Deliberate Trust and Intuitive Faith: A Dual‐Process Model of Reliance

Drawing on the dual process framework from social and cognitive psychology, this paper reconciles two distinct conceptualizations of trust prevalent in the literature: “rational” calculative and irrational “affective” or normative. After critically reviewing previous attempts at reconciliation between these distinctions, we argue that the notion of trust as “reliance” is the higher order category of which “deliberate trust” and “intuitive faith” are subtypes. Our revised approach problematizes the conflation of epistemic uncertainty with phenomenological uncertainty while providing sound footing for a key sociological insight: that reliance on the routine social order is both the cognitive default and based on substantial practical evidence. We develop two broad suggestions for future research from these implications: (1) sociological research should examine the role of intuitive faith—as opposed to deliberate trust—in late modern societies, and (2) analysts should challenge the role of deliberate trust as the “modal” form of reliance in contemporary research.     

Implementation of Child Rights in the Children's Homes in Malaysia

The objective of this study was to examine the implementation of the Convention on the Rights of the Child (CRC) in the Children Homes under the Social Welfare Department (SWD) in Malaysia. Data was collected from 402 registered children who were staying in six Children Homes across the country. This study employed self‐report surveys where multiple data collection methods, such as face‐to‐face structured interviews, key informant interviews (KIIs), and documentation survey, were used. The study found that the SWD failed to comply with most of the commitments of CRC in Children Homes at its implementation level, and it is still needs based. The findings of this study present important guidelines for government and policy makers in improving child welfare services in the Children Homes in Malaysia.     

Meta-analysis using multilevel models with an application to the study of class size effects

Meta-analysis is formulated as a special case of a multilevel (hierarchical data) model in which the highest level is that of the study and the lowest level that of an observation on an individual respondent. Studies can be combined within a single model where the responses occur at different levels of the data hierarchy and efficient estimates are obtained. An example is given from studies of class sizes and achievement in schools, where study data are available at the aggregate level in terms of overall mean values for classes of different sizes, and also at the student level.     

Bayesian Dynamic Factor Models and Portfolio Allocation

We discuss the development of dynamic factor models for multivariate financial time series, and the incorporation of stochastic volatility components for latent factor processes. Bayesian inference and computation is developed and explored in a study of the dynamic factor structure of daily spot exchange rates for a selection of international currencies. The models are direct generalizations of univariate stochastic volatility models and represent specific varieties of models recently discussed in the growing multivariate stochastic volatility literature. We discuss model fitting based on retrospective data and sequential analysis for forward filtering and short-term forecasting. Analyses are compared with results from the much simpler method of dynamic variance-matrix discounting that, for over a decade, has been a standard approach in applied financial econometrics. We study these models in analysis, forecasting, and sequential portfolio allocation for a selected set of international exchange-rate-return time series. Our goals are to understand a range of modeling questions arising in using these factor models and to explore empirical performance in portfolio construction relative to discount approaches. We report on our experiences and conclude with comments about the practical utility of structured factor models and on future potential model extensions.     

Centering or not centering in multilevel models? The role of the group mean and the assessment of group effects

In multilevel regression, centering the model variables produces effects that are different and sometimes unexpected compared with those in traditional regression analysis. In this article, the main contributions in terms of meaning, assumptions, and effects underlying a multilevel centering solution are reviewed, emphasizing advantages and critiques of this approach. In addition, in the spirit of Manski, contextual and correlated effects in a multilevel framework are defined to detect group effects. It is shown that the decision of centering in a multilevel analysis depends on the way the variables are centered, on whether the model has been specified with or without cross-level terms and group means, and on the purposes of the specific analysis.     

Age,Health and Life Satisfaction Among Older Europeans

In this paper we investigate how age affects the self-reported level of life satisfaction among the elderly in Europe. By using a vignette approach, we find evidence that age influences life satisfaction through two counterbalancing channels. On the one hand, controlling for the effects of all other variables, the own perceived level of life satisfaction increases with age. On the other hand, given the same true level of life satisfaction, older respondents are more likely to rank themselves as “dissatisfied” with their life than younger individuals. Detrimental health conditions and physical limitations play a crucial role in explaining scale biases in the reporting style of older individuals.     

Limit theorems for intermediate and central order statistics under nonlinear normalization

In this paper the work of Pancheva (1984) for extreme order statistics under nonlinear normalization is extended to order statistics with variable ranks. Two new results are proved. The first is that under nonlinear normalization, the nondegenerate type (family of types) of the distribution functions with two finite growth points is a possible weak limit of any central order statistic with regular rank sequence. The second result is that the possible nondegenerate weak limits of any central order statistic with regular rank under the traditionally linear normalization and under the power normalization are the same. Finally, the class of all possible weak limits for lower and upper intermediate order statistics is derived under power normalization from the corresponding weak limits of extremes under power normalization.     

The Hysteresis Effect: Theorizing Mismatch in Action

Widespread reliance on representationalist understandings commit social scientists to either partially or totally decouple belief from reality, limiting the domain of phenomena that can be treated by belief as an analytic concept. Developing the contrastive notion of practical belief, we introduce the hysteresis effect as a situational phenomenon involving the systematic production of agent‐environment mismatches and argue for its placement as a central problem for the theory of action. Revealing the dynamic, embodied conservation of belief in the temporality of practice, hysteresis appears when environmental contexts change in a way that leaves actors without an ontologically complicit relationship to institutions as scaffolds of action. Under these circumstances, a past‐inflected reflexiveness replaces a forward‐inflecting practical belief in the actor's temporal relation to the world. Drawing from a variety of historical case studies, we locate hysteresis in routine disjunctures between the temporality of practice and the temporality of environments. Our analysis reveals four distinct types of reflexiveness produced the hysteresis effect, each with a unique dispositional impact on actors and extensions to group‐level phenomena. We conclude the article by emphasizing the non‐eliminativist relationship between belief as disposition and belief as representation.