Theorising suburban infrastructure: a framework for critical and comparative analysis
Bibliographic record
Abstract
Suburban infrastructure holds a position of increasing geographic, political and conceptual importance in a rapidly urbanising world. However, the analytical significance of ‘suburban infrastructure’ risks becoming bogged down as a chaotic concept amid the maelstrom of contemporary peripheral urban growth and the explosion of interest in infrastructure in critical urban studies. This paper develops an open and flexible comparative theory of suburban infrastructure. I eschew concerns with definitional bounding to focus analytical attention on the relations between ‘the suburban’ (broadly considered) and multiple hard and soft infrastructures. These relations are captured in two ‘three‐dimensional’ dialectical triads: the first unpacks the modalities of infrastructure in, for and of suburbs; the second discloses the political economic processes (suburbanisation), lived experience (suburbanism) and dynamics of mediation internalised by particular suburban infrastructures. Bringing these conceptual frames together constructs a nine‐cell matrix that: (1) functions as a heuristic device providing conceptual clarity when discussing the suburbanity of infrastructures; (2) promotes comparative analysis across diverse global suburban contexts; and (3) develops tools to foreground the dialectical relations internalised in the concrete sociospatial modalities of suburban infrastructure. The paper shows that suburban infrastructure can only ever be partially suburban as a result of its co‐constituted and over‐determined production. I conclude by suggesting how the proposed approach may be mobilised to reimagine and reclaim suburban infrastructure as a crucial context and vital mechanism underpinning a progressive polycentric suburban spatial polity.
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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 | 0.015 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.006 | 0.065 |
| Scholarly communication | 0.014 | 0.023 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".