Stochastic forecasts in complex environments can benefit from combining the estimates of large groups of forecasters (“judges”). But aggregating multiple opinions faces several challenges. First, human judges are notoriously incoherent when their forecasts involve logically complex events. Second, individual judges may have specialized knowledge, so different judges may produce forecasts for different events. Third, the credibility of individual judges might vary, and one would like to pay greater attention to more trustworthy forecasts. These considerations limit the value of simple aggregation (...) methods like linear averaging. In this paper, a new algorithm is proposed for combining probabilistic assessments from a large pool of judges. Two measures of a judge’s likely credibility are introduced and used in the algorithm to determine the judge’s weight in aggregation. The algorithm was tested on a data set of nearly half a million probability estimates of events related to the 2008 U.S. presidential election (∼ 16000 judges). (shrink)

��The Coherent Approximation Principle (CAP) is a method for aggregating forecasts of probability from a group of judges by enforcing coherence with minimal adjustment. This paper explores two methods to further improve the forecasting accuracy within the CAP framework and proposes practical algorithms that implement them. These methods allow flexibility to add fixed constraints to the coherentization process and compensate for the psychological bias present in probability estimates from human judges. The algorithms were tested on a data set of nearly (...) half a million probability estimates of events related to the 2008 U.S. presidential election (from about 16000 judges). The results show that both methods improve the stochastic accuracy of the aggregated forecasts compared to using simple CAP. (shrink)

Background The use of lengthy, detailed, and complex informed consent forms is of paramount concern in biomedical research as it may not truly promote the rights and interests of research participants. The extent of information in ICFs has been the subject of debates for decades; however, no clear guidance is given. Thus, the objective of this study was to determine the perspectives of research participants about the type and extent of information they need when they are invited to participate in (...) biomedical research. Methods This multi-center, cross-sectional, descriptive survey was conducted at 54 study sites in seven Asia-Pacific countries. A modified Likert-scale questionnaire was used to determine the importance of each element in the ICF among research participants of a biomedical study, with an anchored rating scale from 1 to 5. Results Of the 2484 questionnaires distributed, 2113 were returned. The majority of respondents considered most elements required in the ICF to be ‘moderately important’ to ‘very important’ for their decision making. Major foreseeable risk, direct benefit, and common adverse effects of the intervention were considered to be of most concerned elements in the ICF. Conclusions Research participants would like to be informed of the ICF elements required by ethical guidelines and regulations; however, the importance of each element varied, e.g., risk and benefit associated with research participants were considered to be more important than the general nature or technical details of research. Using a participant-oriented approach by providing more details of the participant-interested elements while avoiding unnecessarily lengthy details of other less important elements would enhance the quality of the ICF. (shrink)

This paper analyzes individual probabilistic predictions of state outcomes in the 2008 U.S. presidential election. Employing an original survey of more than 19,000 respondents, ours is the first study of electoral forecasting to involve multiple subnational predictions and to incorporate the influence of respondents’ home states. We relate a range of demographic, political, and cognitive variables to individual accuracy and predictions, as well as to how accuracy improved over time. We find strong support for wishful thinking bias in expectations, as (...) Republicans gave higher probabilities to McCain victories and were worse at overall prediction. In addition, we find that respondents living in states with higher vote shares for Obama performed better at prediction and displayed less wishful thinking bias. We conclude by showing that suitable aggregations of our respondents’ predictions outperformed Intrade (a prediction market) and fivethirtyeight.com (a poll-based forecast) at most points in time. (shrink)

. Network data analysis helps in capturing node usage behavior. Existing algorithms use reduced feature set to manage high runtime complexity. Ignoring features may increase classification errors. This paper presents a model, allowing classification of network traffic, while considering all the relevant features. Learning phase partitions training sample on values of the respective features. This creates equivalence classes related to m features. During classification, each feature value of the test instance results in picking one set from equivalence class generated during (...) learning. Algorithm captures new behavior in semi-supervised incremental learning mode. For problems having m features and n training samples the model has incremental learning complexity of and average classification complexity is of the order. (shrink)

