At the heart of Mizrahi’s project lies a sociological narrative concerning the recent history of philosophers’ negative attitudes towards scientism. Critics (e.g. de Ridder (2019), Wilson (2019) and Bryant (2020)), have detected various empirical inadequacies in Mizrahi’s methodology for discussing these attitudes. Bryant (2020) points out one of the main pertinent methodological deficiencies here, namely that the mere appearance of the word ‘scientism’ in a text does not suffice in determining whether the author feels threatened by it. Not all philosophers (...) use the term in ‘inherently negative’ (29) or pejorative ways. In this paper, I not only corroborate Bryant’s critical claim, but argue that Mizrahi’s response to this part of Bryant’s objection is inadequate. (shrink)

Everywhere in the world, and in every period of human history, it has been common for energy decisions to be made in an ethically haphazard manner. With growing population pressure and increasing demand for energy, this approach is no longer viable. We believe that decision makers must include ethical considerations in energy decisions more routinely and systematically. To this end, we propose an applied ethics framework that accommodates principles from three classical ethical theories—virtue ethics, deontology, consequentialism, and two Native American (...) ethics (Lakota and Navajo)—all considered from the perspectives of the impacted communities. We illustrate this framework by evaluating five recent energy decisions: the Dakota Access Pipeline, the Navajo Nation’s possible transition from coal to solar, hydraulic fracturing in Pennsylvania, uranium mining in Virginia, and the construction of the Xiaolangdi Dam in China. An applied ethics framework is preferable to existing ethical analyses because it can serve to sharpen arguments for (un)ethical decisions and action. Rather than treat ethical reasoning as a matter of opinion, we argue that applying ethical principles in a universal and standardized way adds rigor to energy sector decisions by presenting a position available for objective scrutiny. Because our framework identifies which aspects of a targeted action (if any) must adjust to improve ethical merit, it can serve as a practical tool for improving decision-making as we enter a new era of energy transitions. (shrink)

Objective: to evaluate CANLPH score and systemic immune inflammation index (SII) in patients with symptomatic rheumatic mitral stenosis (MS) undergoing percutaneous mitral balloon valvuloplasty (PMBV). -/- Methods: 62 patients who underwent PMBV in our clinic between 2018 and 2021 were included retrospectively. The patients were divided into 2 groups according to echo score. The CANLPH score was calculated from the cut-off values of C-reactive protein to albumin ratio (CAR), neutrophil to lymphocyte ratio (NLR) and platelet to hemoglobin ratio (PHR), determined (...) with the Youden index and SII by the formula platelet x neutrophil/lymphocyte. P <0.05 was considered statistically significant. -/- Results: The mean age of the patients was 44.5±10.4 years (40 female, 64.5%). The mean values of SII and CANLPH scores were higher in the Echo score >8 group (p <0.001, both). The mean mitral gradient before and after PMBV was 12.6±5.7mm Hg and 5.0±2.4 mm Hg, and the mean valve area was 1.12±0.27 cm2 and 1.85±0.29 cm2. A statistically significant and negative correlation was observed between the gradient decrease after the procedure and the CANLPH score and SII (r=-0.426, p=0.001 and r=-0.418, p=0.001, respectively). In receiver operating characteristic (ROC) curve analysis, it was concluded that the ability of CANPLH score to predict the higher Echo scores was noninferior to SII with an area under curve (AUC:0.820 (0.701-0.906) and AUC:0.786 (0.664-0.880), z statistics 0.576 and p=0.564. -/- Conclusion: SII and CANLPH scores are correlated with Echo score. A significant negative relationship was found with both biomarkers and gradient decrease after the PMBV. (shrink)

Data mining possess a significant threat to ethics, privacy, and legality, especially when we consider the fact that data mining makes it difficult for an individual or consumer (in the case of a company) to control accessibility and usage of his data. Individuals should be able to control how his/ her data in the data warehouse is being access and utilize while at the same time providing enabling environment which enforces legality, privacy and ethicality on data scientists, or (...) data engineer during data mining process. This paper review issues of legality, privacy, and ethicality in data mining, review processes of Data mining, and also proposes solution to current ethical and privacy issue in data mining. It introduces a new method which enforces data mining without infringing on the privacy of individual or consumer whose data are being used. The sole aim of this paper is to propose a new method of mining data which restricts scientists within the constraints of legality, privacy, and ethicality. (shrink)

