Maternal depression and children's adjustment problems : the role of mothers' affective reactivity

textMothers with depressive symptoms often express more negative emotions than other mothers, react more punitively, and express more frustration (e.g., Belsky, 1984). Paradoxically, mothers with depressive symptoms are also often found to be less, not more, reactive and to express flat rather than negative affect. These mothers are often described as emotionally "flat", unresponsive, and withdrawn (Kochanska, Kuczynski, Radke-Yarrow, & Welsh, 1987). Mothers' depressive symptoms are also associated with problematic parenting, interfering with children's social development (e.g., Goodman et al., 2011). This study investigated the possibility that mothers with depressive symptoms regulate their affect as a coping strategy to minimize distress when facing aversive child behaviors. Using observational and reported longitudinal data from 319 mother-child dyads, we examined how mothers' affective reactivity changes as a function of (a) changes in mothers' depressive symptoms, and (b) changes in children’s aversiveness during the course of the mother-child interaction. Depressive symptoms were associated with mothers' under-reactivity to low aversive child behaviors. Depressive symptoms also predicted rapid increases in mothers' negative reactivity as children's aversiveness increased, and negative over-reactivity to highly aversive child behaviors. Mothers' affective under-reactivity, over-reactivity, and depressive symptoms were all associated with children's adjustment problems over a two-year period. Results suggest that when aversive child behaviors are minimally disturbing, mothers with depressive symptoms minimize child rearing strain by not reacting; when aversive child behaviors are highly disturbing, they do so by resisting and controlling the child. Findings may enable us to understand adaptations that undermine parenting and place children at risk.Human Development and Family Science

Applied Evaluative Informetrics: Part 1

This manuscript is a preprint version of Part 1 (General Introduction and Synopsis) of the book Applied Evaluative Informetrics, to be published by Springer in the summer of 2017. This book presents an introduction to the field of applied evaluative informetrics, and is written for interested scholars and students from all domains of science and scholarship. It sketches the field's history, recent achievements, and its potential and limits. It explains the notion of multi-dimensional research performance, and discusses the pros and cons of 28 citation-, patent-, reputation- and altmetrics-based indicators. In addition, it presents quantitative research assessment as an evaluation science, and focuses on the role of extra-informetric factors in the development of indicators, and on the policy context of their application. It also discusses the way forward, both for users and for developers of informetric tools.Comment: The posted version is a preprint (author copy) of Part 1 (General Introduction and Synopsis) of a book entitled Applied Evaluative Bibliometrics, to be published by Springer in the summer of 201

Positional Effects on Citation and Readership in arXiv

arXiv.org mediates contact with the literature for entire scholarly communities, both through provision of archival access and through daily email and web announcements of new materials, potentially many screenlengths long. We confirm and extend a surprising correlation between article position in these initial announcements, ordered by submission time, and later citation impact, due primarily to intentional "self-promotion" on the part of authors. A pure "visibility" effect was also present: the subset of articles accidentally in early positions fared measurably better in the long-term citation record than those lower down. Astrophysics articles announced in position 1, for example, overall received a median number of citations 83\% higher, while those there accidentally had a 44\% visibility boost. For two large subcommunities of theoretical high energy physics, hep-th and hep-ph articles announced in position 1 had median numbers of citations 50\% and 100\% larger than for positions 5--15, and the subsets there accidentally had visibility boosts of 38\% and 71\%. We also consider the positional effects on early readership. The median numbers of early full text downloads for astro-ph, hep-th, and hep-ph articles announced in position 1 were 82\%, 61\%, and 58\% higher than for lower positions, respectively, and those there accidentally had medians visibility-boosted by 53\%, 44\%, and 46\%. Finally, we correlate a variety of readership features with long-term citations, using machine learning methods, thereby extending previous results on the predictive power of early readership in a broader context. We conclude with some observations on impact metrics and dangers of recommender mechanisms.Comment: 28 pages, to appear in JASIS

Trends in Russian research output indexed in Scopus and Web of Science

Trends are analysed in the annual number of documents published by Russian institutions and indexed in Scopus and Web of Science, giving special attention to the time period starting in the year 2013 in which the Project 5-100 was launched by the Russian Government. Numbers are broken down by document type, publication language, type of source, research discipline, country and source. It is concluded that Russian publication counts strongly depend upon the database used, and upon changes in database coverage, and that one should be cautious when using indicators derived from WoS, and especially from Scopus, as tools in the measurement of research performance and international orientation of the Russian science system.Comment: Author copy of a manuscript accepted for publication in the journal Scientometrics, May 201

A Boltzmann machine for the organization of intelligent machines

In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved to converge to the minimum of a cost function. Finally, simulations will show the effectiveness of a variety of search techniques for the intelligent machine