As is well known, the Kāśikāvṛtti is the oldest extant rule-by-rule commentary on the Aṣṭādhyāyī of Pāṇini. Two major commentaries on it are available, the Nyāsa from the eighth century and the Padamañjarī, most likely from the eleventh century. In this article we focus on the term pradeśa, which is a familiar feature of the printed editions of the Kāśikāvṛtti on the sañjñā sūtras of the Aṣṭādhyāyī. A closer examination, however, shows that the sentence “Xpradeśāḥ — X... ity evamādayaḥ” is (...) not met with in either of the two commentaries. This has consequences for our understanding of the textual transmission of the Kāśikāvṛtti. (shrink)

In light of the recent events of terrorism and publicized cases of mass slayings and serial killings, there have been calls from the public and policy-makers alike for neuroscience and neurotechnology (neuroS/T) to be employed to intervene in ways that define and assess, if not prevent, such wanton acts of aggression and violence. Ongoing advancements in assessment neuroS/T have enabled heretofore unparalleled capabilities to evaluate the structure and function of the brain, yet each and all are constrained by certain technical (...) and practical limitations. In this paper, we present an overview of the capabilities and constraints of current assessment neuroS/T, address neuro-ethical and legal issues fostered by the use and potential misuse of these approaches, and discuss how neuroethics may inform science and the law to guide right and sound applications of neuroS/T to “deliver us from evil” while not being led into temptations of ampliative claims and inapt use. (shrink)

In _Reliable Reasoning_, Gilbert Harman and Sanjeev Kulkarni -- a philosopher and an engineer -- argue that philosophy and cognitive science can benefit from statistical learning theory, the theory that lies behind recent advances in machine learning. The philosophical problem of induction, for example, is in part about the reliability of inductive reasoning, where the reliability of a method is measured by its statistically expected percentage of errors -- a central topic in SLT. After discussing philosophical attempts to evade (...) the problem of induction, Harman and Kulkarni provide an admirably clear account of the basic framework of SLT and its implications for inductive reasoning. They explain the Vapnik-Chervonenkis dimension of a set of hypotheses and distinguish two kinds of inductive reasoning. The authors discuss various topics in machine learning, including nearest-neighbor methods, neural networks, and support vector machines. Finally, they describe transductive reasoning and suggest possible new models of human reasoning suggested by developments in SLT. (shrink)

Background and rationale Several factors that motivate individuals to participate in non-therapeutic studies have been identified. This study was conducted as limited data is available regarding these motivations from developing countries. Methods This was a single-centre study conducted over 4 months in which a questionnaire was administered to 102 healthy participants and 16 patient participants who had earlier taken part in non-therapeutic studies at our centre. Descriptive statistics and univariate analysis were used to analyse data. Results The most common motivation (...) among healthy participants was financial reward (65%) followed by altruism, free medical check up, curiosity and personal health benefit. Patient participants, however, most commonly said they consented to take part in the trial as they were ‘invited to participate by the treating physician’ (88%). In comparison with the patient participants, healthy participants were more likely to be satisfied with the financial reward (p=0.02), and recommend participation in studies to friends or relatives (p=0.0013). Conclusions The most common motivating factor to participate in non-therapeutic studies appears to be different for healthy participants (financial reward) and patient participants (invitation to participate by the physician). Participants also felt that adequate information and care was given to them during the trial, and that they would participate in future clinical studies, and would also recommend such studies to their friends. (shrink)

The article focuses on the ‘meaningfulness in work’ concept and addresses three theoretical gaps by investigating ‘meaningfulness in work’ from the perspective of Heidegger’s ‘authenticity’ and ‘Dasein’ constructs as well as virtue ethics. First, it adapts Heideggerian phenomenology and argues that meaningfulness in work may be revealed to an ‘authentic’ employee, while they performs everyday activities by ‘existing’ in their world and discovers their Dasein. Second, it emphasizes the normative, as opposed to instrumental implications of meaningfulness and invokes virtue ethics (...) towards this end. Third, it integrates the Heideggerian approach with virtue ethics to describe how an ‘authentic’ and ‘virtuous’ employee may achieve meaningfulness in work (conceptualized as ‘eudaimonia’). An ‘authentic virtuous employee’ ‘exists in their world’ and discovers what is truly meaningful in work to them. They also displays temperance and courage in terms of closing the gaps between current and desired levels of meaningfulness in work, and continually contemplates it. We describe a ‘professional’ as an example of an ‘authentic virtuous employee’. (shrink)

