Revisiting radical diversality: a philosophy of inclusion premised on the selective rejection of origins
Bibliographic record
Abstract
This article addresses the political philosophy of a border position articulated by de Oliveira Andreotti (2011 de Oliveira Andreotti, V. 2011. “(Towards) Decoloniality and Diversality in Global Citizenship Education.” Globalisation, Societies and Education 9 (3–4): 381–397. doi: 10.1080/14767724.2011.605323[Taylor & Francis Online] , [Google Scholar]. “(Towards) Decoloniality and Diversality in Global Citizenship Education.” Globalisation, Societies and Education 9 (3–4): 381–397) with reference to the Latin American Modernity/Coloniality Research Group. This border epistemology will be discussed in the context of the claims of radical diversality as necessary in decolonial thinking and political theory. The article consists of a first half which considers the question of a centre and the problems associated with borders in comparison with Fanon (2004 Fanon, F. 2004. The Wretched of the Earth. New York: Grove Press. [Google Scholar]. The Wretched of the Earth. New York: Grove Press, 2008. Black Skin, White Masks. New York: Grove Press). The second half consists of an analysis of narrative responses from a grad seminar on decolonising methodologies which considered de Oliveira Andreotti’s (2011. “(Towards) Decoloniality and Diversality in Global Citizenship Education.” Globalisation, Societies and Education 9 (3–4): 381–397) work in the Winter Term of 2018.
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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 | 0.016 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.121 |
| Scholarly communication | 0.012 | 0.025 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.005 | 0.010 |
| 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".