Housing policy in the UK: the transformation of “The Right to Buy” social housing policy
Bibliographic record
Abstract
This paper examines how and why the Right to Buy (RTB) scheme changed drastically in the UK from 1980 to 2016 through the lens of Hall’s model of social learning and Sabatier’s advocacy coalition framework (ACF). This paper argues that changes were made to the Right to Buy scheme from 1980 to 2016 in order to increase the attractiveness of the policy. The study was conducted using a non-positivist approach to research. The findings of this study revealed that that the UK government’s decision to reduce the residency requirement from 3 years to 2 years in the RTB scheme in 1984 and to increase the percentage of discounts in the scheme constitutes a first-order policy change as described by Hall. On the other hand, the introduction of the new Right to Acquire in the RTB policy by the Labor party in 1997 constitutes a second-order change. While abolishing the RTB policy in Scotland by the Scottish National Party in July 2016 constitutes a third-order change. Furthermore, the results of this paper showed that the shared core beliefs in the virtues of private ownership between the Conservative party and the “New Labour” that came to power in 1997 in the UK can better be understood through the lens of Sabatier’s ACF.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".