Discourse in Comparative Policy Analysis: Privatisation Policies in Britain, Russia and the United States
Bibliographic record
Abstract
Abstract Privatisation has been of the most widely used and extensively debated policies in the world for the last quarter century. This phenomenon, though, is mostly unified by rhetoric, and substantially varies across time and space, particularly in implementation. To answer the question of what presupposes a choice of particular mechanism of privatisation, three distinct cases of privatisation (the US, the UK, and Russia) are analysed through Fischer's (1995) model of practical policy deliberation. The model tests the reasons for policy ranging from its technical efficiency to its relation to the ideological principles that justify the societal system. The elaborated theory suggests that privatisation policies generally pursue multiple goals, with the prevailing goal being determined by the dominant discourse in which the topic of privatisation is debated in society. The prevailing goal, in turn, determines the privatisation mechanism that maximises this particular goal.
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.009 | 0.021 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".