Resisting Neoliberalism from within the Academy: Subversion through an Activist Pedagogy
Bibliographic record
Abstract
Teaching and learning in the neoliberal academy means that educators in non-market-oriented departments, such as social work, face several constraints and challenges when trying to implement an anti-oppressive, social justice focused curriculum. This article considers challenges that can arise with an introductory social work course in the current context of neoliberalism, especially when open to both social work and non-social work students. With a particular focus on larger class sizes, the use of precarious labour and the depoliticization of the classroom, the authors use an inductive, reflective approach to analyse observations made about shifts in the behaviour and engagement of students in the course. The authors surmise possible explanations for these shifts, considering changes made to the substantive content and pedagogical practices of the course. Through this process the authors propose that these changes represent an ‘activist pedagogy’ which may offer potential for anti-oppressive education with students both inside and outside social work. As such, the authors propose ‘activist pedagogy’ as a possible way to resist and subvert the neoliberal educational paradigm and to better integrate the principles and practices of social justice and anti-oppressive social work into the classroom.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".