Reinforcing unevenness: post-crisis geography and the spatial selectivity of the state
Bibliographic record
Abstract
This paper considers the unevenness of the 2007–08 crisis by examining the literature of England's North–South divide. From the 1980s this longstanding divide was exacerbated as a result of promoting London as a global financial hub, so when the crisis hit many expected some regional economic convergence as redundancies spread throughout the financial sector. This has, however, not taken place and previous patterns of uneven development have rather been reinforced. Attempts have been made to explain this deepening of established geographical patterns as the result of different regions’ degrees of economic resilience, but this approach is, however, problematic because it naturalizes crises, downscales responsibility and neglects politics. Inspired by Martin Jones’s concept of the ‘spatial selectivity of the state’, the paper will rather argue that to understand the uneven geography of the economic crisis, one has to look beyond localized resilience to how the state’s austerity policies have displaced the crisis’s impacts away from its origins in a London-centred financial sector.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".