Bibliographic record
Abstract
The topic of vacant office buildings is the most evident aspect of the dismissed parts of cities. By an international point of view, the issue can be found in a series of research works, including those published by some researchers of the Delft University of Technology (Geraedts R., Van der Voordt T., 2003-2007, Remoy H.T., Van der Voordt T., 2007-2014, Remoy H.T., 2014) and of the Tokyo Metropolitan University (Ogawa H., Kobayashi K. et alii, 2007). It can also be found in a series of policies aimed to re-use these buildings promoted by some Municipality, such as Toronto, London and Paris. \nIn Milan, the problem recently assumed considerable importance: the vacancy rate reached 13,1%, compared to the 7/8% of the 2008, and 1.575.000 square meters of offices are currently vacant (BNP Paribas Real Estate, 2015). The situation is expected to get worse, because a report made by BNP Paribas Real Estate in 2014 shows that 2.390.000 square meters of new offices could be on the market before 2020 and the 77% of these spaces is still without a tenant. Moreover, about 75% of the vacant stock has very low energy performances. \nThe ask of quality of living is always more urgent and it should be more and more able to relate the social, the environmental and the economic aspect characterizing the structure of the concept of sustainability. This paper supports the idea of a necessary adaptive reuse of some office buildings into housing, with two targets: on the one side the reuse and the upgrading of the energy performances of the vacant stock; on the other side the answer to the needs of new forms of living, to promote a smart strategy for the contemporary city. \nThe result of this paper is a picture of the current state of the problem in the city of Milan, through the analysis of the factors (location, prevalent building types, constructive solutions, etc.) that define the basis for the setting of design guidelines oriented to realize projects, that should be characterized by functional and social mix, social housing and new forms of living, in order to rehabilitate buildings and open spaces considered as resources, so that they could also stimulate the regeneration of their own urban context.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".