From the Frankfurt greenbelt to the Regionalpark RheinMain: an institutional perspective on regional greenbelt governance
Bibliographic record
Abstract
Legally protected by its own constitution since 1991, the greenbelt (or ‘GrünGürtel’) forms a ring of greenspace around Frankfurt, Germany and has been considered an effective reaction to municipal development pressures. As a response to Frankfurt’s embeddedness within a highly interconnected suburbanized region under extensive growth pressures, the Regionalpark RheinMain was established to upscale the greenbelt to the regional level. In this article, we explore the institutional complexities of upscaling a localized greenbelt to the regional scale in the Frankfurt Rhine-Main region, which is known for its fragmented institutional environment formed by numerous planning authorities and special purpose agencies with overlapping jurisdictions. Engaging with the literature on the governance of greenbelts from an institutional perspective, we analyse how the development of the Regionalpark RheinMain is shaped by horizontal, vertical and territorial coordination problems. We conclude that that the Regionalpark RheinMain is not appropriately institutionalized to serve as an effective regional greenbelt, resulting in localized initiatives and the delegation of greenbelt planning to municipalities.
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 | 0.002 | 0.016 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".