Hans Krebs' discovery, in 1932, of the urea cycle was a major event in biochemistry. This article describes a program, KEKADA, which models the heuristics Hans Krebs used in this discovery. KEKADA reacts to surprises, formulates explanations, and carries out experiments in the same manner as the evidence in the form of laboratory notebooks and interviews indicates Hans Krebs did. Furthermore, we answer a number of questions about the nature of the heuristics used by Krebs, in particular: How domain‐specific are (...) the heuristics? To what extent are they idiosyncratic to Krebs? To what extent do they represent general strategies of problem‐solving search?The relative generality of KEKADA allows us to view the control structure of KEKADA and its domain‐independent heuristics as a model of scientific experimentation that should apply over a broad domain. (shrink)

The problem of induction is sometimes motivated via a comparison between rules of induction and rules of deduction. Valid deductive rules are necessarily truth preserving, while inductive rules are not.

Papers presented at two national seminars on Language science and cognition and Epistemology and cognition held at Hyderabad.

In this paper, we develop a conceptual framework of the intra-firm transfer of best practices in moral reasoning by integrating three streams of literature: internal knowledge transfer in strategic management, moral reasoning and epistemology in philosophy and business ethics, and leader–member exchange in human resource management. We propose that characteristics of moral reasoning (nature of moral knowledge, tacitness of moral reasoning and causal ambiguity), source characteristics (moral development of leaders), target characteristics (integrity capacity and moral development of subordinates), leader–member exchange (...) and internal ethical climate influence the transfer of best practices in moral reasoning. (shrink)

This paper addresses the conflicting environmental interests of a firm and the community, an important stakeholder. The short-term profit maximization objective of a firm may stand in contrast with what the community wants – a "safe and clean environment". This paper argues that the information regarding the environmental impact of a firm's products, processes, and waste may be asymmetrically distributed between the firm and the community. The resultant information asymmetry may influence the probability of a firm acting opportunistically, and ultimately, (...) a firm's ethical behavior. The paper identifies information asymmetry between a firm and community, as well as that within the community. The perceived information asymmetry across various community segments may perhaps be a determinant of environmental discrimination. The paper further contends that information asymmetry may diminish in the long run. Finally it examines the implications of information asymmetry for firms and government policy. (shrink)

Active networking is an exciting new paradigm in digital networking that has the potential to revolutionize the manner in which communication takes place. It is an emerging technology, one in which new ideas are constantly being formulated and new topics of research are springing up even as this book is being written. This technology is very likely to appeal to a broad spectrum of users from academia and industry. Therefore, this book was written in a way that enables all these (...) groups to understand the impact of active networking in their sphere of interest. Information services managers, network administrators, and e-commerce developers would like to know the potential benefits of the new technology to their businesses, networks, and applications. The book introduces the basic active networking paradigm and its potential impacts on the future of information handling in general and on communications in particular. This is useful for forward-looking businesses that wish to actively participate in the development of active networks and ensure a head start in the integration of the technology in their future products, be they applications or networks. Areas in which active networking is likely to make significant impact are identified, and the reader is pointed to any related ongoing research efforts in the area. The book also provides a deeper insight into the active networking model for students and researchers, who seek challenging topics that define or extend frontiers of the technology. It describes basic components of the model, explains some of the terms used by the active networking community, and provides the reader with taxonomy of the research being conducted at the time this book was written. Current efforts are classified based on typical research areas such as mobility, security, and management. The intent is to introduce the serious reader to the background regarding some of the models adopted by the community, to outline outstanding issues concerning active networking, and to provide a snapshot of the fast-changing landscape in active networking research. Management is a very important issue in active networks because of its open nature. The latter half of the book explains the architectural concepts of a model for managing active networks and the motivation for a reference model that addresses limitations of the current network management framework by leveraging the powerful features of active networking to develop an integrated framework. It also describes a novel application enabled by active network technology called the Active Virtual Network Management Prediction (AVNMP) algorithm. AVNMP is a pro-active management system; in other words, it provides the ability to solve a potential problem before it impacts the system by modeling network devices within the network itself and running that model ahead of real time. (shrink)

