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A numerical algorithm with preference statements to evaluate the performance of scientists.

Martin Ricker1

  • 1Instituto de Biología, Universidad Nacional Autónoma de México (UNAM), Ciudad Universitaria, 04510 México, D.F. Mexico.

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Summary
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This study proposes a numerical algorithm for semi-automatically evaluating scientists

Keywords:
Academic evaluationEvaluation committeeScientists’ valueSistema Nacional de Investigadores (Mexico)UNAM’s PRIDE (Mexico)

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Area of Science:

  • Bibliometrics and Scientometrics
  • Science Policy and Evaluation
  • Research Management

Background:

  • Academic evaluation increasingly relies on quantitative metrics like publication counts and citations.
  • Current evaluation systems struggle with objectivity due to inherent subjective preferences.
  • Scientists operate in a non-market context, making direct price-based evaluation challenging.

Purpose of the Study:

  • To propose a numerical algorithm for semi-automatic academic performance evaluation.
  • To facilitate fair reward distribution within large-scale evaluation systems.
  • To incorporate relative prices of scientific goods and services into evaluation.

Main Methods:

  • Development of a numerical algorithm using relative prices as input.
  • Application of the algorithm to data from 73 scientists at Mexico's National University Biology Institute.
  • Analysis of reward allocation and academic priorities based on committee-determined preferences.

Main Results:

  • The proposed algorithm allows for semi-automatic, quantitative academic performance assessment.
  • Reward distribution and academic priorities are significantly influenced by subjective preferences.
  • Analysis highlights the dependence of evaluation outcomes on committee-defined relative prices.

Conclusions:

  • A semi-automatic evaluation system can reduce arbitrariness and superficiality in assessing scientists.
  • Incorporating relative prices, determined by committees, offers a more nuanced evaluation approach.
  • Recommends setting a maximum number of evaluated products/activities to promote quality over quantity.