Personality judgments from everyday images of faces

The author(s) disclosed receipt of the following financial support for the research and/or authorship of this article: an ESRC studentship [ES/I900748/1] and postdoctoral research support from the Australian Research Council Centre of Excellence in Cognition and its Disorders, University of Western Australia (CE110001021), to the first author. The work was completed while the first author was at the University of York, UK. We thank Richard Vernon for calculating the attributes used in Study 2.Peer reviewedPublisher PD

Ownership and Control: A Small-World Analysis

In this paper we investigate the ownership and control of British firms using recent techniques from computational graph theory. In particular, we analyze the `small-world' properties of UK company ownership and the corporate elite. A `small-world' is characterized by short `path-lengths' (actors are linked by a short chain of acquaintances) and high `clustering' (one's friends tend to be friends in their own right). We find that the network of both ownership and control can be characterized as a small-world. We simulate a set of corporate worlds using newly introduced random-graph models of Chung and Lu. In general, we reject the hypothesis that the corporate world of ownership and control is generated by a random graph model. The network structure of ownership and boards is decidedly more `clubby' than would be expected by chance, suggesting the presence of additional social structure not captured by the random graph model. In addition, we find that financial institutions are important and give rise to different network topologies

Probabilistic estimates of transient climate sensitivity subject to uncertainty in forcing and natural variability

In this paper, the authors address the impact of uncertainty on estimates of transient climate sensitivity (TCS) of the globally averaged surface temperature, including both uncertainty in past forcing and internal variability in the climate record. This study provides a range of probabilistic estimates of the TCS that combine these two sources of uncertainty for various underlying assumptions about the nature of the uncertainty. The authors also provide estimates of how quickly the uncertainty in the TCS may be expected to diminish in the future as additional observations become available. These estimates are made using a nonlinear Kalman filter coupled to a stochastic, global energy balance model, using the filter and observations to constrain the model parameters. This study verifies that model and filter are able to emulate the evolution of a comprehensive, state-of-the-art atmosphere–ocean general circulation model and to accurately predict the TCS of the model, and then apply the methodology to observed temperature and forcing records of the twentieth century. For uncertainty assumptions best supported by global surface temperature data up to the present time, this paper finds a most likely present-day estimate of the transient climate sensitivity to be 1.6 K, with 90% confidence the response will fall between 1.3 and 2.6 K, and it is estimated that this interval may be 45 % smalle