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Informed voting is costly: research shows that voters use heuristics such as party identification and retrospection to make choices that approximate enlightened decision-making. Most of this work, however, focuses on high-information races and ignores elections in which these cues are often unavailable (e.g. primary, local). In these cases, citizens are on their own to search for quality information and evaluate it efficiently. To assess how voters navigate this situation, we field three survey experiments asking respondents what information they want before voting. We evaluate respondents on their ability to both acquire and utilize information in a way that improves their chances of voting for quality candidates, and how this varies by the sophistication of respondents and the offices sought by candidates. We find strong evidence that voters use "deal-breakers" to quickly eliminate undesirable candidates; however, the politically unsophisticated rely on unverifiable, vague, and irrelevant search considerations. Moreover, less sophisticated voters also rely on more personalistic considerations. The findings suggest that voters' search strategies may be ineffective at identifying the best candidates for office, especially at the local level.

Consensus is required for every new strategic initiative. Although politics can contribute to consensus-building, politics have also been associated with undermining the effectiveness of strategic initiatives. Our findings show how managers use heuristics to circumvent the adverse effects of politics in order to enhance consensus and improve the effectiveness of strategies. Based on a longitudinal case study in a large intergovernmental, aerospace organization in Europe, we show that effective consensus-building is enabled by the application of three distinct 'political heuristics' that we coin inception, delimitation, and validation. These three types of heuristics ensure the effectiveness of the strategic initiative and the consensus required. Consensus is achieved by the applications of these heuristics during formal-informal interactions across three phases of strategy development: initiation, content development, and consolidation. Hence, the three aforementioned heuristics mitigate the negative implications of politics and thereby enhance the effectiveness of the strategic initiative. Our findings offer insight into organizational politics and the micro-foundations of strategy, by showing at the micro level how heuristics enable effective and positive application of politics for consensus-building in organizations."

OBJECTIVES: Increasingly, support for water fluoridation has come under attack. We seek an explanation, focusing on the case of Waterloo, Ontario, where a 2010 referendum overturned its water fluoridation program. In particular, we test whether individuals perceive the risks of water fluoridation based not on 'hard' scientific evidence but on heuristics and cultural norms. METHODS: A sample of 376 residents in Waterloo were surveyed in June 2012 using random digit dialing. We use factor analysis, OLS regression, as well as t-tests to evaluate a survey experiment to test the credibility hypothesis. RESULTS: Perceptions of fluoride as a risk are lower among those who perceive fluoride's benefits (B =.473, p < 0.001) and those whose cultural view is 'egalitarian' (B =.156, p < 0.05). The experiment shows a lower level of perception of fluoride's benefits among respondents who are told that water fluoridation is opposed by a national advocacy group (Group A) compared to those who are told that the government and the World Health Organization support fluoridation (Group B) (t = 1.6547, p < 0.05), as well as compared to the control group (t = 1.891 3, p < 0.05). There is no difference between Group B and the control, possibly because people's already general support for fluoridation is less prone to change when told that other public organizations also support fluoridation. CONCLUSION: Public health officials should take into account cultural norms and perceptions when individuals in a community appear to rise up against water fluoridation, with implications for other public health controversies.

In response to the COVID-19 pandemic philosophers and governments have proposed scarce resource allocation guidelines. Their purpose is to advise healthcare professionals on how to ethically allocate scarce medical resources. One challenging feature of the pandemic has been the large numbers of patients needing mechanical ventilatory support. Guidelines have paradigmatically focused on the question of what doctors should do if they have fewer ventilators than patients who need respiratory support: which patient should get the ventilator? There is, however, an important higher level allocation problem. Namely, how are we to ethically distribute newly obtained ventilators across hospitals: which hospital should get the ventilator(s)? In this paper, we identify a set of principles for allocating newly obtained ventilators across hospitals. We focus particularly on low and middle income countries, who frequently have limited pre-existing intensive care capacity, and have needed to source additional ventilators. We first provide some background. Second, we argue that the main population healthcare aim during the COVID-19 pandemic should be to save the most lives. Next, we assess a series of potential heuristics or principles that could be used to guide allocation: allocation to the most densely populated cities, random allocation, allocation based on the ratio of patients to ICU personnel, prioritisation in terms of intrahospital mortality, prioritisation of younger populations, and prioritisation in terms of population mortality. We conclude by providing a plausible ranking of the principles, while noting a number of epistemological challenges, in terms of how they best further the aim of increasing the probability of saving the most lives.

