Resisting far right and neoliberal agendas in education: The stance of critical educators
Bibliographic record
Abstract
Since the 1980s the discourses of neoliberalism and authoritarianism have merged, cre- ating the echoes of a fascist past that has moved from the margins to the center global politics. Education as a mode of domination has become central to politics and operates not only through various levels of schooling but also through a range of cultural apparatuses, including the social media and mainstream platforms. In the current moment, neoliberal fascism has aggressively targeted higher education, attempting to eliminate all vestiges of critical thinking, faculty power, historical consciousness, and critical knowledge. The general aim here is to turn higher education into a white Christian nationalist indoctri- nation center. Against the rise of neo-fascism and it current attacks on higher education globally, this essay raises a number of issues regarding the purpose of education in a time of tyranny, the role of critical pedagogy as an empowering practice, and how the notion of educated hope can overcome a politics of despair and hatred and create a movement of hope and collective resistance. The essay advances the idea that education is central to any viable notion of politics and that educators need to develop a more aggressive and informed pedagogical notion of the political, embrace critical pedagogy as a powerful tool of resistance, and create a mass movement to overthrow neoliberal capitalism with a radical democracy.
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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 | 0.021 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.015 | 0.126 |
| Scholarly communication | 0.026 | 0.020 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 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".