Improving attitude-behavior correspondence through exposure to normative support from a salient ingroup

Two experiments were conducted to test predictions derived from social identity/self-categorization theory concerning the role of group norms in attitude-behavior consistency. In Experiment 1, 160 students who could be classified as having a more or less certain target attitude were exposed to attitude congruent versus incongruent normative support from a relevant reference group (own university) under conditions of low versus high group salience. Experiment 2 was very similar in design and methodology (N=180), but a different correlate of attitude accessibility was used (an experimental manipulation of repeated expression), the target attitude was changed, and the reference group was gender. Across the 2 experiments there was consistent support for the hypothesis that participants would behave more in accordance with their attitudes when they received normative support for, rather than opposition to, their original attitude from a relevant reference group (i.e., their ingroup, not an outgroup). There was slightly weaker support for the second hypothesis that this effect would be stronger under high-than low-salience conditions. The third hypothesis (see Fazio, 1986), that attitude certainty and repeated expression of the attitude would strengthen attitude-behavior consistency, was well supported, as was the expectation that accessibility effects would be independent of reference group norm effects on attitude-behavior consistency.

Input-driven Language Learning

Input-driven models provide an explicit and readily testable account of language learning. Although we share Ellis's view that the statistical structure of the linguistic environment is a crucial and, until recently, relatively neglected variable in language learning, we also recognize that the approach makes three assumptions about cognition and language learning that are not universally shared. The three assumptions concern (a) the language learner as an intuitive statistician, (b) the constraints on what constitute relevant surface cues, and (c) the redescription problem faced by any system that seeks to derive abstract grammatical relations from the frequency of co-occurring surface forms and functions. These are significant assumptions that must be established if input-driven models are to gain wider acceptance. We comment on these issues and briefly describe a distributed, instance-based approach that retains the key features of the input-driven account advocated by Ellis but that also addresses shortcomings of the current approaches.

La traduction de la terminologie philosophique

After examining certain general characteristics of philosophical terminology which are important for the translation of the terms, the author studies the translation of philosophical lexis in a corpus of texts, highlighting the difference in treatment of technical terms and general lexis. A more detailed study of the corpus reveals complexities beyond that binary dichotomy. The author then aims to produce explanations for the translational practice which have been adduced. This necessitates exploring the social context in which the translated terms circulate.