Re-Shaping the Policy Landscape in Scottish Education, 2016-20: The Limitations of Structural Reform
Bibliographic record
Abstract
This paper examines the establishment and operation of a number of new bodies – variously called councils, boards, collaboratives, groups, forums and panels – concerned with the development of Scottish education. What were the intentions behind their creation during the period 2016-20? Do they amount to a significant reshaping of the policy community, making it more open and democratic, and representing a genuine re-distribution of power, or are they more concerned with public presentation and political positioning? The paper is based mainly, but not exclusively, on publicly available minutes and related papers produced by the various bodies. These allow for an analysis of their composition and remits, as well as an examination of the substantive issues they have considered. The discussion also takes account of earlier descriptions of the character of the policy community, as well as hopes that the creation of the Scottish Parliament in 1999 would lead to greater transparency and accountability in political decision-making. It is argued that, while the new bodies provide opportunities for some previously marginalised voices to be heard, they demonstrate the continuing potency of familiar forms of bureaucratic management and professional protectionism. The paper also indicates a number of areas where further research would deepen understanding of the politics of Scottish education.
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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 | 0.035 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.020 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".