This paper is concerned with the efficiency of information aggregation in a committee whose members have heterogeneous preferences over a binary decision variable. We study a voting game with a pre-vote communication stage and identify conditions under which full information aggregation is possible. In particular, if preferences are common knowledge and each committee member is endowed with information, full information aggregation is possible despite preference heterogeneity.

Prediction markets are increasingly being considered as methods for gathering, summarizing and aggregating diffuse information by governments and businesses alike. Critics worry that these markets are susceptible to price manipulation by agents who wish to distort decision making. We study the effect of manipulators on an experimental market, and find that manipulators are unable to distort price accuracy. Subjects without manipulation incentives compensate for the bias in offers from manipulators by setting a different threshold at which they are willing (...) to accept trades. (shrink)

Information is a peculiar quantity. Unlike matter and energy, which are conserved by the laws of physics, the aggregation of knowledge from many sources can in fact produce more information (synergy) or less (redundancy) than the sum of its parts. This feature can endow groups with problem‐solving strategies that are superior to those possible among noninteracting individuals and, in turn, may provide a selection drive toward collective cooperation and coordination. Here we explore the formal properties of (...) class='Hi'>information aggregation as a general principle for explaining features of social organization. We quantify information in terms of the general formalism of information theory, which also prescribes the rules of how different pieces of evidence inform the solution of a given problem. We then show how several canonical examples of collective cognition and coordination can be understood through principles of minimization of uncertainty (maximization of predictability) under information pooling over many individuals. We discuss in some detail how collective coordination in swarms, markets, natural language processing, and collaborative filtering may be guided by the optimal aggregation of information in social collectives. We also identify circumstances when these processes fail, leading, for example, to inefficient markets. The contrast to approaches to understand coordination and collaboration via decision and game theory is also briefly discussed. (shrink)

Is there a rationale for an electoral college system or do these voting systems always waste useful information? This paper studies this question in a setup in which voting is supposed to aggregate decentralized information about individual preferences for two candidates. Individual perceptions may be affected by regional information. When such regional information plays a major role, an electoral college system may be superior to simple majority voting.

In practice, scoring rules elicit good probability estimates from individuals, while betting markets elicit good consensus estimates from groups. Market scoring rules combine these features, eliciting estimates from individuals or groups, with groups costing no more than individuals. Regarding a bet on one event given another event, only logarithmic versions preserve the probability of the given event. Logarithmic versions also preserve the conditional probabilities of other events, and so preserve conditional independence relations. Given logarithmic rules that elicit relative probabilities of (...) base event pairs, it costs no more to elicit estimates on all combinations of these base events. (shrink)

In practice, scoring rules elicit good probability estimates from individuals, while betting markets elicit good consensus estimates from groups. Market scoring rules combine these features, eliciting estimates from individuals or groups, with groups costing no more than individuals. Regarding a bet on one event given another event, only logarithmic versions preserve the probability of the given event. Logarithmic versions also preserve the conditional probabilities of other events, and so preserve conditional independence relations. Given logarithmic rules that elicit relative probabilities of (...) base event pairs, it costs no more to elicit estimates on all combinations of these base events. (shrink)

In India, more than ninety percent of the workforce is informal. In spite of this enormous percentage of informal workers, these workers remain invisible to law and policy circles. One of the reasons for such exclusion and invisibility is the absence of unionism involving informal workers. In order to overcome this invisibility, informal workers are increasingly organizing into associations that are different from traditional trade unions. These organizations devise their strategies and their legal statuses in view of the atypical characteristics (...) of informal activities. In this Article, I document some of these organizations of self-employed informal workers in India – their characteristics and functions. On this basis, I contend that these organizations offer a model for collective action by informal workers. I argue that these associations are a sui generis organization of informal workers, and could become a precursor to solidarity-based collective initiatives by informal workers globally. In the backdrop to this proposition, I analyze the role of law in promoting such aggregation of informal workers in furtherance of their collective action. I argue that while organizations of informal workers in India employ the existing legal framework to the best of their advantage, the law fails to recognize some of their status as workers, thereby creating hurdles towards informal workers’ collective action. A small farmer works on her own farm. In tough times, she also works on other farms as a laborer. When the agriculture season is over, she goes to the forest to collect gum and other forest produce. Year round, she produces embroidered items either at a piece rate for a contractor or for sale to a trader who comes to her village to buy goods. Now, how should her trade be categorized? Does she belong to the agricultural sector, the factory sector, or the home-based work sector? Should she be categorized as a farmer or a farm worker? Is she self-employed or is she a piece-rate worker? Because her situation cannot be defined and contained neatly in a box, she has no work status and her right to representation in a union is unrealized. She is denied access to financial services or training to upgrade her skills. The tyranny of having to belong to a well-defined “category” has condemned her to having no “identity.” — Ela R. BhattEla R. Bhatt, We Are Poor but So Many: The Story of Self-Employed Women in India 17. (shrink)

