Limits to the financialisation of the state: exploring obstructions to social impact bonds as a form of financialised statecraft in the UK, Israel, and Canada
Bibliographic record
Abstract
Within the financialisation literature, scholars have turned their attention to the state, exploring the adoption of financial activities by state actors, paying less attention to the limits of state financialisation. This paper explores these limits using the case of social impact bonds (SIBs). Pioneered in the UK in 2010 and subsequently trialed in some 35 countries, SIBs use private capital to fund social programs, with governments providing a return based on the degree of success. Despite expectations of dramatic growth, the SIB model has never truly taken hold. Based on the rollout of SIBs in the UK, Israel, and Canada, the paper considers the challenges encountered by the SIB enterprise as a form of financialised statecraft and identifies three barriers: (1) resistance to political agendas of state financialisation; (2) clashes between finance and public sector cultures; (3) financial innovation seen as ‘risk’ and ‘disruption’ to entrenched socio-technical routines. These barriers reveal tensions both within the state itself and between finance and the public sector, and indicate the importance of thinking about the limits and failures of state financialisation.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.032 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".