When neoliberalism meets technocracy: intra-elite conflict and the realignment of Britain’s macroeconomic regime under Liz Truss
Bibliographic record
Abstract
This article offers a new account of Liz Truss’s premiership by analysing the political economy of the 2022 mini-Budget crisis. Engaging with literature on depoliticisation, statecraft, and the City-Bank-Treasury nexus, it reconceptualises the rise and fall of the Truss government as a moment of intra-elite conflict over the governance of macroeconomic policy. It argues that Truss’s radical neoliberal experiment constituted a novel form of elite-led backlash against the depoliticisation of economic management. By challenging the independence of key institutions in the British state and breaching long-established practices of depoliticised governance, her disorderly approach to statecraft catalysed an institutional response. Developing a theory of institutional realignment through crisis, the article shows how a ‘Bank-Treasury-OBR nexus’ coalesced during the crisis around a consensus of monetary dominance, fiscal discipline, and technocratic expertise. Leveraging their institutional authority to signal impending market turmoil, the nexus ultimately played a key role in Truss’s downfall. The article concludes by arguing that Truss’s premiership provides important insight into changing dynamics of contestation surrounding depoliticised governance.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.033 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".