Evaluating the Mental Models Approach to Developing a Risk Communication: A Scoping Review of the Evidence

Risk communication is fundamental in ensuring people are equipped with the knowledge needed to navigate varied risks. One generally well‐regarded framework for the development of such communications is the mental models approach to risk communication (MMARC). Developed during the 1990s, the MMARC has been applied to a range of health, technological, and environmental risks. However, as yet, we know of no attempt to collate and review articles that evaluated communications developed using the MMARC. This article took a first step at addressing this gap by conducting a scoping review that aimed to begin to explore the fidelity with which the approach has been applied, explore whether there appeared to be sufficient studies to warrant a future systematic review, and identify future research questions. Although the initial search found over 100 articles explicitly applying the MMARC, only 12 of these developed a risk‐related communication that was tested against a control (and thus included in the current review). All studies reported a positive effect of the MMARC versus control communication for at least some of the outcome measures (knowledge being the most prevalent). However, there was wide variation between studies including type of control, outcomes assessed, and only five studies reported adopting a randomized design. The review highlights both the need for greater fidelity in the way future studies operationalize the MMARC approach, and suggests that a full‐scale systematic review of the MMARC literature appears justified, especially given the possibility of a large gray literature in this area.     

The Chimera of Sustainable Labour–Management Partnership

The paper advances a threefold theoretical contribution using a system, society and dominance (SSD) effects framework to show how and why sustainable management–labour workplace partnerships are a chimera. First, managers (employers) find it increasingly difficult to keep workplace bargains with employees (unions) owing to increasingly neoliberal ‘system’ effects associated with capitalism as a globalized accumulation model. Second, workplace mutuality will be rare because of ‘societal’ level effects under voluntarism. Third, ‘dominance’ effects arising from the power of dominant economies and their multinational corporations can inhibit workplace mutuality. Drawing on empirical case study data from Ireland, the future prognosis of management–labour collaboration under neoliberal work regimes is discussed.     

历史解释中的形式主义与情境主义策略

历史解释中形式主义与情境主义策略之间的冲突自古就有.情境主义的隐含之义是"历史的".人们对历史对象和它们的情境进行的所有描述具有必然的比喻性质.情境主义解释策略在历史编纂中以对现象领域的描述为特色.对于情境及存在于情境中的实体的描述都是比喻性的,它们之间的关系可以用比喻本身的不同形态说明.新历史主义文学史研究有意无意地与文学和历史学领域中占优势的正统学说发生了冲突,它试图以情境主义来弥补当前盛行的形式主义,但它仍然包含有形式主义.在研究中,新历史主义提出了文化诗学的观点,并已经拓展到历史诗学.     

Scale-space theory: a basic tool for analyzing structures at different scales

An inherent property of objects in the world is that they only exist as meaningful entities over certain ranges of scale. If one aims to describe the structure of unknown real-world signals, then a multi-scale representation of data is of crucial importance. This paper gives a tutorial review of a special type of multi-scale representation—linear scale-space representation—which has been developed by the computer vision community to handle image structures at different scales in a consistent manner. The basic idea is to embed the original signal into a one-parameter family of gradually smoothed signals in which the fine-scale details are successively suppressed. Under rather general conditions on the type of computations that are to be performed at the first stages of visual processing, in what can be termed 'the visual front-end', it can be shown that the Gaussian kernel and its derivatives are singled out as the only possible smoothing kernels. The conditions that specify the Gaussian kernel are, basically, linearity and shift invariance, combined with different ways of formalizing the notion that structures at coarse scales should correspond to simplifications of corresponding structures at fine scales-they should not be accidental phenomena created by the smoothing method. Notably, several different ways of choosing scale-space axioms give rise to the same conclusion. The output from the scale-space representation can be used for a variety of early visual tasks; operations such as feature detection, feature classification and shape computation can be expressed directly in terms of (possibly non-linear) combinations of Gaussian derivatives at multiple scales. In this sense the scale-space representation canserve as a basis for early vision. During the last few decades, a number of other approaches to multiscale representations have been developed, which are more or less related to scale-space theory, notably the theories of pyramids, wavelets and multi grid methods.Despite their qualitative differences, the increasing propularity of each of these approaches indicates that the crucial notion of scale is increasingly appreciated by the computer.vision community and by researchers in other related fields. An interesting similarity to biological vision is that the scale-space operators closely resemble receptive field profiles registered in neurophysiological studies of the mam- malian retina and visual cortex.     

A NOTE ON MODELING PROJECT INTERDEPENDENCE IN RESEARCH AND DEVELOPMENT*

This note is concerned with the problem of resource allocation under uncertainty in a research and development laboratory. A distinction is defined between project interrelationships that are specific (or internal) to certain projects and interrelationships resulting from external environmental factors. Formulations are introduced that allow both types of interrelationships to be formally included in a resource allocation optimization model. In the case of external environmental factors, an example is presented and analyzed.