Revolution or backlash? The mediatisation of education policy in Australia
Bibliographic record
Abstract
Recent scholarship has identified the emergence of a new modality of policy work: the mediatisation of policy. This paper provides an Australian case study which reports on the tactics of an Australian Federal Minister of Education and a media commentator who both engaged in public pedagogical work for the purpose of spinning education policy. In particular, we argue that this example of the mediatisation of education policy has worked to stifle pedagogical innovation as advocates of middle schooling reform struggle against what appears to be a backlash to the social-democratic reforms of the post-World War II era. Such backlash politics is understood in terms of a struggle to maintain the role of teachers as curriculum designers and not be merely technicians; to sustain critically reflective learning communities of colleagues and friends; and not succumb to pedagogies of resentment that are driven by a logic of deficit views of students and their communities.
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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 | 0.029 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.055 |
| Scholarly communication | 0.018 | 0.012 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".