Richard W. Brislin

Bio: Richard W. Brislin is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Illusion & Ponzo illusion. The author has an hindex of 12, co-authored 16 publications receiving 12383 citations.

Back-Translation for Cross-Cultural Research

Abstract: Two aspects of translation were investigated: (1) factors that affect translation quality, and (2) how equivalence between source and target versions can be evaluated. The variables of language, content, and difficulty were studied through an analysis of variance design. Ninety-four bilinguals from the University of Guam, representing ten languages, translated or back-translated six essays incorporating three content areas and two levels of difficulty. The five criteria for equivalence were based on comparisons of meaning or predictions of similar responses to original or translated versions. The factors of content, difficulty, language and content-language interaction were significant, and the five equivalence criteria proved workable. Conclusions are that translation quality can be predicted, and that a functionally equivalent translation can be demonstrated when responses to the original and target versions are studied.

Comparative Research Methodology: Cross-Cultural Studies

Abstract: Cross-cultural research can make contributions to theory development by identifying groups of people who seem not to behave according to established theories and by increasing the range of independent variables available for study in any one culture. A major methodological orientation to such studies, developed over the last 10 years, is the emic-etic distinction. An emic analysis documents valid principles that describe behavior in any one culture, taking into account what the people themselves value as meaningful and important. The goal of an etic analysis is to make generalizations across cultures that take into account all human behavior. Examples of these approaches are given from studies on ingroup-outgroup relations in Greece and the United States; and studies on the need for achievement and its relation to the need for affiliation. A specific method to document emic and etic principles is presented which involves the development of core items to measure concerns in all cultures under stud...

Cross-Cultural Research in Psychology

Abstract: INTRODUCTION 363 DEFINITIONS OF CULTURE 367 THE USES AND BENEFITS OF CROSS-CULTURAL RESEARCH 368 THE MUTUAL ENRICHMENT OF CROSS-CULTURAL AND GENERAL PSYCHOLOGY 375 USING CONCEPTS FROM GENERAL PSYCHOLOGY: FACILITATORS OR BLINDERS? 380 EMICS AND ETICS: CULTURE-SPECIFIC AND CULTURE-GENERAL CONCEPTS 382 UNIVERSALS 386 WHAT PROBLEMS WILL CROSS-CULTURAL RESEARCH ALWAYS HAVE? 390 FUTURE NEEDS 391 CONCLUSIONS 392

Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks

Abstract: Image-to-image translation is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image using a training set of aligned image pairs. However, for many tasks, paired training data will not be available. We present an approach for learning to translate an image from a source domain X to a target domain Y in the absence of paired examples. Our goal is to learn a mapping G : X → Y such that the distribution of images from G(X) is indistinguishable from the distribution Y using an adversarial loss. Because this mapping is highly under-constrained, we couple it with an inverse mapping F : Y → X and introduce a cycle consistency loss to push F(G(X)) ≈ X (and vice versa). Qualitative results are presented on several tasks where paired training data does not exist, including collection style transfer, object transfiguration, season transfer, photo enhancement, etc. Quantitative comparisons against several prior methods demonstrate the superiority of our approach.

Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology

Abstract: This paper extends the unified theory of acceptance and use of technology (UTAUT) to study acceptance and use of technology in a consumer context. Our proposed UTAUT2 incorporates three constructs into UTAUT: hedonic motivation, price value, and habit. Individual differences--namely, age, gender, and experience--are hypothesized to moderate the effects of these constructs on behavioral intention and technology use. Results from a two-stage online survey, with technology use data collected four months after the first survey, of 1,512 mobile Internet consumers supported our model. Compared to UTAUT, the extensions proposed in UTAUT2 produced a substantial improvement in the variance explained in behavioral intention (56 percent to 74 percent) and technology use (40 percent to 52 percent). The theoretical and managerial implications of these results are discussed.

Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology

Abstract: This paper extends the unified theory of acceptance and use of technology (UTAUT) to study acceptance and use of technology in a consumer context. Our proposed UTAUT2 incorporates three constructs into UTAUT: hedonic motivation, price value, and habit. Individual differences — namely, age, gender, and experience — are hypothesized to moderate the effects of these constructs on behavioral intention and technology use. Results from a two-stage online survey, with technology use data collected four months after the first survey, of 1,512 mobile Internet consumers supported our model. Compared to UTAUT, the extensions proposed in UTAUT2 produced a substantial improvement in the variance explained in behavioral intention (56 percent to 74 percent) and technology use (40 percent to 52 percent). The theoretical and managerial implications of these results are discussed.

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

Abstract: Image-to-image translation is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image using a training set of aligned image pairs. However, for many tasks, paired training data will not be available. We present an approach for learning to translate an image from a source domain $X$ to a target domain $Y$ in the absence of paired examples. Our goal is to learn a mapping $G: X \rightarrow Y$ such that the distribution of images from $G(X)$ is indistinguishable from the distribution $Y$ using an adversarial loss. Because this mapping is highly under-constrained, we couple it with an inverse mapping $F: Y \rightarrow X$ and introduce a cycle consistency loss to push $F(G(X)) \approx X$ (and vice versa). Qualitative results are presented on several tasks where paired training data does not exist, including collection style transfer, object transfiguration, season transfer, photo enhancement, etc. Quantitative comparisons against several prior methods demonstrate the superiority of our approach.