Chapter 11 Higher education students as consumers?
Bibliographic record
Abstract
In this chapter, we draw on an analysis of English policy documents and focus groups with students at three English higher education institutions, to explore some of the complexity in the ways in which the concept of student-as-consumer is discussed by both those formulating policy and the intended recipients. In relation to policies, this is evident in some of the apparent contradictions within government documents which, on one hand, emphasise strongly many aspects of a consumer discourse (foregrounding ideas around investment, choice and ensuring value of money) but, on the other hand, also discuss in some detail the vulnerability of students and their need of protection– which is clearly at odds with the notion of an ‘empowered consumer’. With respect to students, a similar degree of complexity can be seen in their differential awareness of the student-as-consumer discourse, and their varied responses to it.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 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".