Strategies for housing regeneration in city centres. An opportunity to incorporate bioclimatic criteria in Lavapies, Madrid (Spain)
Bibliographic record
Abstract
According to the OECD 1992 report about Spanish distressed urban areas, in 1992 17% of the vulnerable population lived in old neighbourhoods or historical cities centres. This paper explores different proposals and interventions to improve housing conditions in Lavapies (Madrid). From its very beginning Lavapies was a slum quarter, where dangerous and insane activities could be developed. Plots were progressively densified, with new constructions over what previously were house gardens (vegetables); and also by increasing the height of the buildings. Tenement houses (corralas) were originally the lowest level for ccommodation in Spain. Still now housing conditions are usually insalubrious and it is almost impossible for the sun and fresh air to reach inside the inner houses. Nowadays the quarter is targeted for low classes and immigrants, but also for bohemia people. Property is very fragmented and changes a lot. It is not easy to find ways of improving conditions without expelling traditional residents. The area has been declared of special interest for rehabilitation (with incentives and subsidies). The office in charge of rehabilitation has made studies to incorporate sustainable criteria in the process. But public intervention to rehabilitate residence buildings is really difficult to go ahead, so they concentrate on improving streets and public spaces trying to make the neighbourhood more appealing. Also some important public buildings have been renovated aimed to be paradigmatic. The paper focuses on the scale of the intervention, showing how habitability can be improved without changing morphology, by studying local conditions and by adapting the limits of each individual intervention to reach interaction between different plots.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".