A critical cluster analysis of 44 indicators of author-level performance
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A critical cluster analysis of 44 indicators of author-level performance. / Wildgaard, Lorna Elizabeth.
In: Journal of Informetrics, Vol. 10, No. 4, 2016, p. 1055-1078.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - A critical cluster analysis of 44 indicators of author-level performance
AU - Wildgaard, Lorna Elizabeth
PY - 2016
Y1 - 2016
N2 - This paper explores a 7-stage cluster methodology as a process to identify appropriate indicators for evaluation of individual researchers at a disciplinary and seniority level. Publication and citation data for 741 researchers from 4 disciplines was collected in Web of Science. Forty-four indicators of individual researcher performance were computed using the data. The clustering solution was supported by continued reference to the researcher’s curriculum vitae, an effect analysis and a risk analysis. Disciplinary appropriate indicators were identified and used to divide the researchers into four groups; low, middle, high and extremely high performers. Seniority-specific indicators were not identified. The practical importance of the recommended disciplinary appropriate indicators is concerning. Our study revealed several critical concerns that should be investigated in the application of statistics in research evaluation.The strength of the 7-stage cluster methodology is that it makes clear that in the evaluation of individual researchers, statistics cannot stand alone. The methodology is reliant on contextual information to verify the bibliometric values and cluster solution. It is important to do studies that investigate the usefulness of statistical evaluation methodologies to help us as a community learn more about the appropriateness of particular bibliometric indicators in the analysis of different researcher profiles.
AB - This paper explores a 7-stage cluster methodology as a process to identify appropriate indicators for evaluation of individual researchers at a disciplinary and seniority level. Publication and citation data for 741 researchers from 4 disciplines was collected in Web of Science. Forty-four indicators of individual researcher performance were computed using the data. The clustering solution was supported by continued reference to the researcher’s curriculum vitae, an effect analysis and a risk analysis. Disciplinary appropriate indicators were identified and used to divide the researchers into four groups; low, middle, high and extremely high performers. Seniority-specific indicators were not identified. The practical importance of the recommended disciplinary appropriate indicators is concerning. Our study revealed several critical concerns that should be investigated in the application of statistics in research evaluation.The strength of the 7-stage cluster methodology is that it makes clear that in the evaluation of individual researchers, statistics cannot stand alone. The methodology is reliant on contextual information to verify the bibliometric values and cluster solution. It is important to do studies that investigate the usefulness of statistical evaluation methodologies to help us as a community learn more about the appropriateness of particular bibliometric indicators in the analysis of different researcher profiles.
UR - https://www.sciencedirect.com/science/article/pii/S1751157716301171
U2 - 10.1016/j.joi.2016.09.003
DO - 10.1016/j.joi.2016.09.003
M3 - Journal article
VL - 10
SP - 1055
EP - 1078
JO - Journal of Informetrics
JF - Journal of Informetrics
SN - 1751-1577
IS - 4
ER -
ID: 166716626