Crisis and Austerity in Eight Cities: An Overview
Bibliographic record
Abstract
Chapter 1 focuses on how the eight cities encountered, worked with and against austerity in the period after the GEC. It begins by providing a flavour of the histories and traditions which contribute to explaining how austerity was experienced and mediated. It then turns to a discussion of Athens, Baltimore, Dublin, Leicester and Montréal, where more-or-less harsh forms of forms of austerity were implemented in the decade after GEC. It then looks at the three cities which, in different ways, provide a contrast with the story of austerity. These are Barcelona, Melbourne and Nantes. It is from these cities, primarily, that positive lessons emerge for charting governing directions beyond austerity. Chapters 2 and 3 build further on these reflections. The eight cities are rooted in very different political systems and traditions. For example, the military coup in Greece (1967–1974) and the Francoist dictatorship in Spain (1939–1975) created highly centralized administrations characterized by repression and the suppression of civil society, which nevertheless survived underground and played crucial roles in the democratic transitions of the 1970s. In contrast, the modern welfare state elsewhere emerged much earlier, for example in Australia or in the United Kingdom after the Second World War, to prevent recurrence of the Great Depression and in response to political demands raised by the working class. While we do not analyse governance trends through the twentieth century, these examples capture something of how the scope for democratic practices, like participation, varied in the aftermath of the war.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| 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".