Suppose that the members of a group each hold a rational set of judgments on some interconnected questions, and imagine that the group itself has to form a collective, rational set of judgments on those questions. How should it go about dealing with this task? We argue that the question raised is subject to a difficulty that has recently been noticed in discussion of the doctrinal paradox in jurisprudence. And we show that there is a general impossibility theorem that that (...) difficulty illustrates. Our paper describes this impossibility result and provides an exploration of its significance. The result naturally invites comparison with Kenneth Arrow's famous theorem (Arrow, 1963 and 1984; Sen, 1970) and we elaborate that comparison in a companion paper (List and Pettit, 2002). The paper is in four sections. The first section documents the need for various groups to aggregate its members' judgments; the second presents the discursive paradox; the third gives an informal statement of the more general impossibility result; the formal proof is presented in an appendix. The fourth section, finally, discusses some escape routes from that impossibility. (shrink)

As a generalization of both single-valued neutrosophic element and hesitant fuzzy element, single-valued neutrosophic hesitant fuzzy element is an efficient tool for describing uncertain and imprecise information. Thus, it is of great significance to deal with single-valued neutrosophic hesitant fuzzy information for many practical problems. In this paper, we study the aggregation of SVNHFEs based on some normalized operations from geometric viewpoint. Firstly, two normalized operations are defined for processing SVNHFEs. Then, a series of normalized aggregation (...) operators which fulfill some basic conditions of a valid aggregation operator are proposed. Additionally, a decision-making method is developed for resolving multiattribute decision-making problems based on the proposed operators. Finally, a numerical example is provided to illustrate the feasibility and effectiveness of the method. (shrink)

In our current era, a new rapidly spreading pandemic disease called coronavirus disease, caused by a virus identified as a novel coronavirus, is becoming a crucial threat for the whole world. Currently, the number of patients infected by the virus is expanding exponentially, but there is no commercially available COVID-19 medication for this pandemic. However, numerous antiviral drugs are utilized for the treatment of the COVID-19 disease. Identification of the appropriate antivirus medicine to treat the infection of COVID-19 is still (...) a complicated and uncertain decision. This study’s key objective is to develop a novel approach called _q_-rung orthopair probabilistic hesitant fuzzy rough set, which incorporates the _q_-rung orthopair fuzzy set, probabilistic hesitant fuzzy set, and rough set structures. New _q_-ROPHFR aggregation operators have been established: the _q_-ROPHFR Einstein weighted averaging operator and the _q_-ROPHFR Einstein weighted geometric operator. In this study, we explored some basic features of the developed operators. Afterward, to demonstrate the viability and feasibility of the established decision-making approach in real-world applications, a case study related to selecting drugs for COVID-19 pandemic is addressed. Furthermore, a comprehensive comparison with the _q_-rung orthopair probabilistic hesitant fuzzy rough TOPSIS technique is also presented to illustrate the benefits of the new framework. The obtained results confirm the reliability and effectiveness of the proposed approach for finding uncertainty in real-world decision-making. (shrink)

Returning research results to participants is recognised as an obligation that researchers should always try to fulfil. But can we ascribe the same obligation to researchers who conduct genomics research producing only aggregated findings? And what about genomics research conducted in developing countries? This paper considers Beskow's et al. argument that aggregated findings should also be returned to research participants. This recommendation is examined in the context of genomics research conducted in developing countries. The risks and benefits of attempting such (...) an exercise are identified, and suggestions on ways to avoid some of the challenges are proposed. I argue that disseminating the findings of genomic research to participating communities should be seen as sharing knowledge rather than returning results. Calling the dissemination of aggregate, population level information returning results can be confusing and misleading as participants might expect to receive individual level information. Talking about sharing knowledge is a more appropriate way of expressing and communicating the outcome of population genomic research. Considering the knowledge produced by genomics research a worthwhile output that should be shared with the participants and approaching the exercise as a ‘sharing of knowledge’, could help mitigate the risks of unrealistic expectations and misunderstanding of findings, whilst promoting trusting and long lasting relationships with the participating communities. (shrink)

Most accounts of welfare aggregation in the tradition of Arrow's and Sen's social-choice-theoretic frameworks represent the welfare of an individual in terms of a single welfare ordering or a single scalar-valued welfare function. I develop a multidimensional generalization of Arrow's and Sen's frameworks, representing individual welfare in terms of multiple personal welfare functions, corresponding to multiple 'dimensions' of welfare. I show that, as in the one-dimensional case, the existence of attractive aggregation procedures depends on certain informational assumptions, specifically (...) about the measurability of welfare and its comparability not only across individuals but also across dimensions. I state several impossibility and possibility results. Under Arrow-type conditions, insufficient comparability across individuals leads to dictatorship of a single individual, while insufficient comparability across dimensions leads to dominance of a single dimension. Given sufficient comparability both across individuals and across dimensions, a range of possibilities emerges. I discuss the substantive implications of the results. (shrink)

