Bibliographic record
Abstract
The constant dialogue between social movements and local government has made the city of Barcelona a reference laboratory for urban regeneration and social innovation. However, in the past, the plurality of spaces managed by civil society did not correspond to clear co-management schemes and only recently a regulatory framework based on the concept of commons has been created: the Citizens Assets Programme. Within this new programme, the urban planning concession of the Can Batlló neighbours’ association–a self-managed community active since 2011 at the former industrial site–represents a further innovation. For the first time, an urban planning concession was granted to a self-managed non-profit entity–which considers that the community project of Can Batlló constitutes an important social benefit for the city of Barcelona–which measures and monitors it according to new administrative tools: the community balance, to track the social impact of the community; and the social return to valorise economically the voluntary work of the community in recovering the common and that “justifies” the investment made by the municipality in conceding the space. This research reconstructs the co-production of these new tools in order to study the effects and opportunities that they create both inside and outside the city of Barcelona, with particular attention to the economic valorisation of voluntary work as a means of communicating, attracting resources and legitimizing the work of self-managed communities within regenerated spaces.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".