Bibliographic record
Abstract
The first installment of this two-part paper made a case for a conjunctural approach to urban studies, reserving a special place for the provisional formulation and ongoing revision of midlevel theories – from the entrepreneurial city to austerity urbanism and financialised urban governance – while positioning abstraction and contextualisation as simultaneous, dialogic practices. It follows that such arguments can be developed only so far in the absence of concrete cases, where conjunctural accounts actually gain traction, direction and purpose. Seeking to operationalise some of these methodological principles by way of a situated, single-city case study, this part of the paper returns to the financially challenged casino capital of Atlantic City, tracing its long (and notorious) history of entrepreneurial dealings, from Republican machine control to the ‘experiment’ with legalised gambling that was launched in the mid-1970s, and positioning the structural crisis that preceded the casino pact with the existential crisis that has been generated in the wake of the failure of this distinctive local growth machine. Atlantic City made a very large wager that did not pay off, the unravelling of its much-emulated model of entrepreneurial urbanism dramatising a distinctly ‘late-entrepreneurial’ moment of fiscally mandated governance and political crisis.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".