and porous borders

of conceptual tools that are directly useful in guiding the implementation and evaluation of work redesign projects. In the paragraphs to follow, we examine several existing theoretical approaches to work redesign, with a special eye toward the measurability of the concepts employed and the action implications

This paper considers the complex relationships between the human and ecological elements of sustainability that exist in the minds of stakeholders and argues that a sensemaking approach allows these to be better understood and compared. This is supported by the results of a study, set in a fi nancial institution, exploring the relationships between these non-fi nancial elements of corporate sustainability. The viewpoints of middle management, branch and contact centre employees, executives, a community consultative council, suppliers and a community partner of a large Australian bank obtained in in-depth interviews are analysed and compared utilizing an innovative methodology of semantic analysis. We fi nd that these stakeholders ’ perceptions of the human–ecological relationship differ by group, containing different mixes of trade-offs and synergies between the non-fi nancial elements of corporate sustainability. Copyright © 2010 John Wiley & Sons, Ltd and ERP

B A C K G R O U N D : For the past few decades, nursing has struggled dramatically to reach scientific status. Theories were "borrowed" from the social sciences, or were developed specifically for nursing. However there is a lot of ambiguity about the whole effort as issues of definition

The effects of prior semantic context upon lexical access during sentence comprehension were examined in two experiments. In both studies, subjects comprehended auditorily presented sentences containing lexical ambiguities and simultaneously performed a lexical decision task upon visually presented

In this paper we consider the duality between process and concept in mathematics, in particular using the same symbolism to represent both a process (such as the addition of two numbers 3+2) and the product of that process (the sum 3+2). The ambiguity of notation allows the successful thinker

in positive. We apply the Multiple-Instance learning framework to the problem of learning how to classify natural images. Images are inherently ambiguous since they can represent many different things. A user labels an image as positive if the image somehow contains the concept. Each image is a bag

Cross-document coreference occurs when the same person, place, event, or concept is discussed in more than one text source. Computer recognition of this phenomenon is important because it helps break "the document boundary " by allowing a user to ex-amine information about a

negative if all instances in it are negative. A bag is labeled positive if at least one instance in it is positive. Because the instances themselves are not labeled, each positive bag is an ambiguous example. We would like to learn a concept which will correctly classify unseen bags. We have developed a

formal transformation models, which only specify the mappings and abstract from the implementation. Current solutions are usually only able to describe unambiguous (1-on-1) mappings. In general, however, there are ambiguous (1-on-n) mappings from which the unambiguous mappings are only chosen during