Advancing towards inclusive social research: visual methods as opportunities for people with severe mental illness to participate in research

This article explores the possibilities offered by visual methods in the move towards inclusive research, reviewing some methodological implications of said research and reflecting on the potential of visual methods to meet these methodological requirements. A study into the impact of work on social inclusion and the social relationships of people suffering from severe mental illness (SMI) serves to illustrate the use of visual methods such as photo elicitation and graphic elicitation in the context of in-depth interviews with the aim of improving the aforementioned target group’s participation in research, participation understood as one of the basic elements of inclusive approaches. On the basis of this study, we reflect on the potential of visual methods to improve the inclusive approach to research and conclude that these methods are open and flexible in awarding participantsa voice, allowingpeople with SMI to express their needs, and therefore adding value to said approach.     

语篇分析与英语听力教学

在英语听力教学中 ,不论是非英语专业学生还是英语专业学生 ,都存在一个普遍的问题 ,即对单句和简短对话式的听力理解能力强 ,而对较长的语篇理解能力差。他们在听力中的问题主要反映在语言、词汇和句法结构层面上。这是因为他们在听的过程中只是孤立地去听懂每一句话而不是通篇理解。而语篇分析的目的不在于对局部语义的解读 ,而在于对篇章整体的解读 ,通过语篇解读 ,学生们就能真正理解所听材料 ,记住其主要内容。     

Elicitation of Decision-Makers'Preferences for Management of Major Hazards

A survey has been conducted among decision-makers from the urban area of Lyon (France). It aimed at elicitating attitudes toward industrial risk, with an emphasis on major hazards. The sample was quite small (23 individuals), but most of the actual decision-makers of the area belonged to it. A questionnaire allowed to look at the weights that are given to "catastrophic accidents," when compared to more usual ones. It showed that decision-makers are strongly "adverse to catastrophes." The findings support many risk management approaches that are based on assigning an "extra weight" to potential accidents that may cause a high number of casualties.     

Using Expert Models in Human Reliability Analysis—A Dependence Assessment Method Based on Fuzzy Logic

In human reliability analysis (HRA), dependence analysis refers to assessing the influence of the failure of the operators to perform one task on the failure probabilities of subsequent tasks. A commonly used approach is the technique for human error rate prediction (THERP). The assessment of the dependence level in THERP is a highly subjective judgment based on general rules for the influence of five main factors. A frequently used alternative method extends the THERP model with decision trees. Such trees should increase the repeatability of the assessments but they simplify the relationships among the factors and the dependence level. Moreover, the basis for these simplifications and the resulting tree is difficult to trace. The aim of this work is a method for dependence assessment in HRA that captures the rules used by experts to assess dependence levels and incorporates this knowledge into an algorithm and software tool to be used by HRA analysts. A fuzzy expert system (FES) underlies the method. The method and the associated expert elicitation process are demonstrated with a working model. The expert rules are elicited systematically and converted into a traceable, explicit, and computable model. Anchor situations are provided as guidance for the HRA analyst's judgment of the input factors. The expert model and the FES‐based dependence assessment method make the expert rules accessible to the analyst in a usable and repeatable way, with an explicit and traceable basis.     

Participatory analytic hierarchy process for resource allocation in agricultural development projects

In the framework of 2030 Agenda sustainable agriculture plays a central role. In the field of international aid the participatory approaches to assessment, research, management and budgeting have been widely studied and applied in the last decades, mostly because international aid initiatives, in all their relevant phases from planning through implementation, monitoring and evaluation, are faced with the problem of identifying initiatives that could be successfully and sustainably implemented. The present paper investigates the use of a modified form of analytic hierarchy process, namely the participatory analytic hierarchy process, as a tool for choice criteria elicitation and resource allocation in the framework of an operational planning for agricultural development projects in the Dioceses of Goma, Nord Kivu, Democratic Republic of Congo. During our research, we were able to make use of most frequent inconsistencies in pairwise comparison matrixes in order to stimulate the debate, to adjust local preferences and to build consensus across the group. From an operational point of view, the PAHP methodology was also suited for training the project team and for identifying a shared resource allocation pattern, which matches the existing international guidelines for agricultural development in the region.     

