On the road to the in-between city: Excavating peripheral urbanisation in Chicago’s ‘Crosstown Corridor’
Bibliographic record
Abstract
This paper critically engages the uneven distribution of infrastructure provision, connectivity and mobility in contemporary neoliberal urban landscapes by uncovering the path-dependent trajectories and politics of transportation in post-suburbia. Departing from contemporary debates on the evolving geography of urban peripheries, I utilise a relational theorisation of the ‘in-between city’ to empirically unpack the urbanisation processes internalised in the evolution of the ‘ Zwischenstadt’ in a North American context. Through a longue durée case study of transportation planning, politics and spatial practice in Chicago’s ‘Crosstown Corridor’, in-between urbanisation is demonstrated to express an on-going multiscalar mediation of co-habiting modes of urbanism and strategic state actions that challenge generalised (sub)urbanisation narratives. Despite continued interest from planners, politicians and business groups, proposals for both a major urban expressway and rapid transit line have proved political lightning rods. Consequently, neighbourhood protests, personal political battles and macro-economic trends have locked-in a neglected development pathway for Chicago’s inner suburbs. I argue that through disclosing key contradictory political-economic imperatives and conflicting scales of mobility, it is possible to identify space for political and planning interventions that can adapt to, and develop, polycentric urban practice in and through in-between urban space.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".