Vocal signs of confidence

This study examined whether two paralinguistic variables, vocal loudness and response latency, were associated with confidence in answers to trivia questions. Audience presence and size were manipulated and subjects' assertiveness was measured. Subjects verbally responded to trivia questions by indicating their choice and how confident they were in each answer. Tapes of these responses were later analyzed for latency of response and loudness of speech. As expected, the more confident individuals were in their answers, the faster and louder they responded. Assertive subjects spoke louder. The presence of an audience had no effects on vocal responding. Apparently, the confidence of a speaker can be inferred from the speed and loudness of the speaker's responses.This study was a Master's thesis project conducted by the second author under the supervision of the first author.     

A Comparative Approach to Evaluating Individual Planning for People with Learning Disabilities: challenging the assumptions

Individual planning in services for people with learning disabilities is used on the assumption that it encourages service users across a range of abilities to make important decisions about their lives. Although recent studies have questioned the value and effectiveness of such processes, the principles underlying the practice of individual planning are rarely challenged. This paper considers important aspects of individual planning in London, comparing a system based on the principles of normalisation with a situation-specific, family-orientated system operating in Milan, Italy. Key factors such as the role of professionals and the involvement of service users are considered with the aims of the process. The intention of the paper is to stimulate debate in an area of practice by questioning its assumptions.     

Global Responses to the COVID-19 Pandemic

Public Organization Review -     

Universal versus contextual effects on TQM: a triangulation study using neural networks

The objective of this study is to extend previous research on total quality management (TQM)-context-performance relationships and ‘fit’ using multiple methods. We combine artificial neural networks (ANNs) with structural equation modelling (SEM) to analyse several hypotheses and propositions. This is the first study in this area of research that utilises ANNs and a triangulation technique in the presence of several contextual factors. The SEM analyses suggest that company size and industry type may have contingency effects on some of the TQM practices and/or TQM-performance relationships. However, the ANN models have shown that these two contingency factors do not moderate TQM outcomes, implying that all organisations can benefit from TQM regardless of size and type. As well, these models show that formal TQM implementation and/or ISO certifications do not add any predictive power to the ANN models except in one case: TQM implementation and/or ISO certification added to organisational effectiveness and customer results to predict financial and market (F&M) results. The results further indicate that even though implementing TQM alone has a bigger impact on F&M results than obtaining ISO certification alone, combining the two will have an even greater impact on these results. Joint implementation leads to greater improvements in organisational effectiveness, which, in turn, has a positive effect on customer results and consequently F&M results. This is a unique finding within the context of moderator effects on TQM-performance relationships.     

What Drives Citizen Participation in Political Gatherings in Modern South Africa? A Quantitative Analysis of Self-Reported Behaviour

Social Indicators Research - Community and public gatherings are an important component of political participation in sub-Saharan Africa. Formal and informal community meetings and rallies are...     

Deriving Behavior Model Parameters from Survey Data: Self‐Protective Behavior Adoption During the 2009–2010 Influenza A(H1N1) Pandemic

In this paper, we demonstrate how public opinion surveys can be designed to collect information pertinent to computational behavior modeling, and we present the results of a public opinion and behavior survey conducted during the 2009–2010 H1N1 influenza pandemic. The results are used to parameterize the Health Belief Model of individual health‐protective decision making. Survey subjects were asked questions about their perceptions of the then‐circulating influenza and attitudes towards two personal protective behaviors: vaccination and avoidance of crowds. We empirically address two important issues in applying the Health Belief Model of behavior to computational infectious disease simulation: (1) the factors dynamically influencing the states of the Health Belief Model variables and (2) the appropriateness of the Health Belief Model in describing self‐protective behavior in the context of pandemic influenza.