Alternatives to austerity? Post-crisis policy advice from global institutions
Bibliographic record
Abstract
The 2008 global financial crisis caused major anxiety about the stability of the neoliberal economic regime. This affected the financial and banking systems and also raised the spectre of mass unemployment and social unrest. A ‘post-crisis’ world was widely proclaimed in 2010. This was premature; by 2012 Europe was embroiled in a sovereign debt crisis and the US economy showed few signs of real recovery. A second recession seemed likely and austerity emerged as the standard response. Austerity, ‘the quality or state of being austere’ and ‘enforced or extreme economy’, became a buzzword. In practice, austerity means an economic and social policy based on balanced budgets to be achieved by reduced government spending, especially on employment and social policies, an approach entirely consistent with the neoliberal paradigm that has dominated policy-making for several decades. Yet the depth of the crisis provided an opportunity for rethinking the neoliberal policy package that had replaced the Keynesian welfare state, established after the Second World War. Cognizant of the fact that the development of alternatives to dominant paradigms may have many sources, this article probes the policy advice provided by two global organizations – the OECD and the ILO. As well as tracing the austerity motif, the article seeks to identify the extent to which alternatives were canvassed at the global social policy level.
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 | 0.018 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.012 | 0.018 |
| Insufficient payload (model declined to judge) | 0.007 | 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".