Spectacles of intimacy? Mapping the moral landscape of teenage social media

This paper explores young people's expressed concerns about privacy in the context of a highly mediated cultural environment, mapping social media practices against axes of visibility and participation. Drawing on interdisciplinary conceptual resources from both the humanities and social sciences, we use ‘spectacles of intimacy’ to conceptualise breaches of privacy, mapping an emergent moral landscape for young people that moves beyond concerns with e-safety to engage with the production and circulation of audiences and value. The paper draws on data from a methodological innovation project using multi-media and mixed methods to capture lived temporalities for children and young people. We present a model that captures a moral landscape shaped by emotional concerns about social media, the affordances of those media and affective discourses emerging from young people's use of the media.     

CAN THE PRESIDENT REALLY AFFECT ECONOMIC GROWTH? PRESIDENTIAL EFFORT AND THE POLITICAL BUSINESS CYCLE

Presidential elections are often seen as referendums on the health of the economy; however, little evidence exists on the president's ability to influence gross domestic product (GDP). This study examines the effect of the incentive to be reelected and the resulting increase in presidential effort on GDP growth. Growth is found to rise in reelection years for first‐term presidents after 1932 and to fall in election years before 1932, when reelection was uncommon, and for second‐term presidents generally. This effect is largest for high‐quality presidents—who probably have the highest return to effort—and is spread across multiple sectors of the economy. (JEL D78, D72, E32, J24)     

Population constraints on pooled surveys in demographic hazard modeling

In non-experimental research, data on the same population process may be collected simultaneously by more than one instrument. For example, in the present application, two sample surveys and a population birth registration system all collect observations on first births by age and year, while the two surveys additionally collect information on women’s education. To make maximum use of the three data sources, the survey data are pooled and the population data introduced as constraints in a logistic regression equation. Reductions in standard errors about the age and birth-cohort parameters of the regression equation in the order of three-quarters are obtained by introducing the population data as constraints. A halving of the standard errors about the education parameters is achieved by pooling observations from the larger survey dataset with those from the smaller survey. The percentage reduction in the standard errors through imposing population constraints is independent of the total survey sample size.     

Input-output evaluation of rural development: a forestry-centred application

The purpose of this paper is to analyse the role of forestry in the rural economy of Scotland. The Generation of Regional Input-Output Tables (GRIT) technique is applied to the estimation of input-output tables for rural Scotland. This is followed by a forestry-centred multiplier analysis. The results suggest that the forestry planting and harvesting sectors offer great potential for improving economic activity. However, their backward linkages with other rural industries seem to be limited. On the other hand, the backward linkages of wood-processing industries with the rest of the economy are strong. From this analysis, it is concluded that the joint development of forestry and wood-processing industries would promote economic development in rural Scotland.     

A hierarchical model for ordinal matrix factorization

This paper proposes a hierarchical probabilistic model for ordinal matrix factorization. Unlike previous approaches, we model the ordinal nature of the data and take a principled approach to incorporating priors for the hidden variables. Two algorithms are presented for inference, one based on Gibbs sampling and one based on variational Bayes. Importantly, these algorithms may be implemented in the factorization of very large matrices with missing entries.     

A theory of unanimous jury voting with an ambiguous likelihood

Theory and Decision - We examine collective decision-making in a jury voting game under the unanimity rule when voters have ambiguous beliefs. Unlike in existing studies (Ellis in Theoretical...