This paper presents problem solving using heuristics and operational research in order to make appropriate decisions in emergency situations with a particular emphasis on the application of a heuristic model of team training for emergency situations. It is intended for military command and teaching personnel as well as for civil defense personnel (Department of Emergency Management) and local government authorities (administrative district chiefs and mayors commanders). The heuristic approach to problem solving should enable adequate decision making for command staff from the local to the national level after the proclamation of emergency and a state of emergency in some regions or the whole territory of Serbia. ; This paper presents problem solving using heuristics and operational research in order to make appropriate decisions in emergency situations with a particular emphasis on the application of a heuristic model of team training for emergency situations. It is intended for military command and teaching personnel as well as for civil defense personnel (Department of Emergency Management) and local government authorities (administrative district chiefs and mayors commanders). The heuristic approach to problem solving should enable adequate decision making for command staff from the local to the national level after the proclamation of emergency and a state of emergency in some regions or the whole territory of Serbia.

Indonesians often consume online news presenting figures of survey results, not only political news but other news as well, for instance, a news headline stated that 63 percent of people on average agreed to a cabinet reshuffle. Strangely enough, it was not stated 37 percent of people on average did not agree to a cabinet reshuffle, which has the same meaning. An attractive frame of online news will potentially get clicks from its audience. In theories of framing effect, news framing in general has a cognitive effect on the audience, including the framing of survey results. However, an opposing view suggests that the advent of new media, especially the internet and Web 2.0 technology, has changed the fundamental order of mass communication, which leads to a minimum effect of new media framing and difficulty in measuring them due to the emergence of preference-based effects as a natural attribute of the online media environment. This interesting research tries to examine the effects of framing in the realm of psychology, which is still quite rarely done in studies on framing effects, by using experimental quantitative methods that test individual evaluation heuristics. The framing of survey results turned out to have an effect on the heuristic assessment of the individual reader. The study prove that the framing effects remain even in new media platforms. The findings presented in this article are expected to contribute to the development of framing theories and media effects.

Informed voting is costly: research shows that voters use heuristics such as party identification and retrospection to make choices that approximate enlightened decision-making. Most of this work, however, focuses on high-information races and ignores elections in which these cues are often unavailable (e.g. primary, local). In these cases, citizens are on their own to search for quality information and evaluate it efficiently. To assess how voters navigate this situation, we field three survey experiments asking respondents what information they want before voting. We evaluate respondents on their ability to both acquire and utilize information in a way that improves their chances of voting for quality candidates, and how this varies by the sophistication of respondents and the offices sought by candidates. We find strong evidence that voters use "deal-breakers" to quickly eliminate undesirable candidates; however, the politically unsophisticated rely on unverifiable, vague, and irrelevant search considerations. Moreover, less sophisticated voters also rely on more personalistic considerations. The findings suggest that voters' search strategies may be ineffective at identifying the best candidates for office, especially at the local level.

The increasing throughput of DNA sequencing technologies creates a need for faster algorithms. The fate of most reads is to be mapped to a reference sequence, typically a genome. Modern mappers rely on heuristics to gain speed at a reasonable cost for accuracy. In the seeding heuristic, short matches between the reads and the genome are used to narrow the search to a set of candidate locations. Several seeding variants used in modern mappers show good empirical performance but they are difficult to calibrate or to optimize for lack of theoretical results. Here we develop a theory to estimate the probability that the correct location of a read is filtered out during seeding, resulting in mapping errors. We describe the properties of simple exact seeds, skip seeds and MEM seeds (Maximal Exact Match seeds). The main innovation of this work is to use concepts from analytic combinatorics to represent reads as abstract sequences, and to specify their generative function to estimate the probabilities of interest. We provide several algorithms, which together give a workable solution for the problem of calibrating seeding heuristics for short reads. We also provide a C implementation of these algorithms in a library called Sesame. These results can improve current mapping algorithms and lay the foundation of a general strategy to tackle sequence alignment problems. The Sesame library is open source and available for download at https://github.com/gui11aume/sesame. ; We acknowledge the financial support of the Spanish Ministry of Economy, Industry and Competitiveness (Centro de Excelencia Severo Ochoa 2013–2017, Plan Estatal PGC2018-099807-B-I00), of the CERCA Programme/Generalitat de Catalunya, and of the European Research Council (Synergy Grant 609989). RC was supported by the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement 608959. We also acknowledge support of the Spanish Ministry of Economy and Competitiveness (MEIC) to the EMBL partnership.

