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Record W7087492121 · doi:10.7202/1118939ar

The Social Value of Can Batlló

2024· article· en· W7087492121 on OpenAlexvenueno aff

Bibliographic record

VenueSens public · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Glycation End Products research
Canadian institutionsnot available
Fundersnot available
KeywordsCommonsWork (physics)Government (linguistics)Urban regenerationCivil societyInvestment (military)Order (exchange)

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.136

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.330
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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