On Maitre D's, Trojan Horses and Aftershocks: Neoliberalism Redux in Ireland after the Crash
Bibliographic record
Abstract
Critical scholarship has revealed the darker side of the model of economic recovery, which Ireland has embraced from 2008 and has placed under scrutiny the claim that the country is witnessing a ‘Celtic comeback’ because of this model. But as crisis recedes and the contours of a new normal become manifest, perhaps it is surprising that less attention is being given to the politics of Ireland’s post-crash politico-institutional architecture and growth agenda. In this brief provocation, we mobilise Peck, Theodore and Brenner’s (2013) theorisation of ‘neoliberalism redux’ to explore the structuration of regulatory institutions and experiments in Ireland after the crash. We argue that whilst Ireland will continue to be cast as a small open, liberalised, entrepreneurial and glocalised economy, its post-crash development manifesto needs to be construed as less a straightforward reset or return to a pre-crash model after a shock or blip and more a historically novel and contested reimagining and reinvention. It could have been – and may yet be – different. We invoke the themes of ‘maitre d’s’, ‘Trojan horses’ and ‘aftershocks’ to open a debate on the forces which will combine to determine the fate of neoliberalism redux in Ireland.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".