Lyn Tett and Mary Hamilton (eds) (2019) Resisting Neoliberalism in Education: Local, National and Transnational Perspectives
Bibliographic record
Abstract
In this edited collection from Tett and Hamilton, the authors explore the pervasive nature of neoliberalism within a range of educational contexts, including compulsory, adult and higher education. The need to resist dominant ideology, which puts profit over people, is a key theme throughout. Part One provides food for thought on ways to subvert dominant ideology within adult education. Chapter 1 (Thériault) examines the demands on community-based organisations in Quebec to undertake ‘accountability literacies’ (p.13) to prove their worth but highlights the resourcefulness of youth workers, who practise everyday resistance. I was left with a desire to read even more about the findings from this study, having personal experience of ‘conflictual cooperation’ as a youth worker funded by the state whilst challenging state demands on young people. Chapters 2 and 3 focus on adult education in England, examining adult literacy practice and policy. Duckworth and Smith (Chapter 2) propose that a discourse of transformation and hope constitutes natural resistance to the dominant expectations of ‘performative curricula’ (p.38). Allatt and Tett (Chapter 3) describe the approaches that adult literacy workers use to navigate ‘creative solutions’ (p.53) to meeting the demands set out by the discourse of employability skills that permeates policy and practice.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".