The master plans: what comes next?
Bibliographic record
Abstract
The master plan was designed in the framework of the 2002 Regional Development Plan (RDP) as the preferred tool for the development of the fourteen “areas of regional interest”. The plan thus made a triple promise: better coordination of public action, effective public/private partnerships (PPPs) and true democratic participation. The tool was implemented for the first time during the last regional legislature, and is evaluated here based on an empirical study of several cases including the emblematic case of the state administrative district, as well as an afternoon meeting to discuss the results. The authors feel that the administrative complexity, the opposing interests of the public and private sectors, and the difficulty to establish true participation on behalf of inhabitants jeopardise the efficiency of a tool which – when all is said and done – is not binding. But they do not confine themselves to this acknowledgment of (partial) failure. Instead of recommending the elimination of this mechanism, they outline proposals to improve it. Although the ‘master plan’ tool is headed in the right direction, it calls for other advancements towards urban management which is more democratic, more effective, respectful of collective interests and beneficial for the future of the city.
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 | 0.016 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.020 |
| Scholarly communication | 0.022 | 0.027 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".