Wealth generation: How to boost income mobility in the UK
Bibliographic record
Abstract
Many argue that income mobility is declining. This applies to all types of income mobility (relative and absolute; intergenerational and intragenerational). As remedies, those who worry and others who want to improve mobility tend to propose expansions to welfare programmes. We argue that economic freedom (i.e., safer property rights, less regulated markets, lower taxation and open trade) is far more potent to improve income mobility than redistributive policies. There is a direct effect of economic freedom by removing legal hurdles to work. There is also an indirect effect by promoting economic growth in ways that are biased towards the poor. There is new international evidence suggesting that economic freedom promotes intergenerational absolute and relative income mobility. There is rich subnational data from Canada showing that economic freedom promotes intragenerational income mobility (relative and absolute). There is indirect evidence from economic history, economic geography and the economics of occupational licensing confirming the above results. The UK is a middling country in terms of both income mobility and occupational licensing laws. We highlight two main areas of reform to promote economic freedom to increase the UK's performance in mobility: deregulation in occupational licensing laws and housing restrictions.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 0.005 |
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".