Bibliographic record
Abstract
After a decade of design explorations and reflections, meanwhile uses are widely accepted by the international community as a successful multidisciplinary approach to deal with the post-financial crisis main consequences. Among them, can be counted the increasing offer of waiting lands and vacant buildings and the search of unconventional agents of transformation to claim any abandoned space. What is still missing, however, is the acknowledgment that the impact of the phenomenon and its diffused quality, mostly interstitial, is giving us an unprecedented possibility to reconsider the definition and management of the city’s form. In that perspective, since the 60s of the last century, the planning activity succeeded to claim a total control over the territorial development, expanding the role of the calculating thinking to a limitless unprecedented perspective. Therefore, architecture was progressively reduced to a stylistic exercise to confirm ex-post political decision already taken out of any previous spatial experimentation. This paper aims to demonstrate that meanwhile uses can contribute to limit the hubris of the contemporary planning and, beyond that, to imagine new urban configurations for the existing city. The ex-railroad freight Ravone in Bologna, Italy, is the proposed testing ground, which seems to confirm this vision.
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 | 0.014 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.020 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.022 | 0.012 |
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".