By comparing developments in two southern Italian factories, this article contrasts “aggregative” and “deliberative” procedures in trade unions. In one of the plants, the preferences of some of the workers appear to have been changed by deliberation. The process of rational persuasion seems to have required, however, more than sheer circulation of information. Based on this evidence, the article argues that when a potential conflict of interests is involved, speakers need to provide evidence that they are animated by a (...) “communicative” rather than “strategic” intent. This implies validating their implicit claim to sincerity of communication. (shrink)

Theories of aggregated legislative intent posit that the legislative intent of parliament is what a significant enough proportion of legislators intended (e.g., legislative intent is p if a majority intend that p). After all, many think the same way about democracy (‘votes reveal the will of the people’) and about courts (‘a court decision is based on judicial voting’). The existing literature on aggregated legislative intent, however, tends to make two undefended assumptions: (i) Informed Assumption: all legislators have policy intentions; (...) and (ii) Group Intent Assumption: the existence of an aggregated intent entails the existence of a group intent. Despite these assumptions being subject to great scrutiny, they largely remain undefended. This paper defends the Group Intent Assumption and shows that aggregated theories can survive with a weaker version of the Informed Assumption. (shrink)

With the rapidly growing amounts of information, visualization is becoming increasingly important, as it allows users to easily explore and understand large amounts of information. However the field of information visualiza- tion currently lacks sufficient theoretical foundations. This article addresses foundational questions connecting information visualization with computing and philosophy studies. The idea of multiscale information granula- tion is described based on two fundamental concepts: information (structure) and computation (process). A new information processing paradigm (...) of Granular Computing enables stepwise increase of granulation/aggregation of information on different levels of resolution, which makes possible dynamical viewing of data. Information produced by Google Earth is an illustration of visualization based on clustering (granulation) of information on a succession of layers. Depending on level, specific emergent properties become visible as a result of different ways of aggregation of data/information. As information visualization ultimately aims at amplifying cognition, we discuss the process of simulation and emulation in relation to cognition, and in particular visual cognition. (shrink)

Facing an increasingly competitive market, enterprises need correct decisions to solve operational problems in a timely manner to maintain their competitive advantages. In this context, insufficient information may lead to an overfitting phenomenon in general mathematical modeling methods, making it difficult to ensure good analytical performance. Therefore, it is important for enterprises to be able to effectively analyze and make predictions using small data sets. Although various approaches have been developed to solve the problem of prediction, their application is (...) often limited by insufficient observations. To further enforce the effectiveness of data uncertainty processing, this study proposed an aggregating prediction model for management decision analysis using small data sets. Compared with six popular approaches, the results from the experiments show that the proposed method can effectively deal with the small data set prediction problem and is thus an appropriate decision analysis tool for managers. (shrink)

It is said what aggregative properties are and also what emergent properties are, and examples are given each of kind of property. It is also explained why, even though all emergent properties are aggregative properties, not all aggregative properties are emergent properties. It is further made clear that, strictly speaking, emergence is a property of one's knowledge of a given kind of aggregate, and not of such aggregates themselves, this being why a property that is emergent at one time will, (...) when additional information becomes available, cease to be emergent. And it is explained why, for this very reason, the right answer to the question 'why does X exist?' is never 'because X is an emergent property.'. (shrink)

One of the major problems that artificial intelligence needs to tackle is the combination of different and potentially conflicting sources of information. Examples are multi-sensor fusion, database integration and expert systems development. In this paper we are interested in the aggregation of propositional logic-based information, a problem recently addressed in the literature on information fusion. It has applications in multi-agent systems that aim at aggregating the distributed agent-based knowledge into an (ideally) unique set of propositions. We (...) consider a group of autonomous agents who individually hold a logically consistent set of propositions. Each set of propositions represents an agent’s beliefs on issues on which the group has to make a collective decision. To make the collective decision, several aggregation procedures have been proposed in the literature. Assuming that all propositions in question are factually right or wrong, we ask how good belief fusion is as a truth tracker. Will it single out the true set of propositions? And how does information fusion compare with other aggregation procedures? We address these questions in a probabilistic framework and show that information fusion does especially well for agents with a middling competence of hitting the truth of an individual proposition. (shrink)

