Abstract
Lindsey recently examined the precision of the manuscript review process using a stochastic model. The study reported that the low reliability found by previous studies results in journals publishing a large number of papers that should otherwise be rejected and rejecting an equally large number of papers that should be accepted.Hargens andHerting have criticized this view. This paper addresses their criticisms. The paper includes an examination of sociology journals usingimpact scores. The differences between journals is noted. Part of the variation between sociology journals derives from their editorial operations. Central to their editorial operations is the reviewing of manuscripts for publication. Not all journals perform this task equally well. The consequences of poor editorial management are discussed. To improve the quality of published work journals need to reduce the low reliability of the current manuscript review process.
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L.L. Hargens, J.R. Herting, A new approach to referees' assessment of manuscripts,Social Science Research, 19 (1990) 1. This paper is the source for the methodological approach used to examine the argument inLindsey, op. cit. reference 5D. Lindsey, Assessing precision in the manuscript review process: A little better than chance,Scientometrics, 14 (1988) 75.Hargens andHerting compute tests for statistical independence on a number of previously published data sets and report that “one can reject with great confidence the hypothesis that referee recommendations are statistically independent.” However, several of the data sets, even using their approach of collapsing the data along the diagonal, have expected cell frequencies of less than five. The data presented forLaw andSociety Review contains an expected cell frequency of zero.S.E. Fienberg,The Analysis of Cross-Classified Categorical Data, (2nd Ed.) Cambridge, MA, MIT Press, 1981, 142–143, has addressed this issue.Fienberg writes, “Many authors have concerned themselves with the analysis of contingency tables whose entries are missing, a priori zero, or otherwise predetermined. One way to treat such data is to remove these special cells from the model building and analysis process, after which we are left with a contingency table that is said to be structurally incomplete ... One of the most serious problems encountered in the application of incomplete contingency table methodology is that investigators who have data in the form of an incomplete contingency table often fail to recognize that fact. They either fill in the cells containing the fixed zeros using some “appropriate values,” or they collapse the data ... These practices can lead to inappropriate conclusions, general confusion, and bad science.” Also see,S.J. Haberman, Log-linear models and frequency tables with small expected cell counts,Annals of Statistics, 5 (1977) 1148.
Hargens andHerting, op. cit. reference 29 above, page 12. This paper is the source for the methodological approach used to examine the argument inLindsey, op. cit. reference 5D. Lindsey, Assessing precision in the manuscript review process: A little better than chance,Scientometrics, 14 (1988) 75.Hargens andHerting compute tests for statistical independence on a number of previously published data sets and report that “one can reject with great confidence the hypothesis that referee recommendations are statistically independent.” However, several of the data sets, even using their approach of collapsing the data along the diagonal, have expected cell frequencies of less than five. The data presented forLaw and Society Review contains an expected cell frequency of zero.S.E. Fienberg,The Analysis of Cross-Classified Categorical Data, (2nd Ed.) Cambridge, MA, MIT Press, 1981, 142–143, has addressed this issue.Fienberg writes, “Many authors have concerned themselves with the analysis of contingency tables whose entries are missing, a priori zero, or otherwise predetermined. One way to treat such data is to remove these special cells from the model building and analysis process, after which we are left with a contingency table that is said to be structurally incomplete ... One of the most serious problems encountered in the application of incomplete contingency table methodology is that investigators who have data in the form of an incomplete contingency table often fail to recognize that fact. They either fill in the cells containing the fixed zeros using some “appropriate values,” or they collapse the data ... These practices can lead to inappropriate conclussions, general confusion, and bad science.” Also see,S.J. Haberman, Log-linear models and frequency tables with small expected cell counts,Annals of Statistics, 5 (1977) 1148.
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Lindsey, D. Precision in the manuscript review process: Hargens and Herting revisited. Scientometrics 22, 313–325 (1991). https://doi.org/10.1007/BF02020004
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DOI: https://doi.org/10.1007/BF02020004