Understanding the Inflation and Social Policy Nexus
Bibliographic record
Abstract
The cost-of-living crisis that began in the aftermath of the COVID-19 crisis and the attempted Russian invasion of Ukraine has major implications for social policy. In advanced industrial countries, this is the most dramatic cost-of-living crisis since the mid-late 1970s and early 1980s. In this contribution, we explore the inflation and social policy nexus to identify the nature and sources of inflation, its redistributive and policy implications, and the specific nature of the current cost-of-living crisis compared to two other recent crises: the 2008 financial crisis and the COVID-19 pandemic. Focusing on advanced industrial countries and drawing on the available scholarship about these topics, we offer the background necessary to understand the challenges facing welfare states in times of dramatically high inflation. As a way to provide broad context to the present themed section, our discussion stresses the economic, social, and political dynamics shaping social policy adaptation to inflationary pressures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".