Entrepreneurial egalitarianism: How inequality and insecurity stifle innovation, and what we can do about it
Bibliographic record
Abstract
Despite recent advances in our understanding of how innovation happens – for example, recognising the role of the state in fuelling private sector innovation, and of user demand in enabling the generation and dissemination of innovation – the assumption that inequality somehow enables innovation remains widespread. This paper builds upon empirical evidence that more equal societies tend to be more innovative by exploring how inequality and insecurity can inhibit innovative activity at the individual level, both directly and indirectly, by diminishing the resources and capabilities which enable innovation, and disincentivising risktaking and entrepreneurialism. The paper also outlines an ‘entrepreneurial egalitarianism’ policy agenda, exploring how social and economic policies based on egalitarian values can support innovation, focusing in particular on a contributory social security system with income guarantees that supports entrepreneurial risk-taking, an expansive conception of universal basic services, a widening of access to capital, and the potential for institutions such as trade unions to facilitate innovation.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".