The emerging role of mega-urban regions in the sustainability of global production-consumption systems
Bibliographic record
Abstract
Abstract Mega-urban regions (MURs) are important consumers or traders of resources from, or producers of wastes destined for, the global hinterlands. These roles, coupled with their concentration, clustering and centrality effects, mean MURs have a disproportionately large effect on the sustainability of global production-consumption systems (PCSs). Actions taken within MURs influence the sustainability of global PCSs, and vice versa; but that influence is complicated by complex governance intersections. Three cases are used to illustrate governance innovation in MUR-PCS interactions: industrial symbiosis in Tianjin, China; electricity production in London, UK; and the adoption of standards and labels for seafood in Bangkok, Thailand. In London and Tianjin, waste capture reduced consumption of hinterland resources, whereas in Bangkok, the aim was to improve the sustainability of resource use in coastal and marine hinterlands. We suggest an agenda for research to evaluate the potential for transferrable MUR governance innovation to enable sustainable and equitable PCSs.
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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 | 0.002 | 0.002 |
| 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 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.004 |
| 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".