Bibliographic record
Abstract
This chapter explores the way neoliberalism has changed the field of practice in post-16 education and training in the UK, Australia, New Zealand and Canada. While ‘third way’ politics brought a commitment to questions of social justice, neoliberalism was hugely influential in reshaping the way that universities and vocational education and training (VET) providers were to operate. Secondly the chapter will outline the major change brought about around ‘user pays’ philosophy exploring issues of fees and student debt. While this approach has a long history in some countries, by the 21st century it was fully established in the post-16 educational and training sector and, as we shall see, since the crisis it has had substantial impacts on levels of student debt. The final section of this chapter returns us to the question of the widening participation agenda, where we will examine how effective it has been in the UK, Australia, Canada and New Zealand in bringing different social groups into the education and training field
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".