Judgment-aggregation theory has always focused on the attainment of rational collective judgments. But so far, rationality has been understood in static terms: as coherence of judgments at a given time, defined as consistency, completeness, and/or deductive closure. This paper asks whether collective judgments can be dynamically rational, so that they change rationally in response to new information. Formally, a judgment aggregation rule is dynamically rational with respect to a given revision operator if, whenever all individuals revise their (...) judgments in light of some information (a learnt proposition), then the new aggregate judgments are the old ones revised in light of this information, i.e., aggregation and revision commute. We prove an impossibility theorem: if the propositions on the agenda are non-trivially connected, no judgment aggregation rule with standard properties is dynamically rational with respect to any revision operator satisfying some basic conditions on revision. Our theorem is the dynamic-rationality counterpart of some well-known impossibility theorems for static rationality. We also explore how dynamic rationality might be achieved by relaxing some of the conditions on the aggregation rule and/or the revision operator. Notably, premise-based aggregation rules are dynamically rational with respect to so-called premise-based revision operators. (shrink)

We analyse the incentives of individuals to misrepresent their truthful judgments when engaged in collective decision-making. Our focus is on scenarios in which individuals reason about the incentives of others before choosing which judgments to report themselves. To this end, we introduce a formal model of strategic behaviour in logic-based judgment aggregation that accounts for such higher-level reasoning as well as the fact that individuals may only have partial information about the truthful judgments and preferences of their peers. (...) We find that every aggregation rule must belong to exactly one of three possible categories: it is either (i) immune to strategic manipulation for every level of reasoning, or (ii) manipulable for every level of reasoning, or (iii) immune to manipulation only for everykth level of reasoning, for some natural number kgreater than 1. (shrink)

Protein aggregation has been studied for at least 3 decades, and many of the principles that regulate this event are relatively well understood. Here, however, we present a different perspective to explain why proteins aggregate: we argue that aggregation may occur as a side‐effect of the lack of one or more natural partners that, under physiologic conditions, would act as chaperones. This would explain why the same surfaces that have evolved for functional purposes are also those that favour (...) aggregation. In the course of reviewing this field, we substantiate our hypothesis with three paradigmatic examples that argue for the generality of our proposal. An obvious corollary of this hypothesis is, of course, that targeting the physiological partners of a protein could be the most direct and specific approach to designing anti‐aggregation molecules. Our analysis may thus inform a different strategy for combating diseases of protein aggregation and misfolding. (shrink)

We introduce a new operator – belief fusion– which aggregates the beliefs of two agents, each informed by a subset of sources ranked by reliability. In the process we definepedigreed belief states, which enrich standard belief states with the source of each piece of information. We note that the fusion operator satisfies the invariants of idempotence, associativity, and commutativity. As a result, it can be iterated without difficulty. We also define belief diffusion; whereas fusion generally produces a belief state (...) with more information than is possessed by either of its two arguments, diffusion produces a state with less information. Fusion and diffusion are symmetric operators, and together define a distributive lattice. Finally, we show that AGM revision can be viewed as fusion between a novice and an expert. (shrink)

A necessary condition for a group being taken as a rational agent is that its choices and judgements are ‘logically contestable’, but this can lead to problems of aggregation, as Arrow impossibility theorem or the discursive dilemma. This paper proposes a contractarian or constitutional approach: the relevant thing is what aggregation mechanisms would be preferred by the members of the group. Two distinctions need to be made: first, judgement aggregation is not aggregation of decisions, and judgement (...) aggregation needs be distinguished from the aggregation of information: we assume that every member of the group has already taken into account the opinions of the other members, by means of a process of public deliberation, but they may end having different opinions; we also assume that the members are rational, so that they have no reasons to accept further changes in their individual opinions. So, from the epistemic point of view, the collective judgment is not a 'better' opinion than those of the individual members. The collective judgement is better seen as a kind of compromise, the outcome of a ‘bargain’, so to say. Basically, we assume that individuals will have an interest in choosing a specific aggregation function by taking into account how are they affected by the collective actions carried out by the group, and grounded on the chosen collective judgement. (shrink)

There are those philosophers and historians of science who claim that the acceptance and rejection of scientific theories is underdetermined by experimental results. They conclude that there is no rational method for deciding such matters solely on the basis of empirical information. The acceptance and rejection of scientific theories depends on social influence and is settled by social dominance. This I call the dominance thesis. There are also those who hold, on the contrary, that the acceptance and rejection of (...) theories in science is based solely on empirical information according to a rational method. They conclude that the acceptance and rejection of scientific theories is fully determined by experimental results. This I call the experimentalism thesis. The dominance thesis and the experimentalism thesis are both false. Both share a common premise, to wit, that empirical information is limited to experimental results. There is, however, another source of empirical information, the opinions of experts. When such social information is properly aggregated, the acceptance and rejection of scientific theories, though underdetermined by experimental results, is fully determined by the total information available. (shrink)

