Assessing the impact of maker services in Barcelona and Milan towards the 15-minute city model through their accessibility
Bibliographic record
Abstract
Re-organizing cities with proximity-based urban planning models such as the 15-Minute City model is an emerging and promising direction of policy, practice and research for sustainable cities. The planning of new urban spaces, infrastructures and mobilities requires planning and designing services that support citizens in their proximities. Along this direction, the emergence of the Maker Movement and its maker laboratories (Fab Labs, Makerspaces, Hackerspaces, DIYbio Labs, and so on) contributes to building the infrastructure for distributed design and manufacturing services in cities. How can we adopt the impact assessment of maker services in terms of potential accessibility for designing services towards the 15-Minute City model? We explore this issue within the context of the metropolitan areas of Barcelona and Milan by analysing 1) the 15-minute walking distance catchment areas of their maker service; 2) how to adopt this method for service design and impact assessment in the 15-Minute City model.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".