Hardly neutral players: Australia's role in liberalising trade in education services
Bibliographic record
Abstract
In this paper we explore the avowedly partisan stance of Australia regarding trade in education services, the government's enthusiastic approach to market liberalisation through GATS, and its response to the concerns of vocal critics including academic and student unions. Education is a major export enterprise for Australia, both onshore and offshore. Education is publicly referred to as an 'industry' as often as a 'sector', and institutions behave in an aggressively market-oriented manner unthinkable two decades ago. While other major education exporters, including the EU, US and Canada, have showed flagging commitment to pursuing trade liberalisation in education due to opposition from the academic community and little pressure from the 'industry' for such an approach, Australia and New Zealand have come to represent the most ardent supporters of free trade in education. The Australian government's approach has involved making changes to its domestic education regulations to ensure they are consistent with market liberalisation, and facilitating the exploration of concerns through various international forums, including APEC, the WTO and OECD. Issues such as quality assurance, consumer protection, and public subsidies remain high on the list of matters for further debate.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.016 | 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".