Electronic machinic phenomena yield fascinating links with biological processes. Either in the macro-micro-structure of binary encoded information ‐ bytes on media ‐ to the processual flow programs execute on hardware while operating it. Observing micro-electronic worlds akin to living entities: electronic voltages running throughout electronic architectures pipelining data to memory registers; operating systems executing programs on electronic substrates; data flows taking place in machines and in communications protocols within networks. Static art-sci constructs explore and visualize these observations as 2D (...) drawings (Neon Paleolitikos Drawings, 2017‐present) or 3D sculptures (Binary and Biological Sculpture Series, 2018‐present), creatively exposing their inherent rhythmic organization of information, while dynamic installations (Phoenix.Wolfanddotcom.info, Wolfanddotcom, Half-Plant, 2017, Ant Ennae Labyrinths, 2019‐present) propose immersive interference mechanisms that attempt user entanglement in non-human environments. Seven aesthetic case examples are introduced and explored, observing and seeking resonances between micro-granular electronic, biological and hybrid data as source synthesis. This research proposes a look at bio-electronic aggregates on Neon Paleolitikos strata. After the Anthropocene, Neon Paleolitikos is an imaginary epoch dating since the decline of mankind until the zenith of bio-electronic life forms: operational symbioses combined among ruins of silica, transistors, algorithms, cells, plants, animals and electricity. (shrink)

Decision makers often rely on expert opinion when making forecasts under uncertainty. In doing so, they confront two methodological challenges: the elicitation problem, which requires them to extract meaningful information from experts; and the aggregation problem, which requires them to combine expert opinion by resolving disagreements. Linear averaging is a justifiably popular method for addressing aggregation, but its robust simplicity makes two requirements on elicitation. First, each expert must offer probabilistically coherent forecasts; second, each expert must respond (...) to all our queries. In practice, human judges (even experts) may be incoherent, and may prefer to assess only the subset of events about which they are comfortable offering an opinion. In this paper, a new methodology is developed for combining expert assessment of chance. The method retains the conceptual and computational simplicity of linear averaging, but generalizes the standard approach by relaxing the requirements on expert elicitation. The method also enjoys provable performance guarantees, and in experiments with real-world forecasting data is shown to offer both computational efficiency and competitive forecasting gains as compared to rival aggregation methods. This paper is relevant to the practice of decision analysis, for it enables an elicitation methodology in which judges have freedom to choose the events they assess. (shrink)

The primary theme of this paper is the normative case against ownership of one's genetic information along with the source of that information (usually human tissues samples). The argument presented here against such “upstream” property rights is based primarily on utilitarian grounds. This issue has new salience thanks to the Human Genome Project and “bio-prospecting” initiatives based on the aggregation of genetic information, such as the one being managed by deCODE Genetics in Iceland. The rationale for (...) ownership is twofold: ownership will protect the basic human rights of privacy and autonomy and it will enable the data subjects to share in the tangible benefits of the genetic research. Proponents of this viewpoint often cite the principle of genetic exceptionalism, which asserts that genetic information needs a higher level of protection than other kinds of personal information such as financial data. We argue, however, that the recognition of such ownership rights would lead to inefficiency along with the disutility of genetic discoveries. Biomedical research will be hampered if property rights in genes and genetic material are too extensive. We contend that other mechanisms such as informed consent and strict confidentiality rules can accomplish the same result as a property right without the liabilities of an exclusive entitlement. (shrink)

Though it is held that some models in science have explanatory value, there is no conclusive agreement on what provides them with this value. One common view is that models have explanatory value vis-à-vis some target systems because they are developed using an abstraction process. Though I think this is correct, I believe it is not the whole picture. In this paper, I argue that, in addition to the well-known process of abstraction understood as an omission of features or (...) class='Hi'>information, there is also a family of abstraction processes that involve aggregation of features or information and that these processes play an important role in endowing the models they are used to build with explanatory value. After offering a taxonomy of abstraction processes involving aggregation, I show by considering in detail several models drawn from different sciences that the abstraction processes involving aggregation that are used to build these models are responsible for their having explanatory value. (shrink)

Cybersecurity aggregates are numerical data obtained by aggregation on features along a database of cybersecurity reports. These aggregates are obtained by integration of time-stamped tables using some recent results of non-standard calculus. Time-series of aggregates are shown to contain relevant information about the concrete system dealt with. Trend time series is also forecasted using known data-driven methods. Although absolute forecasting of trend time series is not obtained, a directional forecasting of trend time series is achieved thence validated by (...) means of a rolling cross validation scheme on a public database of Scareware reports. (shrink)

We introduce a new operator – belief fusion– which aggregates the beliefs of two agents, each informed by a subset of sources ranked by reliability. In the process we definepedigreed belief states, which enrich standard belief states with the source of each piece of information. We note that the fusion operator satisfies the invariants of idempotence, associativity, and commutativity. As a result, it can be iterated without difficulty. We also define belief diffusion; whereas fusion generally produces a belief state (...) with more information than is possessed by either of its two arguments, diffusion produces a state with less information. Fusion and diffusion are symmetric operators, and together define a distributive lattice. Finally, we show that AGM revision can be viewed as fusion between a novice and an expert. (shrink)