In this paper we focus on what is referred to as the ‘mineness’ of experience, that is, the intimate familiarity we have with our own thoughts, perceptions, and emotions. Most accounts characterize mineness in terms of an experiential dimension, the first-person givenness of experience, that is subsumed under the notion of minimal self-consciousness or a ‘minimal self’. We argue that this account faces problems and develop an alternative account of mineness in terms of the coherence of experiences with what we (...) label an ‘embodied biography’. Building on a near consensus among consciousness researchers over the function of consciousness as integrating infor- mation, we argue that the phenomenology of mineness consists in the absence of any further thought on top of the experience itself. Finally we argue that this non-phenomenological account of mineness fits well with existing data on pathologies of mineness such as delusions of thought insertion. (shrink)

How can different individuals' probability assignments to some events be aggregated into a collective probability assignment? Classic results on this problem assume that the set of relevant events -- the agenda -- is a sigma-algebra and is thus closed under disjunction (union) and conjunction (intersection). We drop this demanding assumption and explore probabilistic opinion pooling on general agendas. One might be interested in the probability of rain and that of an interest-rate increase, but not in the probability of rain (...) or an interest-rate increase. We characterize linear pooling and neutral pooling for general agendas, with classic results as special cases for agendas that are sigma-algebras. As an illustrative application, we also consider probabilistic preference aggregation. Finally, we compare our results with existing results on binary judgment aggregation and Arrovian preference aggregation. This paper is the first of two self-contained, but technically related companion papers inspired by binary judgment-aggregation theory. (shrink)

Scalability, efficiency, and security had been a persistent problem over the years in data mining, several techniques had been proposed and implemented but none had been able to solve the problem of scalability, efficiency and security from cloud computing. In this research, we solve the problem scalability, efficiency and security in data mining over cloud computing by using a restful web services and combination of different technologies and tools, our model was trained by using different machine learning algorithm, (...) and finally using different validation and cross-validation methods to compare and validate our results. We build, train, test and deploy our model by restful API services which can be called through an endpoint, and with very high accuracy and huge success. (shrink)

In the end of the course the student will be able to: • Understand the functioning of data mining tools and their contributions to managerial professions • Master the use of dynamic search tools on the open web and on the dark web. • Use the proper tools according to the objectives sought • Master the latest trends and innovations in Business Analytics • Analyze the opportunities offered in terms of data mining by artificial intelligence and IoT.

In this paper we look at the manual analysis of arguments and how this compares to the current state of automatic argument analysis. These considerations are used to develop a new approach combining a machine learning algorithm to extract propositions from text, with a topic model to determine argument structure. The results of this method are compared to a manual analysis.

We can have credences in an infinite number of propositions—that is, our opinion set can be infinite. Accuracy-first epistemologists have devoted themselves to evaluating credal states with the help of the concept of ‘accuracy’. Unfortunately, under several innocuous assumptions, infinite opinion sets yield several undesirable results, some of which are even fatal, to accuracy-first epistemology. Moreover, accuracy-first epistemologists cannot circumvent these difficulties in any standard way. In this regard, we will suggest a non-standard approach, called a relativistic approach, (...) to accuracy-first epistemology and show that such an approach can successfully circumvent undesirable results while having some advantages over the standard approach. (shrink)

How can different individuals' probability functions on a given sigma-algebra of events be aggregated into a collective probability function? Classic approaches to this problem often require 'event-wise independence': the collective probability for each event should depend only on the individuals' probabilities for that event. In practice, however, some events may be 'basic' and others 'derivative', so that it makes sense first to aggregate the probabilities for the former and then to let these constrain the probabilities for the latter. We formalize (...) this idea by introducing a 'premise-based' approach to probabilistic opinion pooling, and show that, under a variety of assumptions, it leads to linear or neutral opinion pooling on the 'premises'. This paper is the second of two self-contained, but technically related companion papers inspired by binary judgment-aggregation theory. (shrink)

