Book contents
- Frontmatter
- Contents
- Additional Resources
- Introduction: Structure Matters
- Part I A Brief Guide to Network Science
- Part II Language
- Part III Mind
- Part IV Society
- 14 Network Illusions: How Structure Misleads Us
- 15 Group Problem Solving: Harnessing the Wisdom of the Crowds
- 16 The Segregation of Belief: How Structure Facilitates False Consensus
- 17 The Conspiracy Frame: Coherence through Self-Supporting Beliefs
- 18 The Kennedy Paradox: Games of Conflict and Escalation
- 19 Fund People Not Projects: A Universal Basic Income for Research
- References
- Index
19 - Fund People Not Projects: A Universal Basic Income for Research
from Part IV - Society
Published online by Cambridge University Press: 08 November 2024
- Frontmatter
- Contents
- Additional Resources
- Introduction: Structure Matters
- Part I A Brief Guide to Network Science
- Part II Language
- Part III Mind
- Part IV Society
- 14 Network Illusions: How Structure Misleads Us
- 15 Group Problem Solving: Harnessing the Wisdom of the Crowds
- 16 The Segregation of Belief: How Structure Facilitates False Consensus
- 17 The Conspiracy Frame: Coherence through Self-Supporting Beliefs
- 18 The Kennedy Paradox: Games of Conflict and Escalation
- 19 Fund People Not Projects: A Universal Basic Income for Research
- References
- Index
Summary
A universal basic income is widely endorsed as a critical feature of effective governance. It is also growing in popularity in an era of substantial collective wealth alongside growing inequality. But how could it work? Current economic policies necessarily influence wealth distributions, but they are often sufficiently complicated that they hide their inefficiencies. Simplifications based on network science can offer plausible solutions and even offer ways to base universal basic income on merit. Here we will examine a case study based on a universal basic income for researchers. This is an important case because numerous funding agencies currently require costly proposal processes with high administrative costs. These are costly for the proposal writers, their evaluators, and the progress of science itself. Moreover, the outcomes are known to be biased and inefficiently managed. Network science can help us redesign funding allocations in a less costly and potentially more equitable way.
Keywords
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- Information
- Behavioral Network ScienceLanguage, Mind, and Society, pp. 320 - 329Publisher: Cambridge University PressPrint publication year: 2024