491 research outputs found

    A functional-cognitive framework for attitude research

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    In attitude research, behaviours are often used as proxies for attitudes and attitudinal processes. This practice is problematic because it conflates the behaviours that need to be explained (explanandum) with the mental constructs that are used to explain these behaviours (explanans). In the current chapter we propose a meta-theoretical framework that resolves this problem by distinguishing between two levels of analysis. According to the proposed framework, attitude research can be conceptualised as the scientific study of evaluation. Evaluation is defined not in terms of mental constructs but in terms of elements in the environment, more specifically, as the effect of stimuli on evaluative responses. From this perspective, attitude research provides answers to two questions: (1) Which elements in the environment moderate evaluation? (2) What mental processes and representations mediate evaluation? Research on the first question provides explanations of evaluative responses in terms of elements in the environment (functional level of analysis); research on the second question offers explanations of evaluation in terms of mental processes and representations (cognitive level of analysis). These two levels of analysis are mutually supportive, in that better explanations at one level lead to better explanations at the other level. However, their mutually supportive relation requires a clear distinction between the concepts of their explanans and explanandum, which are conflated if behaviours are treated as proxies for mental constructs. The value of this functional-cognitive framework is illustrated by applying it to four central questions of attitude research

    Explicit and implicit determinants of fair-trade buying behavior

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    We examined the usefulness of an implicit attitude measure (IAT) to explain the weak attitude-behavior relationships often found in research about ethical consumer behavior. The results indicated that the IAT effects for buyers and non-buyers of Fair Trade products were significantly different, showing that the IAT can be used to differentiate between buyers and non-buyers. Further, the authors conclude that the IAT has unique predictive validity and that most importantly implicit attitudes need to be enhanced to raise ethical consumer behavior

    Generalization versus contextualization in automatic evaluation revisited: a meta-analysis of successful and failed replications

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    To account for disparate findings in the literature on automatic evaluation, Gawronski, Rydell, Vervliet, and De Houwer (2010) proposed a representational theory that specifies the contextual conditions under which automatic evaluations reflect initially acquired attitudinal information or subsequently acquired counterattitudinal information. The theory predicts that automatic evaluations should reflect the valence of expectancy-violating counterattitudinal information only in the context in which this information had been learned. In contrast, automatic evaluations should reflect the valence of initial attitudinal information in any other context, be it the context in which the initial attitudinal information had been acquired (ABA renewal) or a novel context in which the target object had not been encountered before (ABC renewal). The current article presents a meta-analysis of all published and unpublished studies from the authors' research groups regardless of whether they produced the predicted pattern of results. Results revealed average effect sizes of d = 0.249 for ABA renewal (30 studies, N = 3,142) and d = 0.174 for ABC renewal (27 studies, N = 2,930), both of which were significantly different from zero. Effect sizes were moderated by attention to context during learning, order of positive and negative information, context-valence contingencies during learning, and sample country. Although some of the obtained moderator effects are consistent with the representational theory, others require theoretical refinements and future research to gain deeper insights into the mechanisms underlying contextual renewal

    Age of second language acquisition affects nonverbal conflict processing in children : an fMRI study

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    Background: In their daily communication, bilinguals switch between two languages, a process that involves the selection of a target language and minimization of interference from a nontarget language. Previous studies have uncovered the neural structure in bilinguals and the activation patterns associated with performing verbal conflict tasks. One question that remains, however is whether this extra verbal switching affects brain function during nonverbal conflict tasks. Methods: In this study, we have used fMRI to investigate the impact of bilingualism in children performing two nonverbal tasks involving stimulus-stimulus and stimulus-response conflicts. Three groups of 8-11-year-old children - bilinguals from birth (2L1), second language learners (L2L), and a control group of monolinguals (1L1) - were scanned while performing a color Simon and a numerical Stroop task. Reaction times and accuracy were logged. Results: Compared to monolingual controls, bilingual children showed higher behavioral congruency effect of these tasks, which is matched by the recruitment of brain regions that are generally used in general cognitive control, language processing or to solve language conflict situations in bilinguals (caudate nucleus, posterior cingulate gyrus, STG, precuneus). Further, the activation of these areas was found to be higher in 2L1 compared to L2L. Conclusion: The coupling of longer reaction times to the recruitment of extra language-related brain areas supports the hypothesis that when dealing with language conflicts the specialization of bilinguals hampers the way they can process with nonverbal conflicts, at least at early stages in life

    Feature- versus rule-based generalization in rats, pigeons and humans

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    Humans can spontaneously create rules that allow them to efficiently generalize what they have learned to novel situations. An enduring question is whether rule-based generalization is uniquely human or whether other animals can also abstract rules and apply them to novel situations. In recent years, there have been a number of high-profile claims that animals such as rats can learn rules. Most of those claims are quite weak because it is possible to demonstrate that simple associative systems (which do not learn rules) can account for the behavior in those tasks. Using a procedure that allows us to clearly distinguish feature-based from rule-based generalization (the Shanks-Darby procedure), we demonstrate that adult humans show rule-based generalization in this task, while generalization in rats and pigeons was based on featural overlap between stimuli. In brief, when learning that a stimulus made of two components ("AB") predicts a different outcome than its elements ("A" and "B"), people spontaneously abstract an opposites rule and apply it to new stimuli (e.g., knowing that "C" and "D" predict one outcome, they will predict that "CD" predicts the opposite outcome). Rats and pigeons show the reverse behavior-they generalize what they have learned, but on the basis of similarity (e.g., "CD" is similar to "C" and "D", so the same outcome is predicted for the compound stimulus as for the components). Genuinely rule-based behavior is observed in humans, but not in rats and pigeons, in the current procedure
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