Active networking is an exciting new paradigm in digital networking that has the potential to revolutionize the manner in which communication takes place. It is an emerging technology, one in which new ideas are constantly being formulated and new topics of research are springing up even as this book is being written. This technology is very likely to appeal to a broad spectrum of users from academia and industry. Therefore, this book was written in a way that enables all these (...) groups to understand the impact of active networking in their sphere of interest. Information services managers, network administrators, and e-commerce developers would like to know the potential benefits of the new technology to their businesses, networks, and applications. The book introduces the basic active networking paradigm and its potential impacts on the future of information handling in general and on communications in particular. This is useful for forward-looking businesses that wish to actively participate in the development of active networks and ensure a head start in the integration of the technology in their future products, be they applications or networks. Areas in which active networking is likely to make significant impact are identified, and the reader is pointed to any related ongoing research efforts in the area. The book also provides a deeper insight into the active networking model for students and researchers, who seek challenging topics that define or extend frontiers of the technology. It describes basic components of the model, explains some of the terms used by the active networking community, and provides the reader with taxonomy of the research being conducted at the time this book was written. Current efforts are classified based on typical research areas such as mobility, security, and management. The intent is to introduce the serious reader to the background regarding some of the models adopted by the community, to outline outstanding issues concerning active networking, and to provide a snapshot of the fast-changing landscape in active networking research. Management is a very important issue in active networks because of its open nature. The latter half of the book explains the architectural concepts of a model for managing active networks and the motivation for a reference model that addresses limitations of the current network management framework by leveraging the powerful features of active networking to develop an integrated framework. It also describes a novel application enabled by active network technology called the Active Virtual Network Management Prediction (AVNMP) algorithm. AVNMP is a proactive management system; in other words, it provides the ability to solve a potential problem before it impacts the system by modeling network devices within the network itself and running that model ahead of real time. (shrink)

This paper addresses the conflicting environmental interests of a firm and the community, an important stakeholder. The short-term profit maximization objective of a firm may stand in contrast with what the community wants – a "safe and clean environment". This paper argues that the information regarding the environmental impact of a firm's products, processes, and waste may be asymmetrically distributed between the firm and the community. The resultant information asymmetry may influence the probability of a firm acting opportunistically, and ultimately, (...) a firm's ethical behavior. The paper identifies information asymmetry between a firm and community, as well as that within the community. The perceived information asymmetry across various community segments may perhaps be a determinant of environmental discrimination. The paper further contends that information asymmetry may diminish in the long run. Finally it examines the implications of information asymmetry for firms and government policy. (shrink)

This research investigates the nature of phatic communion in instant messaging interactions. It adopts and expands Jakobson’s much-quoted definition according to which ‘phatic’ is the language in an interaction whose primary purpose is to maintain contact between the speakers. Adapting conversation analysis for the study of textual interactions, the research observes the linguistic means used by interlocutors to signal attention, interest, and agreement – these being identified as important constituents of contact. The corpus comprises 60 chats, collected from 20 participants (...) who chat in a mixture of English and Indian languages such as Marathi and Hindi. Openings, middles, and closings of these interactions are analyzed to study the ways in which participants establish, maintain, and terminate contact. The use of various linguistic means in these interactions such as back-channels, evaluations, expressives, and questions draws attention to a significant amount of interactional work done by interlocutors towards maintaining contact. (shrink)

Although evidence-based medicine (EBM) has gained prominence in current medical practice and research, it has also had to deal with a number of problems and inconsistencies. For example, how do clinicians reconcile discordant results of randomized trials or how do they apply results of randomized trials to individual patients? In an attempt to examine such problems in a structured way, this essay describes EBM within a philosophical framework of science. Using this approach, some of the problems and challenges faced by (...) EBM can be explained at a more fundamental level. As well, by employing a similar description of the competing alternative research tradition of clinical medicine, this essay not only highlights the philosophical differences between these two modes of medical practice, but suggests that they, in fact, play a de facto complementary role in current clinical medicine. (shrink)

Statistical Learning Theory (e.g., Hastie et al., 2001; Vapnik, 1998, 2000, 2006) is the basic theory behind contemporary machine learning and data-mining. We suggest that the theory provides an excellent framework for philosophical thinking about inductive inference.

Like Glenn Shafer, we are nostalgic for the time when “philosophers, mathematicians, and scientists interested in probability, induction, and scientific methodology talked with each other more than they do now”, [p.10]. 1 Shafer goes on to mention other relevant contemporary communities. He himself has been at the interface of many of these communities while at the same time making major contributions to them and this very symposium represents something of that desired discussion. We begin with a couple of general points (...) about issues several commentators have raised and then discuss other more particular issues. (shrink)