Non-compensatory aggregation rules are applied in a variety of problems such as voting theory, multi-criteria analysis, composite indicators, web ranking algorithms and so on. A major open problem is the fact that non-compensability implies the analytical cost of loosing all available information about intensity of preference, i.e. if some variables are measured on interval or ratio scales, they have to be treated as measured on an ordinal scale. Here this problem has been tackled in its most general formulation, (...) that is when mixed measurement scales (interval, ratio and ordinal) are used and both stochastic and fuzzy uncertainties are present. Objectives of this article are first to present a comprehensive review of useful solutions already proposed in the literature and second to advance the state of the art mainly in the theoretical guarantee that weights have the meaning of importance coefficients and they can be summarized in a voting matrix. This is a key result for using non-compensatory Condorcet consistent rules. A proof on the probability of existence of ties in the voting matrix is also developed. (shrink)

Protecting the privacy of individually-identifiable health data and promoting the public’s health often seem at odds. Privacy advocates consistently seek to limit the acquisition, use, and disclosure of identifiable health information in governmental and private sector settings. Their concerns relate to misuses or wrongful disclosures of sensitive health data that can lead to discrimination and stigmatization against individuals. Public health practitioners, on the other hand, seek regular, ongoing access to and use of identifiable health information to accomplish important (...) public health objectives. The collection and use of identifiable health data by federal, tribal, state, and local health authorities support nearly all public health functions and goals.Identifiable health data are the lifeblood of public health practice. When aggregated, these data help authorities monitor the incidence, patterns, and trends of injury and disease in populations. Health data are acquired by public health authorities through testing, screening, and treatment programs. (shrink)

To address complexity information fusion problems involving fuzzy and grey uncertainty information, we develop prioritized averaging aggregation operator and Bonferroni mean aggregation operator with grey linguistic 2-tuple variables and apply them to design a new decision-making scheme. First, the grey linguistic 2-tuple prioritized averaging operator is developed to characterize the prioritization relationship among experts and employed to fuse experts’ information into an overall opinion. Second, we establish dual generalized grey linguistic 2-tuple weighted Bonferroni mean operator (...) to capture the interrelationship among any attribute subsets, which can be reduced to some conventional operators by adjusting parameter vector. On that basis, a flexible group decision-making approach with fuzzy and grey information is designed and applied to an evaluation problem, in which grey relationship analysis method and a linear programming model are combined to extract attribute weights from partially known attribute information. Furthermore, an illustrative example is employed to illustrate the practicality and flexibility of the designed method by conducting the related comparative studies. (shrink)

Background Informed consent is an integral component of good medical practice. Many researchers have investigated measures to improve the quality of informed consent, but it is not clear which techniques work best and why. To address this problem, we propose developing a core outcome set to evaluate interventions designed to improve the consent process for surgery in adult patients with capacity. Part of this process involves reviewing existing research that has reported what is important to patients and doctors in the (...) informed consent process. Methods This qualitative synthesis comprises four phases: identification of published papers and determining their relevance; appraisal of the quality of the papers; identification and summary of the key findings from each paper while determining the definitiveness of each finding against the primary data; comparison of key themes between papers such that findings are linked across studies. Results Searches of bibliographic databases returned 11,073 titles. Of these, 16 studies met the inclusion criteria. Studies were published between 1996 and 2016 and included a total of 367 patients and 74 health care providers. Thirteen studies collected data using in-depth interviews and constant comparison was the most common means of qualitative analysis. A total of 94 findings were extracted from the primary papers and divided into 17 categories and ultimately 6 synthesised findings related to: patient characteristics, knowledge, communication, the model patient, trust and decision making. Conclusions This qualitative meta-aggregation is the first to examine the issue of informed consent for surgery. It has revealed several outcomes deemed important to capture by patients and clinicians when evaluating the quality of a consent process. Some of these outcomes have not been examined previously in research comparing methods for informed consent. This review is an important step in the development of a COS to evaluate interventions designed to improve the consent process for surgery. Registration The study protocol was registered on the international prospective register for systematic reviews. (shrink)

We can formalize judgments as logical formulas. Judgment aggregation deals with judgments of several agents, which need to be aggregated to a collective judgment. There are several logical formalizations of judgment aggregation. This paper focuses on a modal formalization which nicely expresses classical properties of judgment aggregation rules and famous results of social choice theory, like Arrow’s impossibility theorem. A natural deduction system for modal logic of judgment aggregation is presented in this paper. The system is (...) sound and complete. As an example of derivation, a formal proof of Arrow’s impossibility theorem is given. (shrink)

