John A. Stewart

Productivity Differences Among Scientists: Evidence for Accumulative Advantage

The highly skewed distributions of productivity among scientists can be partly explained by a process of accumulative advantage. Because offeedback through recognition and resources, highly productive scientists maintain or increase their productivity, while scientists who produce very little produce even less later on. A major implication of accumulative advantage is that the distribution of productivity becomes increasingly unequal as a cohort of scientists ages. Cross-sectional survey data support this hypothesis for chemists, physicists, and mathematicians, who show strong linear increases in inequality with increasing career age. This increase is highly associated with a changing distribution of time spent on research. Another implication of accumulative advantage is also corroborated: the association among productivity, resources and esteem increases as career age increases.

Interpretive Listening: An Alternative to Empathy.

In the immediately preceding essay, Ronald C. Arnett and Gordon Nakagawa critique the assumptive roots of empathie listening. This essay briefly summarizes their critique and outlines an alternative approach to listening which is grounded in the hermeneutic phenomenologies of Martin Heidegger, Hans‐Georg Gadamer, and Paul Ricoeur. Four themes—openness, linguisticality, play, and the fusion of horizons—are explicated as distinctive features of this alternative. Conceptual and pedagogical implications are also discussed.

Lotka's Law: A Problem in Its Interpretation and Application

Science, Big Science (1963) Derek de Solla Price wrote that ’the total number of scientists goes up as the square, more or less, of the number of good ones’, his text indicating that this quite provocative idea was consistent with a number of findings, including the empirical law named ’Lotka’s law’, after its discoverer.1 In August 1974, John Stewart and Paul Allison submitted to us a manuscript questioning the consistency of Price’s ’square root’ law with Lotka’s law. After this manuscript was referred to Price for comment, it emerged that Michael Moravcsik and Belver Griffith had also been concerned with this problem. Price’s reply to Stewart and Allison clearly indicated the plausibility of his earlier reasoning. Moravcsik and Griffith, working separately and in concert, explicated the differences between the Stewart and Allison and Price papers, and the assumptions underlying those differences. The present paper is intended to identify and explicate the problem for our readers, and to indicate areas of actual or

The Poisson-lognormal model for bibliometric/scientometric distributions

Abstract The Poisson-lognormal model assumes that the intensity parameter of a Poisson process has a lognormal distribution in a sample of observations. This model can yield highly skewed, discrete distributions, but must be estimated by numerical methods. When applied to many of the empirical data sets related to the ‘laws’ of Lotka, Bradford, and Zipf, this compound Poisson model produces good to excellent fits. Discussion includes possible ‘causal’ processes and some implications for future bibliometric and scientometric studies.

Rhetoritherapy revisited: A test of its effectiveness as a treatment for communication problems

The present study examined the effectiveness of rhetoritherapy (Phillips, 1986) as a treatment for individuals with communication difficulties, such as communication apprehension, reticence, and shyness. Following Glasers (1981) comments on problems in previous studies, the present study employed several standardized tests of social communication problems and used a pretest‐posttest design with a control group and two treatment groups: one was identical to the rhetoritherapy program developed at Penn State University and the other was a speech communication class. Participants in all three groups completed the PRCA‐24, the McCroskey, Andersen, Richmond, and Wheeless Shy Scale, and the Jones and Russell Social Reticence Scale (SRS) during the first and last weeks of the semester. In addition, participants had a friend complete the Shy and SRS measures about them at both points in time. Dummy variable regression analyses were used to identify significant differences between the three groups in their relati...