Suppose several individuals (e.g., experts on a panel) each assign probabilities to some events. How can these individual probability assignments be aggregated into a single collective probability assignment? This article reviews several proposed solutions to this problem. We focus on three salient proposals: linear pooling (the weighted or unweighted linear averaging of probabilities), geometric pooling (the weighted or unweighted geometric averaging of probabilities), and multiplicative pooling (where probabilities are multiplied rather than averaged). We present axiomatic characterisations of each class of (...) pooling functions (most of them classic, but one new) and argue that linear pooling can be justified procedurally, but not epistemically, while the other two pooling methods can be justified epistemically. The choice between them, in turn, depends on whether the individuals' probability assignments are based on shared information or on private information. We conclude by mentioning a number of other pooling methods. (shrink)

It is a consequence of the theory of imprecise credences that there exist situations in which rational agents inevitably become less opinionated toward some propositions as they gather more evidence. The fact that an agent's imprecise credal state can dilate in this way is often treated as a strike against the imprecise approach to inductive inference. Here, we show that dilation is not a mere artifact of this approach by demonstrating that opinion loss is countenanced as rational by a (...) substantially broader class of normative theories than has been previously recognised. Specifically, we show that dilation-like phenomena arise even when one abandons the basic assumption that agents have (precise or imprecise) credences of any kind, and follows directly from bedrock norms for rational comparative confidence judgements of the form `I am at least as confident in p as I am in q'. We then use the comparative confidence framework to develop a novel understanding of what exactly gives rise to dilation-like phenomena. By considering opinion loss in this more general setting, we are able to provide a novel assessment of the prospects for an account of inductive inference that is not saddled with the inevitability of rational opinion loss. (shrink)

Democratic decision-making is often defended on grounds of the ‘wisdom of crowds’: decisions are more likely to be correct if they are based on many independent opinions, so a typical argument in social epistemology. But what does it mean to have independent opinions? Opinions can be probabilistically dependent even if individuals form their opinion in causal isolation from each other. We distinguish four probabilistic notions of opinion independence. Which of them holds depends on how individuals are causally affected (...) by environmental factors such as commonly perceived evidence. In a general theorem, we identify causal conditions guaranteeing each kind of opinion independence. These results have implications for whether and how ‘wisdom of crowds’ arguments are possible, and how truth-conducive institutions can be designed. (shrink)

What does it take for a subject to experience a personal memory as being her own? According to Fernández’ (2019) model of endorsement, this particular phenomenal quality of our memories, their “sense of mineness”, can be explained in terms of the experience of the mnemonic content as veridical. In this article, I criticize this model for two reasons: (a) the evidence that is used by Fernández to ground his theoretical proposal is dubious; and more importantly, (b) the endorsement model does (...) not accommodate many non-pathological everyday memories that preserve their sense of mineness, but whose veridicality is explicitly denied, suspected, not automatically endorsed, or neither denied nor endorsed. Finally, I sketch two alternative explanations: one also problematic, the other one more promising, and present some normative advantages of the latter. This also displays the undesirability of the endorsement model from a normative perspective. (shrink)

Election prediction by means of opinion polling is a rare empirical success story for social science. I examine the details of a prominent case, drawing two lessons of more general interest: Methodology over metaphysics. Traditional metaphysical criteria were not a useful guide to whether successful prediction would be possible; instead, the crucial thing was selecting an effective methodology. Which methodology? Success required sophisticated use of case-specific evidence from opinion polling. The pursuit of explanations via general theory or causal (...) mechanisms, by contrast, turned out to be precisely the wrong path—contrary to much recent philosophy of social science. (shrink)

Opinions are rarely binary; they can be held with different degrees of conviction, and this expanded attitude spectrum can affect the influence one opinion has on others. Our goal is to understand how different aspects of influence lead to recognizable spatio-temporal patterns of opinions and their strengths. To do this, we introduce a stochastic spatial agent-based model of opinion dynamics that includes a spectrum of opinion strengths and various possible rules for how the opinion strength of (...) one individual affects the influence that this individual has on others. Through simulations, we find that even a small amount of amplification of opinion strength through interaction with like-minded neighbors can tip the scales in favor of polarization and deadlock. (shrink)