In flood risk management, the choice of vulnerability functions has a remarkable impact on the overall uncertainty of modelling flood damage. The spatial transferability of empirical vulnerability functions is limited, leading to the need for computation and validation of region-specific vulnerability functions. In data-scarce regions however, this option is not feasible. In contrast, the physical processes of flood impact model chains can be developed in these regions because of the availability of global datasets. Here we evaluated the implementation of a synthetic vulnerability function into a flood impact model. The function bases on expert heuristics on a targeted sample of representative buildings (targeted heuristics). We applied the vulnerability function in a meso-scale river basin and evaluated the new function by comparing the resulting flood damage with the damage computed by other approaches, (1) an ensemble of vulnerability functions available from the literature, (2) an individual vulnerability function calibrated with region-specific data, and (3) the vulnerability function used in flood risk management by the Swiss government. The results show that targeted heuristics can be a valuable alternative for developing flood impact models in regions without any data or only few data on flood damage.

In flood risk management, the choice of vulnerability functions has a remarkable impact on the overall uncertainty of modelling flood damage. The spatial transferability of empirical vulnerability functions is limited, leading to the need for computation and validation of region-specific vulnerability functions. In data-scarce regions however, this option is not feasible. In contrast, the physical processes of flood impact model chains can be developed in these regions because of the availability of global datasets. Here we evaluated the implementation of a synthetic vulnerability function into a flood impact model. The function bases on expert heuristics on a targeted sample of representative buildings (targeted heuristics). We applied the vulnerability function in a meso-scale river basin and evaluated the new function by comparing the resulting flood damage with the damage computed by other approaches, (1) an ensemble of vulnerability functions available from the literature, (2) an individual vulnerability function calibrated with region-specific data, and (3) the vulnerability function used in flood risk management by the Swiss government. The results show that targeted heuristics can be a valuable alternative for developing flood impact models in regions without any data or only few data on flood damage.

This paper focuses on iterated local search heuristics for the maximum cut‐clique (MCC, or clique neighborhood) problem. Given an undirected graph G = (V,E) and a clique C of G, the cut‐clique is the set of edges running between C and V\C, establishing the cut (C,V\C). The MCC in G is to find a clique with the largest number of edges in the neighborhood of the clique, also known as the maximum edge‐neighborhood clique. This problem has been recently introduced in the literature together with a number of applications, namely, in cell biology instances. However, it has only been addressed so far by exact methods. In this paper, we introduce the first approximate algorithms for tackling the MCC problem, compare the results with the exact methodologies, and explore a new application within marketing analysis, which provide a new alternative perspective for mining market basket problems. ; This work has been partially supported by the Portuguese National Funding by FCT (project PEst-OE/MAT/UI0152), Pedro Martins; and by the Ministerio de Economía y Competitividad (Spanish Government), A. Ladrón-de-Guevara (ECO2011-27942) and H. Ramalhinho (TRA2013-48180-C3-2-P).

