Intra-Regional Relationality and Green City-Regionalism: Placing the Role of ‘Secondary Cities’
Bibliographic record
Abstract
This chapter considers the implications of ‘intra-regional relationality’ in comparative urban studies for extant and emerging work on city-regionalism, particularly as this involves spatial planning policies and growth discourses around global climate action. Scholars of new global green networks rarely highlight the city-regional context of ‘discrete places’, within which specific ‘leading’ cities engage in transnational network activities. Yet the urbanization of green internationalism reflects uneven local development patterns that require us to pay more attention to the complex roles of secondary cities. Put another way, we must think about the regional role(s) of secondary cities in city-regional complexes rather than simply ‘abstracting’ the green successes of core cities. Doing so changes how we map and explain urban sustainability as we follow the relational geographies and inter-urban flows that shape green polities. This chapter briefly illustrates these arguments with reference to initiatives in two city-regions in the Pacific Northwest: Vancouver-Surrey and Seattle-Tacoma.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".