Socio-spatial impact of great urban projects in Bilbao and applicable lessons for other cities
Bibliographic record
Abstract
Urban regeneration involves multiple actors and organisations. This article focuses on the post-scenario of iconic, large scale urban project within a medium sized city. The city of Bilbao gained international recognition following the building of the Guggenheim Museum by Canadian architect Frank Ghery on the Abandoibarra site. Before this iconic project was built, the city suffered from socio-political problems including high unemployment, the closure of industries such as shipyards and steelworks and the terrorism associated with the Basque separatists which affected investment in the city. This effect, now known as the Bilbao effect, became a success story immediately with every city around the world wanting to replicate this type of intervention in brownfield industrial sites. The citys strategy was to implement large scale urban interventions with star architects and iconic buildings whilst removing and demolishing the existing industrial heritage that remained on those sites. This piece focuses in the internal contradictions of these processes, the increase in real estate values that these interventions provoked, and the process of gentrification that occurred as a result. It also analyses the issues raised by this development and looks at how they could be usefully applied to similar sites around the world.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".