Most sources providing information on infant feeding strongly recommend breastfeeding. The WHO and UNICEF recommend that women breastfeed their babies and that health professionals promote breastfeeding. This creates severe pressure on women to breastfeed, a pressure which is ethically questionable since many women have physical or emotional problems with breastfeeding. In this article, we use insights from the ethics of risk to criticize the current breastfeeding policy. We argue that there are problems related to balancing aggregate wellbeing versus individual (...) wellbeing, that not enough attention is paid to alternatives, that women’s emotions and their need for free choice should be considered and that issues of equity are currently overlooked. We also criticize the way scientific information is presented in the current policy. We conclude that the official sources of information on infant feeding should be revised. Information should be more nuanced and designed to support mothers, and families in making a free choice on what is the best way to feed their babies. (shrink)

The partitioned Bonferroni mean operator can efficiently aggregate inputs, which are divided into parts based on their interrelationships. To date, it has not been used to aggregate linguistic Pythagorean fuzzy numbers. In this paper, we extend the PBM operator and partitioned geometric Bonferroni mean operator to the linguistic Pythagorean fuzzy sets and use them to develop a novel multiattribute group decision-making model under the linguistic Pythagorean fuzzy environment. We first define some novel operational laws for LPFNs, which take into consideration (...) the interactions between the membership degree and nonmembership degree from two different LPFNs. Based on these novel operational laws, we put forward the interaction PBM operator, the weighted interaction PBM operator, the interaction PGBM operator, and the weighted interaction PGBM operator. Then, we study some properties of these proposed operators and discuss their special cases. Based on the proposed LPFWIPBM and LPFWIPGBM operators, a novel multiattribute group decision-making model is developed to process the linguistic Pythagorean fuzzy information. Finally, some illustrative examples are introduced to compare our proposed methods with the existing ones. (shrink)

In the biomedical context, policy makers face a large amount of potentially discordant evidence from different sources. This prompts the question of how this evidence should be aggregated in the interests of best-informed policy recommendations. The starting point of our discussion is Hunter and Williams’ recent work on an automated aggregation method for medical evidence. Our negative claim is that it is far from clear what the relevant criteria for evaluating an evidence aggregator of this sort are. What is (...) the appropriate balance between explicitly coded algorithms and implicit reasoning involved, for instance, in the packaging of input evidence? In short: What is the optimal degree of ‘automation’? On the positive side: We propose the ability to perform an adequate robustness analysis as the focal criterion, primarily because it directs efforts to what is most important, namely, the structure of the algorithm and the appropriate extent of automation. Moreover, where there are resource constraints on the aggregation process, one must also consider what balance between volume of evidence and accuracy in the treatment of individual evidence best facilitates inference. There is no prerogative to aggregate the total evidence available if this would in fact reduce overall accuracy. (shrink)

The constitution of a collective judgment is analyzed from a contractarian point of view. The optimal collective judgment is defined as the one that maximizes the sum of the utility each member gets from the collective adoption of that judgment. It is argued that judgment aggregation is a different process from the aggregation of information and public deliberation. This entails that the adoption of a collective judgment should not make any rational member of the group change her (...) individual opinion, and so the collective judgment can not have any kind of epistemic superiority over the individual ones. ‡The author acknowledges Spanish Government's research projects HUM2005–01686/FISO and HUM2005-25447-E, as well as the grant PR2006-0108 which allowed a three months stay at the Helsinki Collegium for Advanced Studies, in which a big part of this paper was written. †To contact the author, please write to: Universidad Nacional de Educación a Distancia, Dpto. de Lógica, Historia y F. de la ciencia, Humanidades, Paseo de Senda del rey 7, 28040 Madrid, Spain; e-mail: [email protected]. (shrink)

We introduce a conceptual model for reaching group decisions. Our model extends a well-known, single-agent cognitive model, the recognition-primed decision (RPD) model. The RPD model includes a recognition phase and an evaluation phase. Group extensions of the RPD model, applicable to a group of RPD agents, have been considered in the literature, however the proposed models do not formalize how distributed and possibly inconsistent information can be combined in either phase. We show how such information can be utilized (...) by aggregating it using a specific social choice method, namely judgment aggregation. Our model is applicable to hierarchical groups of agents containing at least one RPD agent. (shrink)

We show that Bayesian ex post aggregation is unstable with respect to refinements. Suppose a group of Bayesians use ex post aggregation. Since it is a joint problem, each agent’s problem is captured by the same model, but probabilities and utilities may vary. If they analyze the same situation in more detail, their refined analysis should preserve their preferences among acts. However, ex post aggregation could bring about a preference reversal on the group level. Ex post (...) class='Hi'>aggregation thus depends on how much information is used and may keep oscillating (‘‘flipping’’) as one keeps adding more information. (shrink)

