base. Therefore, our analyses are anchored in the sociological studies of Bourdieu (2004; 2007; 2019), approximate of the defenses of Connell (1999), Dubet (2011; 2014; 2020), Dardot and Laval (2016), Fanfani (2011), Wacquant (2005), related to social justice, Fraser (2002; 2006), Fraser and Jaeggi (2020), among others. In this context, our methodological operation has been guided by the techniques of bibliographic and documentary research, in order to characterize a greater attention to analysis, which recover the relationship between the curricular text/document “National Common Curriculum Base”, the curriculum, the equity, the school inequality and the meritocracy, approximated to social, political, economic, cultural contributions, in the detriment of the pure description and interpretation of the proposed curricular structures. In conclusion, discourses and writings have been involved in the determinants of the production and reproduction of the homo economicus, as a cultivated culture, associated with the individualistic neoliberal character, given the treatment in a pragmatic way, of the possibility of equity, school inequality and meritocracy to be linked to the demands (real and created) on justice in their forms of recognition and/or redistribution.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".