Governing a sub/urban planet
Bibliographic record
Abstract
This paper evaluates Roger Keil's influence on the fields of urban and regional governance and suburban studies, underscoring his foundational contributions and identifying pathways for future sub/urban research. We trace Keil's intellectual trajectory from his early work on metropolitan politics and new regionalism in Los Angeles to his later engagement with the evolving landscapes of twenty-first-century global suburbanization. Through this progression, we demonstrate how his scholarship illuminates the intricate co-constitutive relationship between sub/urban governance and extended urbanization. Cutting through rote critique and caricature, we argue that Keil's research, theoretical interventions, and activism on the urban periphery have consistently opened new lines of inquiry while offering generous analytical tools and provocations to probe our possible urban futures. Essential to his approach is a distinctive interdisciplinary sociospatial perspective that critically interrogates the dialectics of suburbanization–suburbanism, decenters the city within critical urban studies, and situates urban knowledge production at the intersection of global urban processes and politics on the street. In an ‘urban age’ that is increasingly characterized by the suburban, Keil's work offers a vital foundation for researchers, scholar-activists, and practitioners seeking to develop deeper insights into post-city urban worlds where diverse, transformative sub/urban politics and polities continue to emerge.
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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 | 0.001 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.008 |
| 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".