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Is the gap widening among universities? On research output inequality and its measurement in the Korean higher education system

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Abstract

This study examines whether the inequality between universities is increasing in terms of research output, in the context of the New Public Management (NPM) regime based higher education reform in South Korea. Recent reforms in higher education sectors around the world illustrate a number of characteristics of NPM, with performance-based funding standing out among others. Performance-based funding has brought up several concerns, especially with unintended consequences of the reforms such as a widening gap in the research activities of universities. We provide an exploratory case study of the South Korean higher education system where performance-based funding programs are rampant, using a novel panel dataset comprised of all the general four-year universities (n = 184) in 2009–2015. The descriptive analysis of the temporal trend of research output inequality among universities shows that the answer of whether the gap is widening or not depends greatly on the use of indices of inequality. We report the conflicting results between the ‘relative’ and ‘absolute’ inequality index when applied to the dataset. Our findings are followed by the discussion on the measurements of inequality and their axioms regarding the institutional Matthew effect, suggesting more consideration on the nature of the data and the context.

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Notes

  1. Performance-based funding here refers to various sorts of funding schemes based performance such as evaluation-, competition-, selection- and assessment-based funding analyzed in the previous literature.

  2. The four categories of journals classified by the NRF are (i) KCI (the citation index for domestic academic journals created by NRF), (ii) non-KCI domestic journals, (iii) SCI/SCOPUS (including SSCI, A&HCI, SCIE), and (iv) non-SCI/SCOPUS international journals.

  3. In our dataset, the numbers of publication counts are rounded to three decimal places.

  4. The package ‘ineq’ of R (Zeileis 2014) is used for the actual calculation of relative Gini coefficients. The absolute Gini coefficients were calculated by simply multiplying the mean value to the relative Gini coefficients (Niño-Zarazúa and Roope 2016).

  5. While the relative Gini coefficient ranges from zero (perfect equality) to one (perfect inequality), there is no upper bound for absolute Gini coefficients which depend on the mean value of the given attribute.

  6. One of the axioms for inequality measures is ‘anonymity’ so that the measures only refer to distribution of attributes without assigning or identifying the attributes to particular members of the group.

  7. Gradations on the right side of the figures are for the absolute Gini coefficients, which are converted by multiplying averages of the mean value of each publication to the left side gradations of the figures, which are for the relative Gini coefficients.

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Jeon, J., Kim, S.Y. Is the gap widening among universities? On research output inequality and its measurement in the Korean higher education system. Qual Quant 52, 589–606 (2018). https://doi.org/10.1007/s11135-017-0652-y

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