Bibliographic record
Abstract
Theodore (2020: 2) argued that since the GEC, ‘austerity has become the primary means for the further neoliberalisation of inherited arrangements’: neoliberalisation upon earlier waves of neoliberalism. Chapter 2 delves into this proposition. It begins by exploring the impact of the GEC, and its aftermath, in the eight countries and cities studied. It proceeds to examine the interplay of key terms introduced in Chapter 1: crisis, austerity and neoliberalisation. The chapter allocates the cities to three groups: those in which austerity is recognised as a central concept or challenge and a warrant for neoliberalisation (Athens, Dublin and Leicester), those in which it is concealed or re-signified within an otherwise vigorous neoliberalisation agenda (Baltimore and Montréal), and those positioning themselves critically, at a distance or outside it (Barcelona, Dandenong and Nantes). The chapter concludes by discussing theoretical implications of convergence and divergence in the cross-cutting relationships between crisis, austerity and neoliberalisation. Table 2.1 characterises the eight cities in relation to population, economic performance and political control in the 2015–18 period. As explained in the Introductory chapter, the statistics are imprecise and drawn from a range of sources, some more up to date than others. Athens is the capital of Greece, and the epicentre of European austerity. Baltimore is at the southern end of the mega-region stretching several hundred miles from Boston to Washington, DC in the USA. Barcelona is the capital of Catalonia and, in terms of size and stature, Spain’s second city.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".