Civil Society Actors as Catalysts for Transnational Social Learning

This paper explores the roles of transnational civil society organizations and networks in transnational social learning. It begins with an investigation into social learning within problem domains and into the ways in which such domain learning builds perspectives and capacities for effective action among domain organizations and institutions. It suggests that domain learning involves problem definition, direction setting, implementation of collective action, and performance monitoring. Transnational civil society actors appear to take five roles in domain learning: (1) identifying issues, (2) facilitating voice of marginalized stakeholders, (3) amplifying the importance of issues, (4) building bridges among diverse stakeholders, and (5) monitoring and assessing solutions. The paper then explores the circumstances in which transnational civil society actors can be expected to make special contributions in important problem domains in the future.     

The Strength of Strong and Weak Ties

Strong civil societies, composed of diverse community groups and nongovernmental organizations, are increasingly seen as neccessary for robust economic growth and effective democratic governance. Yet financial and other resources for civil society organizations typically are scarce.     

CONVERSATIONS WITH EDWIN J.G. PITMAN

Edwin Pitman was born on 29th October, 1897, in Melbourne, Victoria. He was Professor of Mathematics at the University of Tasmania from 1926 until his retirement in 1962. His publications on distribution-free methods in Statistics established a sound basis for the development of these methods. His theoretical papers gave a sound mathematical treatment of the concepts of intrinsic accuracy and sufficiency, and a definitive treatment of estimation problems for location and scale parameters. The concept of asymptotic relative efficiency is due to him. He was elected a Fellow of the Australian Academy of Science (FAA) in 1954, a Fellow of the Institute of Mathematical Statistics in 1948, President of the Australian Mathematical Society in 1958 and 1959, and Vice-President of the International Statistical Institute in 1960. He was elected an Honorary Life Member of the Statistical Society of Australia in 1966, an Honorary Fellow of the Royal Statistical Society in 1965, and an Honorary Life Member of the Australian Mathematical Society in 1968.
In 1977, in honour of his eightieth birthday, the University of Tasmania conferred on him an Honorary Doctorate of Science, and the Statistical Society of Australia instituted the Pitman Medal (1979), to be awarded to a member of the Society for high distinction in Statistics.
The conversations recorded here took place in May, 1991, at Pitman's home in Hobart, Tasmania.     

A latent Gaussian Markov random-field model for spatiotemporal rainfall disaggregation

Summary. Rainfall data are often collected at coarser spatial scales than required for input into hydrology and agricultural models. We therefore describe a spatiotemporal model which allows multiple imputation of rainfall at fine spatial resolutions, with a realistic dependence structure in both space and time and with the total rainfall at the coarse scale consistent with that observed. The method involves the transformation of the fine scale rainfall to a thresholded Gaussian process which we model as a Gaussian Markov random field. Gibbs sampling is then used to generate realizations of rainfall efficiently at the fine scale. Results compare favourably with previous, less elegant methods.     

THREE-WAY STRATIFICATION SAMPLING DESIGN WHEN ONE OF THE STRATIFYING VARIABLES IS TIME

Bryant, Hartley & Jessen (1960) presented a two‐way stratification sampling design when the sample size n is less than the number of strata. Their design was extended to a three‐way stratification case by Chaudhary & Kumar (1988) , but this design does not take into account serial correlation, which might be present as a result of the presence of a time variable. In this paper, a new sampling procedure is presented for three‐way stratification when one of the stratifying variables is time. The purpose of such a design is to take into account serial correlation. The variance of the unweighted estimator of the population mean with respect to a super population model is used as the basis for comparison. Simulation results show that the suggested design is more efficient than the Chaudhary & Kumar (1988) design.     

Prenatal Maternal Anxiety and Depression Predict Negative Behavioral Reactivity in Infancy

The effects of maternal antenatal and postnatal anxiety and depression on infant negative behavioral reactivity were examined in a sample of 22 mother‐infant pairs. Maternal anxiety and depression were assessed by standardized measures during the third trimester of pregnancy and postpartum. Infant negative behavioral responses to novelty were assessed using a previously validated measure at 4 months of age. Maternal anxiety and depression during the prenatal, but not the postnatal period, were related to infant negative behavioral reactivity to novelty. These data illustrate that prenatal maternal psychological state can exert persisting influences on human infant behavior.