“Globalization,” Coloniality, and Decolonial Love in STEM Education
Bibliographic record
Abstract
Abstract From the era of European empire to the global trades escalated after the World Wars, technological advancement, one of the key underlying conditions of globalization, has been closely linked with the production and reproduction of the colonizer/colonized. The rhetoric of modernity characterized by “salvation,” “rationality,” “development,” and nature-society or nature-culture divides underlies dominant perspectives on Science, Technology, Engineering, and Mathematics (STEM) education that have historically positioned economic development and national security as its core values. Such rhetoric inevitably and implicitly generates the logic of oppression and exploitation. Against the backdrop of nationalist and militaristic discourse representing modernity or coloniality, counter-voices have also arisen to envision a future of STEM education that is more humane and socioecologically just. Such bodies of critiques have interrogated interlocking colonial domains that shape the realm of STEM education: (a) settler colonialism, (b) paternalism, genderism, and coloniality, and (c) militarism and aggression and violence against the geopolitical Other. Our ways of knowing and being with STEM disciplines have been inexorably changed in the midst of the COVID-19 pandemic, which powerfully showed us how we live in the global chain of contagion. What kinds of portrayal can we depict if we dismantle colonial imaginaries of STEM education and instead center decolonial love—love that resists the nature-culture or nature-society divide, love to know our responsibilities and enact them in ways that give back, love that does not neglect historical oppression and violence yet carries us through? STEM education that posits decolonial love at its core will be inevitably and critically transdisciplinary, expanding the epistemological and ontological boundaries to embrace those who had been colonized and disciplined through racialized, gendered, and classist disciplinary practices of STEM.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.055 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| 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".