Expert knowledge elicitation using item response theory

In an expert knowledge elicitation exercise, experts face a carefully constructed list of questions that they answer according to their knowledge. The elicitation process concludes when a probability distribution is found that adequately captures the experts' beliefs in the light of those answers. In many situations, it is very difficult to create a set of questions that will efficiently capture the experts' knowledge, since experts might not be able to make precise probabilistic statements about the parameter of interest. We present an approach for capturing expert knowledge based on item response theory, in which a set of binary response questions is proposed to the expert, trying to capture responses directly related to the quantity of interest. As a result, the posterior distribution of the parameter of interest will represent the elicited prior distribution that does not assume any particular parametric form. The method is illustrated by a simulated example and by an application involving the elicitation of rain prophets' predictions for the rainy season in the north-east of Brazil.     

如何在教学中提高大学生的数学素质

论述了提高大学生数学素质的重要性，指出了当前教学中不利于提高大学生数学素质的一些问题，并提供了解决问题的对策。     

Can Business Owners Form Accurate Counterfactuals? Eliciting Treatment and Control Beliefs About Their Outcomes in the Alternative Treatment Status

A survey of participants in a large-scale business plan competition experiment, in which winners received an average of U.S. $50,000 each, is used to elicit ex-post beliefs about what the outcomes would have been in the alternative treatment status. Participants are asked the percent chance they would be operating a firm, and the number of employees and monthly sales they would have, had their treatment status been reversed. The study finds the control group to have reasonably accurate expectations of the large treatment effect they would experience on the likelihood of operating a firm, although this may reflect the treatment effect being close to an upper bound. The control group dramatically overestimates how much winning would help them grow the size of their firm. The treatment group overestimates how much winning helps their chance of their business surviving and also overestimates how much winning helps them grow their firms. In addition, these counterfactual expectations appear unable to generate accurate relative rankings of which groups of participants benefit most from treatment.     

Experimental Evidence Against the Paradigm of Mortality Risk Aversion

This article deals with the question of how societal impacts of fatal accidents can be integrated into the management of natural or man‐made hazards. Today, many governmental agencies give additional weight to the number of potential fatalities in their risk assessments to reflect society's aversion to large accidents. Although mortality risk aversion has been proposed in numerous risk management guidelines, there has been no evidence that lay people want public decisionmakers to overweight infrequent accidents of large societal consequences against more frequent ones of smaller societal consequences. Furthermore, it is not known whether public decisionmakers actually do such overweighting when they decide upon the mitigation of natural or technical hazards. In this article, we report on two experimental tasks that required participants to evaluate negative prospects involving 1–100 potential fatalities. Our results show that neither lay people nor hazard experts exhibit risk‐averse behavior in decisions on mortality risks.     

The Aggregation of Expert Judgment: Do Good Things Come to Those Who Weight?

Good policy making should be based on available scientific knowledge. Sometimes this knowledge is well established through research, but often scientists must simply express their judgment, and this is particularly so in risk scenarios that are characterized by high levels of uncertainty. Usually in such cases, the opinions of several experts will be sought in order to pool knowledge and reduce error, raising the question of whether individual expert judgments should be given different weights. We argue—against the commonly advocated “classical method”—that no significant benefits are likely to accrue from unequal weighting in mathematical aggregation. Our argument hinges on the difficulty of constructing reliable and valid measures of substantive expertise upon which to base weights. Practical problems associated with attempts to evaluate experts are also addressed. While our discussion focuses on one specific weighting scheme that is currently gaining in popularity for expert knowledge elicitation, our general thesis applies to externally imposed unequal weighting schemes more generally.