In recent years, neuroscience has begun to transform itself into a “big data” enterprise with the importation of computational and statistical techniques from machine learning and informatics. In addition to their translational applications such as brain-computer interfaces and early diagnosis of neuropathology, these tools promise to advance new solutions to longstanding theoretical quandaries. Here I critically assess whether these promises will pay off, focusing on the application of multivariate pattern analysis (MVPA) to the problem of reverse inference. I argue that (...) MVPA does not inherently provide a new answer to classical worries about reverse inference, and that the method faces pervasive interpretive problems of its own. Further, the epistemic setting of MVPA and other decoding methods contributes to a potentially worrisome shift towards prediction and away from explanation in fundamental neuroscience. (shrink)

Patients suffering from depersonalization complain of feeling detached from their body, their mental states, and actions or even from themselves. In this chapter, I argue that depersonalization consists in the lack of a phenomenal feature that marks my experiences as mine, which is usually called “mineness,” and that the study of depersonalization constitutes a neglected yet incomparable probe to assess empirically the scope, role, and even the nature of mineness. Here is how I will proceed. After describing depersonalization (§2) and (...) arguing that it involves a lack of mineness (§3) I will confront a series of objections (§4). I will then spell out what depersonalization can teach us about the scope of mineness (§5), about its role and psychological function (§6) and even about its nature (§7). (shrink)

Ever since the era of internet had ushered in cloud computing, there had been increase in the demand for the unlimited data available through cloud computing for data analysis, pattern recognition and technology advancement. With this also bring the problem of scalability, efficiency and security threat. This research paper focuses on how data can be dynamically mine in real time for pattern detection in a secure cloud computing environment using combination of decision tree algorithm and Random Forest over a restful (...) Application Programming Interface (API). We are able to successfully Implement data mining on cloud computing bypassing or avoiding direct interaction with data warehouse and without any terminal involve by using combination of IBM Cloud storage facility, Amazing Web Service, Application Programming Interface and Window service along with a decision tree and Random Forest algorithm for our classifier. We were able to successfully bypass direct connection with the data warehouse and cloud terminal with 94% accuracy in our model. (shrink)

Scalability, efficiency, and security had been a persistent problem over the years in data mining, several techniques had been proposed and implemented but none had been able to solve the problem of scalability, efficiency and security from cloud computing. In this research, we solve the problem scalability, efficiency and security in data mining over cloud computing by using a restful web services and combination of different technologies and tools, our model was trained by using different machine learning algorithm, (...) and finally using different validation and cross-validation methods to compare and validate our results. We build, train, test and deploy our model by restful API services which can be called through an endpoint, and with very high accuracy and huge success. (shrink)

The necessary condition for the reception of art is aesthetic distance, which paradoxically relies on direct experience: one has to be there in front of the artwork, has to live the experience. Therefore, the current pandemic and the practice of social distancing, which attempts to slow it down, is a serious challenge for the arts. This text analyses the ways in which artists and the institutions which mediate art react to the conditions caused by the pandemic. I will present some (...) creative practices which turn the adversity of the pandemic into an asset (the White Cuib Facebook project and the series by Sándor Bartha). So, there are projects which mine the gap (social distancing) and use it creatively. Then I will analyze the practice of some museums and galleries, focusing on the positive examples (e.g., the “Stay at Home Museum”) as well as on the difficulties. The examined cases will reveal the fact that while the artists were able to react in creative ways to the constraints and to create artworks which point beyond the contextual value, art institutions generally attempted merely to get through this period, hoping that they would soon be able to get back to life as usual. (shrink)

Big Data is a large-sized and complex dataset, which cannot be managed using traditional data processing tools. Mining process of big data is the ability to extract valuable information from these large datasets. Association rule mining is a type of data mining process, which is indented to determine interesting associations between items and to establish a set of association rules whose support is greater than a specific threshold. The classical association rules can only be extracted from binary (...) data where an item exists in a transaction, but it fails to deal effectively with quantitative attributes, through decreasing the quality of generated association rules due to sharp boundary problems. In order to overcome the drawbacks of classical association rule mining, we propose in this research a new neutrosophic association rule algorithm. The algorithm uses a new approach for generating association rules by dealing with membership, indeterminacy, and non-membership functions of items, conducting to an efficient decision-making system by considering all vague association rules. To prove the validity of the method, we compare the fuzzy mining and the neutrosophic mining. The results show that the proposed approach increases the number of generated association rules. (shrink)

