Bibliographic record
Abstract
The idea of sustainable development emerged both from science and the environmental movement in the 70s and 80s of last century. Since then a lot was done in the field, sometimes without even naming it “sustainable development”, but a lot still remains to be done. In this paper we start from the consideration that sustainable development requires that we see our world as a system that connects space and any discussion today must first consider the enormous impacts that modern globalization trends are playing in shaping the economic geography of places, such as macro-regions. In the future, macro-regional development could be the most important platform for enhancing sustainability. The regional dimension is suitable for redefining the meaning of sustainable social, economic and environmental systems in a way which is practical and very close to the people and to the operative public decisions (Alkan Olsson et al. 2004). This paper is divided in different sections: the first is about the regional sustainable development concept and place-based approach; the second is about Local Agenda 21; the third about regional integration and developmental regionalism; the fourth is about regional sustainable development in practise and the European macro-regions; at the end some conclusive remarks concerns the macro-regional future strategies addressing sustainable development.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.033 | 0.013 |
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".