Still vacant after all these years – Evaluating the efficiency of property-led urban regeneration
Bibliographic record
Abstract
Property developers and investors have been at the forefront of urban regeneration in the UK since the 1980s. This has produced an emphasis on prime office space, luxury apartments, shopping centres and leisure attractions, which has been widely criticised on social equity grounds. There has, however, been only limited interrogation of the failure of property-led regeneration to deliver on the development it promises or on whether it represents good value for public money. Nottingham Eastside is one such example of policy and market failure, where for over a quarter of a century, property developers and investors have come and gone, none of four masterplans have been implemented, decontamination and infrastructure provision has never been completed, and most of the land is still vacant. By reconstructing the story of Nottingham Eastside, the paper argues that over-reliance on property-led regeneration can be highly inefficient, let alone inequitable, as a means to achieve strategic urban redevelopment.
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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 | 0.012 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".