A recent systematic review of Machine Learning (ML) approaches to health data, containing over 100 studies, found that the most investigated problem was mental health (Yin et al., 2019). Relatedly, recent estimates suggest that between 165,000 and 325,000 health and wellness apps are now commercially available, with over 10,000 of those designed specifically for mental health (Carlo et al., 2019). In light of these trends, the present chapter has three aims: (1) provide an informative overview of some of the recent (...) work taking place at the intersection of text mining and mental health so that we can (2) highlight and analyze several pressing ethical issues that are arising in this rapidly growing field and (3) suggest productive directions for how these issues might be better addressed within future interdisciplinary work to ensure the responsible development of text mining approaches in psychology generally, and in mental health fields, specifically. In Section 1, we review some of the recent literature on text-mining and mental health in the contexts of traditional experimental settings, social media, and research involving electronic health records. Then, in Section 2, we introduce and discuss ethical concerns that arise before, during, and after research is conducted. Finally, in Section 3, we offer several suggestions about how ethical oversight of text-mining research might be improved to be more responsive to the concerns mapped out in Section 2. (shrink)

Historic preservation, which is a vital act for conveying people’s understanding of the past, such as events, ideas, and places to the future, allows people to preserve history for future generations. Additionally, since the historic properties are currently concentrated in urban areas, an urban-oriented approach will contribute to the issue. Hence, public awareness is a key factor that paves the way for this conservation. Public history, a history with a public audience and special methods of representation, can serve society in (...) this regard. Historical video games, which get their game objectives from the past, can be considered a form of public history, raising people’s awareness and letting them gain historical experience. While plenty of studies focused on this content with various approaches, this study takes the topic under consideration with a player-oriented focus. The research uses the Steam video game digital distribution service database to explore the existing historical games based on their genre, player scale, dimension, VR compatibility attributes, and player rating. The database includes 1,148 games published between 2002 and 2022, filtered as historical by Steam tags and sorted by player review. For the data collection, the study uses the Octoparse web scraping tool for data extraction, and for the data analysis, it uses RapidMiner Studio data mining software. The study aims to provide a framework applicable to the development of commercially playable historical video games contributing to heritage preservation by raising public awareness in the context of public history. (shrink)

"Data mining is not an invasion of privacy because access to data is only by machines, not by people": this is the argument that is investigated here. The current importance of this problem is developed in a case study of data mining in the USA for counterterrorism and other surveillance purposes. After a clarification of the relevant nature of privacy, it is argued that access by machines cannot warrant the access to further information, since the analysis will have (...) to be made either by humans or by machines that understand. It concludes that the current data mining violates the right to privacy and should be subject to the standard legal constraints for access to private information by people. (shrink)

In times of populist mistrust towards experts, it is important and the aim of the paper to ascertain the rationality of arguments from expert opinion and to reconstruct their rational foundations as well as to determine their limits. The foundational approach chosen is probabilistic. However, there are at least three correct probabilistic reconstructions of such argumentations: statistical inferences, Bayesian updating, and interpretive arguments. To solve this competition problem, the paper proposes a recourse to the arguments' justification strengths achievable in (...) the respective situation. (shrink)

Accounts of arguments from expert opinion take it for granted that expert judgments count as (defeasible) evidence for propositions, and so an argument that proceeds from premises about what an expert judges to a conclusion that the expert is probably right is a strong argument. In Mizrahi (2013), I consider a potential justification for this assumption, namely, that expert judgments are significantly more likely to be true than novice judgments, and find it wanting because of empirical evidence suggesting that (...) expert judgments under uncertainty are not significantly more likely to be true than novice judgments or even chance. In this paper, I consider another potential justification for this assumption, namely, that expert judgments are not influenced by the cognitive biases novice judgments are influenced by, and find it wanting, too, because of empirical evidence suggesting that experts are vulnerable to pretty much the same cognitive biases that novices are vulnerable to. If this is correct, then the basic assumption at the core of accounts of arguments from expert opinion, namely, that expert judgments count as (defeasible) evidence for propositions, remains unjustified. (shrink)