Applying mild methods of preparation, part of the ribosomes of rabbit reticulocytes are found in aggregates (later called polyribosomes) of up to six ribosomal units. Upon treatment with RNA-ase, they desintegrate into single ribosomes. The fast-sedimenting aggregates are found to be more active in protein synthesis in terms of incorporation of radioactive amino acids, whereas the single ribosomes are more receptive to stimulation by the artificial messenger RNA poly-U. The findings indicate that the linkage of ribosomes into aggregates is due (...) to the messenger RNA. They support a tape-reading mechanism of protein synthesis whereby growth of the peptide chain is accompanied by shifting the active site of the ribosome from one coding group of nucleotides of the messenger RNA to the next. (shrink)

BackgroundBayesian estimation with informative priors permits updating previous findings with new data, thus generating cumulative knowledge. To reduce subjectivity in the process, the present study emphasizes how to systematically weigh and specify informative priors and highlights the use of different aggregation methods using an empirical example that examined whether observed mother-adolescent positive and negative interaction behavior mediate the associations between maternal and adolescent internalizing symptoms across early to mid-adolescence in a 3-year longitudinal multi-method design.MethodsThe sample consisted of 102 mother-adolescent (...) dyads. Mothers and adolescents reported on their internalizing symptoms and their interaction behaviors were observed during a conflict task. We systematically searched for previous studies and used an expert-informed weighting system to account for their relevance. Subsequently, we aggregated the priors using three methods: linear pooling, logarithmic pooling, and fitting a normal distribution to the linear pool by means of maximum likelihood estimation. We compared the impact of the three differently specified informative priors and default priors on the prior predictive distribution, shrinkage, and the posterior estimates.ResultsThe prior predictive distributions for the three informative priors were quite similar and centered around the observed data mean. The shrinkage results showed that the logarithmic pooled priors were least affected by the data. Most posterior estimates were similar across the different priors. Some previous studies contained extremely specific information, resulting in bimodal posterior distributions for the analyses with linear pooled prior distributions. The posteriors following the fitted normal priors and default priors were very similar. Overall, we found that maternal, but not adolescent, internalizing symptoms predicted subsequent mother-adolescent interaction behavior, whereas negative interaction behavior seemed to predict subsequent internalizing symptoms. Evidence regarding mediation effects remained limited.ConclusionA systematic search for previous information and an expert-built weighting system contribute to a clear specification of power priors. How information from multiple previous studies should be included in the prior depends on theoretical considerations, and may also be affected by pragmatic considerations regarding the impact of the previous results at hand. (shrink)

Conceptual constructive models are a type of scientific model that can be used to construct or reshape the target phenomenon conceptually. Though it has received scant attention from the philosophers, it raises an intriguing issue of how a conceptual constructive model can construct the target phenomenon in a conceptual way. Proponents of the conception of conceptual constructive models are not being explicit about the application of the constructive force of a model in the target construction. It is far from clear (...) that how a conceptual constructive model exerts its constructive force on the constructed phenomenon of interest. Consequently, the function and the epistemic status of a conceptual constructive model are dubious at best. Making use of the conception of abstraction-as-aggregation, I argue that a conceptual constructive model can be used to construct the phenomenon of interest conceptually via a two-step process of abstraction: (1) abstracting away the lower-level details; and (2) aggregating the relevant information into a higher-level composite element. I contend that this process of abstraction, which is not playing the representational role as in a typical representational model, confers the constructive force on a model. (shrink)

This article’s purpose is to defend the depiction of ordinary-sized physical objects as mereological aggregates (MAs), to clarify what the ontology of an MA is, and to show why mereological essentialism (ME) applies to MAs that seem to be ubiquitous if we are to adopt what Frank Jackson calls “Serious Metaphysics” and refuse to broaden our ontology beyond what is (allegedly) bequeathed to us by physics and chemistry. To accomplish this goal, first, I clarify certain background issues that inform what (...) follows and I identify certain constraints that relate to the contemporary ambivalence towards ME. Second, I present a primer on Husserlian mereology that provides a superior account of parts and wholes than the inadequate approach identified in the previous section. Third, I will offer a defense of ME as the correct approach to providing an ontological account of MAs. Finally, I will evaluate two defeaters against my thesis. (shrink)

The neutrosophic cubic hesitant fuzzy set can efficiently handle the complex information in a decision-making problem because it combines the advantages of the neutrosophic cubic set and the hesitant fuzzy set. The algebraic operations based on Dombi norms and co-norms are more flexible than the usual algebraic operations as they involve an operational parameter. First, this paper establishes Dombi algebraic operational laws, score functions, and similarity measures in neutrosophic cubic hesitant fuzzy sets. Then, we proposed Dombi exponential operational laws (...) in which the exponents are neutrosophic cubic hesitant fuzzy values and bases are positive real numbers. To use neutrosophic cubic hesitant fuzzy sets in decision-making, we are developing Dombi exponential aggregation operators in the current study. In the end, we present applications of exponential aggregation operators in multiattribute decision-making problems. (shrink)