[EN] In recent years, a large number of heuristics have been proposed for the minimization of the total or mean flowtime/completion time of the well-known permutation flowshop scheduling problem. Although some literature reviews and comparisons have been made, they do not include the latest available heuristics and results are hard to compare as no common benchmarks and computing platforms have been employed. Furthermore, existing partial comparisons lack the application of powerful statistical tools. The result is that it is not clear which heuristics, especially among the recent ones, are the best. This paper presents a comprehensive review and computational evaluation as well as a statistical assessment of 22 existing heuristics. From the knowledge obtained after such a detailed comparison, five new heuristics are presented. Careful designs of experiments and analyses of variance (ANOVA) techniques are applied to guarantee sound conclusions. The comparison results identify the best existing methods and show that the five newly presented heuristics are competitive or better than the best performing ones in the literature for the permutation flowshop problem with the total completion time criterion ; This research is partially supported by National Science Foundation of China (60874075, 61174187), and Science Foundation of Shandong Province, China (BS2010DX005), and Postdoctoral Science Foundation of China (20100480897). Ruben Ruiz is partially funded by the Spanish Ministry of Science and Innovation, under the project "SMPA-Advanced Parallel Multiobjective Sequencing: Practical and Theorerical Advances" with reference DPI2008-03511/DPI and by the Small and Medium Industry of the Generalitat Valenciana (IMPIVA) and by the European Union through the European Regional Development Fund (FEDER) inside the R+D program "Ayudas dirigidas a Institutos Tecnologicos de la Red IMPIVA" during the year 2011, with project number IMDEEA/2011/142. ; Pan, Q.; Ruiz García, R. (2013). A comprehensive review and evaluation of ...

This article argues for the value of working with conflicts in social practice as resources for collaboration, learning and development. The interest in conflicts in social practice is rooted in a preoccupation with social power relations and how to understand and analyse power relations from a subject-science perspective. Following this interest, a methodological framework, best described as a kind of 'mobile ethnography', is discussed and exemplified through an empirical example. A preliminary conceptual framework for understanding power as a capacity for action is presented. The overarching ambition of the article is to consider what democratic collaboration and coexistence entails and how it might be supported conceptually and analytically by the notion of conflicts as heuristics for social inquiry and by the notion of power as a capacity for action and social participation.

117 128 40 1 ; S ; [EN] In recent years, a large number of heuristics have been proposed for the minimization of the total or mean flowtime/completion time of the well-known permutation flowshop scheduling problem. Although some literature reviews and comparisons have been made, they do not include the latest available heuristics and results are hard to compare as no common benchmarks and computing platforms have been employed. Furthermore, existing partial comparisons lack the application of powerful statistical tools. The result is that it is not clear which heuristics, especially among the recent ones, are the best. This paper presents a comprehensive review and computational evaluation as well as a statistical assessment of 22 existing heuristics. From the knowledge obtained after such a detailed comparison, five new heuristics are presented. Careful designs of experiments and analyses of variance (ANOVA) techniques are applied to guarantee sound conclusions. The comparison results identify the best existing methods and show that the five newly presented heuristics are competitive or better than the best performing ones in the literature for the permutation flowshop problem with the total completion time criterion This research is partially supported by National Science Foundation of China (60874075, 61174187), and Science Foundation of Shandong Province, China (BS2010DX005), and Postdoctoral Science Foundation of China (20100480897). Ruben Ruiz is partially funded by the Spanish Ministry of Science and Innovation, under the project "SMPA-Advanced Parallel Multiobjective Sequencing: Practical and Theorerical Advances" with reference DPI2008-03511/DPI and by the Small and Medium Industry of the Generalitat Valenciana (IMPIVA) and by the European Union through the European Regional Development Fund (FEDER) inside the R+D program "Ayudas dirigidas a Institutos Tecnologicos de la Red IMPIVA" during the year 2011, with project number IMDEEA/2011/142. Pan, Q.; Ruiz García, R. (2013). A comprehensive review and ...

The paper presents learning and the heuristic method in educating Civil Defense staff with a view to making appropriate decisions in emergency situations and a state of emergency with special reference to the use of heuristic models in the education of emergency teams and the command of the Army of Serbia. It is designed for command and teaching staff, as well as for the personnel of civil defense, the protection and rescue system (Department for Emergency Situations) and local governments (district chief executives, mayors and mayors-commanders and commanding officers of the Army of Serbia that can be employed in emergency situations during the protection and rescue of people and materiel. The heuristic approach to problem solving and learning should provide the training of command personnel from the local to the national levels in making adequate decisions after the proclamation of emergency and a state of emergency in parts of the territory, or across the territory of the Republic of Serbia.