There are many reasons we might want to take the opinions of various individuals and pool them to give the opinions of the group they constitute. If all the individuals in the group have probabilistic opinions about the same propositions, there is a host of pooling functions we might deploy, such as linear or geometric pooling. However, there are also cases where different members of the group assign probabilities to different sets of propositions, which might overlap a lot, a little, (...) or not at all. There are far fewer proposals for how to proceed in these cases, and those there are have undesirable features. I begin by considering four proposals and arguing that they don't work. Then I'll describe my own proposal, which is intended to cover the situation in which we want to pool the individual opinions in order to ascribe an opinion to the group considered as an agent in its own right. (shrink)

In this paper, I reply to Seidel’s objections against my argument from expert performance to the effect that arguments from expert opinion are weak arguments. I clarify what Seidel takes to be unclear points in my argument and show that it withstands Seidel’s objections.

I aim to show that, contrary to standard deflationary or eliminativist theories of the self, we can argue from the phenomenology of pre-reflective self-awareness for the thesis that subjects of experience are substances. The phenomenological datum of subjectivity points to a specific metaphysical structure of our experience, that is, towards the substance view rather than the bundle or the minimal self view. Drawing on modern philosophical accounts of pre-reflective self-awareness, mineness and (self-) acquaintance, I will argue that a subject is (...) aware of being the one individual who has many experiences and that it is revealed to the subject that it is the bearer of experiences and their unifier. The subject is present in pre-reflective awareness and known as the subject of experiences, and even this minimal self-awareness gives us reason to favour the substance view. Thus, one can demonstrate how the debates on the phenomenology of pre-reflective self-awareness and the metaphysics of selfhood intersect. (shrink)

One of the negative legacies of the apartheid era is a markedly skewed mining sector that favours the established companies, and almost completely neglects small-scale mining enterprises. Though a major source of revenue for South Africa(SA), the current state of the mining sector does not directly benefit the previously disadvantaged who dominate small-scale mining. The aim of this study is to explore the support structures and success factors relevant to small scale mining entrepreneurs in South (...) Africa. To achieve this end, the qualitative research approach was utilized to collect and analyze the data. The results affirmed the availability of a comprehensive support structure for aspiring small-scale mining entrepreneurs. A number of factors not limited to having a marketing ethos, requisite business knowledge, possession of appropriate equipment, and the ability to mine effectively and efficiently were reported as being central to successful small-scale mining. Furthermore, it is acknowledged that having passion and the right work ethics worked in favour of successful small-scale entrepreneurs. (shrink)

According to the PubMed resource from the U.S. National Library of Medicine, over 750,000 scientific articles have been published in the ~5000 biomedical journals worldwide in the year 2007 alone. The vast majority of these publications include results from hypothesis-driven experimentation in overlapping biomedical research domains. Unfortunately, the sheer volume of information being generated by the biomedical research enterprise has made it virtually impossible for investigators to stay aware of the latest findings in their domain of interest, let alone to (...) be able to assimilate and mine data from related investigations for purposes of meta-analysis. While computers have the potential for assisting investigators in the extraction, management and analysis of these data, information contained in the traditional journal publication is still largely unstructured, free-text descriptions of study design, experimental application and results interpretation, making it difficult for computers to gain access to the content of what is being conveyed without significant manual intervention. In order to circumvent these roadblocks and make the most of the output from the biomedical research enterprise, a variety of related standards in knowledge representation are being developed, proposed and adopted in the biomedical community. In this chapter, we will explore the current status of efforts to develop minimum information standards for the representation of a biomedical experiment, ontologies composed of shared vocabularies assembled into subsumption hierarchical structures, and extensible relational data models that link the information components together in a machine-readable and human-useable framework for data mining purposes. (shrink)

This paper contributes to the project of articulating and defending the supra-Bayesian approach to judgment aggregation. I discuss three cases where a person is disposed to defer to two different experts, and ask how they should respond when they learn about the opinion of each. The guiding principles are that this learning should go by conditionalisation, and that they should aim to update on the evidence that the expert had updated on. But this doesn’t settle how the update on (...) pairs of experts should go, because we also need to know how the experts are related. I work through three examples showing how the results change given different prior beliefs about this relationship. (shrink)

