“Undemocracy”: inequalities in science

Xie, Yu

doi:10.1126/science.1252743

Cited by 110 publications

(72 citation statements)

References 15 publications

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“…[9,10] for various socio-economic inequalities. The study of inequality in society [11][12][13] is a topic of global focus and utmost current interest, bringing together researchers from various disciplines.…”

Section: Introductionmentioning

confidence: 99%

Inequality measures in kinetic exchange models of wealth distributions

Ghosh

Chatterjee

Inoue

et al. 2016

Physica A: Statistical Mechanics and its Applications

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In this paper, we study the inequality indices for some models of wealth exchange. We calculated Gini index and newly introduced k-index and compare the results with reported empirical data available for different countries. We have found lower and upper bounds for the indices and discuss the efficiencies of the models. Some exact analytical calculations are given for a few cases. We also exactly compute the quantities for Gamma and double Gamma distributions.

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Section: Introductionmentioning

confidence: 99%

Inequality measures in kinetic exchange models of wealth distributions

Ghosh

Chatterjee

Inoue

et al. 2016

Physica A: Statistical Mechanics and its Applications

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“…Private capital is the only recourse to meet these ambitions, and it is accompanied by dependency and demands. Endowments, the capital stores of universities, have grown increasingly concentrated (Xie 2014), with the five largest (Harvard, Yale, Texas, Stanford, and Princeton) exceeding US$110 billion in value (the approximate total of the next fifteen universities' endowments).…”

mentioning

confidence: 99%

Academic Capitalism

Hackett

2014

Science, Technology, & Human Values

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“…Such dynamics are enforced by increasing scarcity of time resources and an augmented need to filter a large amount of accessible information [59]. Evidence of the Matthew effect, also called accumulative advantage, is frequently detected in science [60] and considered by scientists to be the major bias in proposal evaluation ([48] pp.…”

Section: Self-reinforcing Dynamics Of Bibliometric Indicatorsmentioning

confidence: 99%

Strategies towards Evaluation beyond Scientific Impact. Pathways not only for Agricultural Research

Wolf

Häring

Heß

2015

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Various research fields, like organic agricultural research, are dedicated to solving real-world problems and contributing to sustainable development. Therefore, systems research and the application of interdisciplinary and transdisciplinary approaches are increasingly endorsed. However, research performance depends not only on self-conception, but also on framework conditions of the scientific system, which are not always of benefit to such research fields. Recently, science and its framework conditions have been under increasing scrutiny as regards their ability to serve societal benefit. This provides opportunities for (organic) agricultural research to engage in the development of a research system that will serve its needs. This article focuses on possible strategies for facilitating a balanced research evaluation that recognises scientific quality as well as societal relevance and applicability. These strategies are (a) to strengthen the general support for evaluation beyond scientific impact, and (b) to provide accessible data for such evaluations. Synergies of interest are found between open access movements and research communities focusing on global challenges and sustainability. As both are committed to increasing the societal benefit of science, they may support evaluation criteria such as knowledge production and dissemination tailored to societal needs, and the use of open access. Additional synergies exist between all those who scrutinise current research evaluation systems for their ability to serve scientific quality, which is also a precondition for societal benefit. Here, digital communication technologies provide opportunities to increase effectiveness, transparency, fairness and plurality in the dissemination of scientific results, quality assurance and reputation. Furthermore, funders may support transdisciplinary approaches and open access and improve data availability for evaluation beyond scientific impact. If they begin to use current research information systems that include societal impact

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“Undemocracy”: inequalities in science

Cited by 110 publications

References 15 publications

Inequality measures in kinetic exchange models of wealth distributions

Inequality measures in kinetic exchange models of wealth distributions

Academic Capitalism

Strategies towards Evaluation beyond Scientific Impact. Pathways not only for Agricultural Research

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