Expanding the boundaries of evaluative learning research: how intersecting regularities shape our likes and dislikes

Over the last 30 years, researchers have identified several types of procedures through which novel preferences may be formed and existing ones altered. For instance, regularities in the presence of a single stimulus (as in the case of mere exposure) or 2 or more stimuli (as in the case of evaluative conditioning) have been shown to influence liking. We propose that intersections between regularities represent a previously unrecognized class of procedures for changing liking. Across 4 related studies, we found strong support for the hypothesis that when environmental regularities intersect with one another (i.e., share elements or have elements that share relations with other elements), the evaluative properties of the elements of those regularities can change. These changes in liking were observed across a range of stimuli and procedures and were evident when self-report measures, implicit measures, and behavioral choice measures of liking were employed. Functional and mental explanations of this phenomenon are offered followed by a discussion of how this new type of evaluative learning effect can accelerate theoretical, methodological, and empirical development in attitude research

On the assumptions that we make about the world around us : a conceptual framework for feature transformation effects

Various phenomena such as halo effects, spontaneous trait inferences, and evaluative conditioning have in common that assumptions about object features (e.g., whether a person is intelligent or likeable) are influenced by other object features (e.g., whether that person is attractive or co-occurs with other liked persons). Surprisingly, these phenomena have rarely been related to each other, most likely because different phenomena are described using different terms. To overcome this barrier, we put forward a conceptual framework that can be used to describe a wide range of these phenomena. After introducing the four core concepts of the framework, we illustrate how it can be applied to various phenomena. Doing so helps to reveal similarities and differences between those phenomena, thus improving communication and promoting interactions between different areas of research. Finally, we illustrate the generative power of the framework by discussing some of the new research questions that it highlights

Which is the More Predictable Gender? Public Good Contribution and Personality

Personality questionnaires have been used and can be used to predict behavior in economic settings. Using two sets of state-of-the-art measures from personality psychology (the Big Six) and social psychology (Social Value Orientation), we find that the behavior of men is predictable in the first half of a public good contribution experiment, whereas that of women is not. This result agrees with the reinterpretation of Carol Gilligan's (1982) view that women are more sensitive to the context in which decisions are made. --gender,context,personality,public goods

At what sample size do correlations stabilize?

Sample correlations converge to the population value with increasing sample size, but the estimates are often inaccurate in small samples. In this report we use Monte-Carlo simulations to determine the critical sample size from which on the magnitude of a correlation can be expected to be stable. The necessary sample size to achieve stable estimates for correlations depends on the effect size, the width of the corridor of stability (i.e., a corridor around the true value where deviations are tolerated), and the requested confidence that the trajectory does not leave this corridor any more. Results indicate that in typical scenarios the sample size should approach 250 for stable estimates

A functional perspective on personality

Personality psychology has made enormous progresses over the years by accumulating empirical evidence on how patterns of stable individual differences in behaviours can be clustered systematically at different levels of abstraction (i.e. traits and facets) and how they can predict important consequential outcomes. At the same time, functionally orientated researchers have accumulated a vast body of knowledge on environment-behaviour relations and the underlying behavioural principles, that is, abstract descriptions of the way in which behaviour is a function of elements in the past and present environment. We explore a functional perspective on personality that attempts to bridge the two domains and to exploit the best of both worlds. From this functional perspective, personality refers to the impact of the individual on different types of environment-behaviour relations as well as on the way other factors moderate those relations. We discuss the potential of this functional perspective on personality to organise existing scientific knowledge and inspire future research

The gatekeeper: individual differences are key in the chain from perception to behaviour

A basic assumption in mainstream social cognition is that the path from perception to behaviour is often automatic and direct, as supported for example by several experimental studies showing that priming can lead directly to a congruent behaviour without any need of conscious awareness of the process. However, we argue that the priming of a goal or an object activates individual differences in automatic evaluations at the associative level that in turn are the key predictors of action (gatekeeper model). A study (n = 90) on the American stereotype is presented to support the model. The results show that individual differences of the American stereotype as assessed with the IAT predicts a relevant action (essay evaluation) but only under condition of priming. Broader implications for predictive validity of implicit measures are also discussed

Agrochemical Contamination of Honey and Bee Bread Collected in the Piedmont Region, Italy

This study shows the results of a local biomonitoring plan developed by a regional beekeeping association, Aspromiele, in several areas of Piedmont (Italy), in order to understand the status of contamination from pesticides present in the environment and eventually to evaluate their impact on apiculture. Glyphosate was the most abundant chemical found in the bee bread and honey samples. The other pesticides detected at lower concentrations and minor frequency were mandipropamid, tau-fluvalinate, metalaxil and spiroxamine. Even if in the present study the pesticides found in the bee bread and honey were limited to a few molecules, it is important to highlight that the presence of glyphosate could represent a hazard to bees. Honeybees are the main pollinators in agricultural ecosystems, and thus appropriate environmental management could lead to a reduction in the impact of these chemicals on bees and other beneficial insects

A Practical Primer To Power Analysis for Simple Experimental Designs

Power analysis is an important tool to use when planning studies. This contribution aims to remind readers what power analysis is, emphasize why it matters, and articulate when and how it should be used. The focus is on applications of power analysis for experimental designs often encountered in psychology, starting from simple two-group independent and paired groups and moving to one-way analysis of variance, factorial designs, contrast analysis, trend analysis, regression analysis, analysis of covariance, and mediation analysis. Special attention is given to the application of power analysis to moderation designs, considering both dichotomous and continuous predictors and moderators. Illustrative practical examples based on G*Power and R packages are provided throughout the article. Annotated code for the examples with R and dedicated computational tools are made freely available at a dedicated web page (https://github.com/mcfanda/primerPowerIRSP). Applications of power analysis for more complex designs are briefly mentioned, and some important general issues related to power analysis are discussed

R+EVUE THE B-SIDE

Visible from only one perspective at a time, architecture suffers the fate of never revealing itself as a whole. An inherent duplicity arises between what can be seen and what remains hidden. The back side—which never shows a representative face nor welcomes us into the building and rarely gets printed in glossy architecture magazines—is the overlooked side of architecture. As a result, we studied the backs of a few famous buildings. What we found is the B-side of architecture. Liberated from the front’s representative obligations, the B-side is an ambiguous space of programmatic, representative, contextual or even ideological experimentation. We represent our discoveries through a series of analytical and experimental drawings