When you have a conscious experience—such as feeling pain, watching the sunset, or thinking about your loved ones—are you aware of the experience as your own, even when you do not reflect on, think about, or attend to it? Let us say that an experience has “mineness” just in case its subject is aware of it as her own while she undergoes it. And let us call the view that all ordinary experiences have mineness “typicalism.” Recently, Guillot has offered a (...) novel argument for typicalism by leveraging the relation between self-knowledge and self-awareness. She starts by arguing that all ordinary experiences give their subjects immediate justification to believe that their experiences are their own. She then argues that this can be explained by typicalism. In this paper, I argue that her argument fails. I start by clarifying the notion of mineness and giving more details about her argument. I then explain why her argument fails by raising doubts about whether typicalism explains the target explanandum. I close by considering some implications of our discussion for self-knowledge. (shrink)

Uptake is typically understood as the hearer’s recognition of the speaker’s communicative intention. According to one theory of uptake, the hearer’s role is merely as a ratifier. The speaker, by expressing a particular communicative intention, predetermines what kind of illocutionary act she might perform. Her hearer can then render this act a success or a failure. Thus the hearer has no power over which act could be performed, but she does have some power over whether it is performed. Call this (...) the ratification theory of uptake. Several philosophers have recently endorsed an alternative theory of uptake, according to which the hearer can determine the nature of the act the speaker performs. According to this theory, if the hearer regards an utterance as illocutionary act y, then it is act y, even if the speaker intended to perform act x. Call this the constitution theory of uptake. The purported advantage of this theory is that it identifies a common but underanalysed way in which speakers can be silenced. I argue that despite its initial intuitive pull, the constitution theory of uptake should be rejected. It is incompatible with ordinary intuitions about speech, it entails a conceptual impossibility, and it has unsavoury political implications, entailing that marginalised speakers barely qualify as agents. (shrink)

This essay provides an opinionated survey of some recent developments in the literature on ontological dependence. Some of the most popular definitions of ontological dependence are formulated in modal terms; others in non-modal terms (e.g., in terms of the explanatory connective, ‘because’, or in terms of a non-modal conception of essence); some (viz., the existential construals of ontological dependence) emphasise requirements that must be met in order for an entity to exist; others (viz., the essentialist construals) focus on conditions that (...) must be satisfied in order for an entity to be the very entity it is at each time at which it exists; some are rigid, in the sense that they concern a relation between particular entities; others are generic, in the sense that they involve only a relation between an entity and some entities or other, which bear certain characteristics. I identify three potential measures of success with respect to which these different definitions of ontological dependence can be evaluated and consider the question of how well they in fact meet these desiderata. I end by noting that certain challenges face even the most promising essentialist construals of ontological dependence. (shrink)

Many students struggle to enter moral debates in a productive way because they automatically think of moral claims as ‘just opinions’ and not something one could productively argue about. Underlying this response are various versions of a muddled distinction between ‘facts’ and ‘opinions.’ This paper outlines a way to help students overcome their use of this distinction, thereby clearing an obstacle to true moral debate. It explains why the fact-opinion distinction should simply be scrapped, rather than merely sharpened. It (...) then proposes a different distinction well suited to replace it. Finally, it outlines an activity which can be used to teach the new distinction, as well as a number of benefits to attempting the whole replacement process. (shrink)

It is often suggested that when opinions differ among individuals in a group, the opinions should be aggregated to form a compromise. This paper compares two approaches to aggregating opinions, linear pooling and what I call opinion agglomeration. In evaluating both strategies, I propose a pragmatic criterion, No Regrets, entailing that an aggregation strategy should prevent groups from buying and selling bets on events at prices regretted by their members. I show that only opinion agglomeration is able to (...) satisfy the demand. I then proceed to give normative and empirical arguments in support of the pragmatic criterion for opinion aggregation, and that ultimately favor opinion agglomeration. (shrink)

Wikipedia is a goldmine of information; not just for its many readers, but also for the growing community of researchers who recognize it as a resource of exceptional scale and utility. It represents a vast investment of manual effort and judgment: a huge, constantly evolving tapestry of concepts and relations that is being applied to a host of tasks. This article provides a comprehensive description of this work. It focuses on research that extracts and makes use of the concepts, relations, (...) facts and descriptions found in Wikipedia, and organizes the work into four broad categories: applying Wikipedia to natural language processing; using it to facilitate information retrieval and information extraction; and as a resource for ontology building. The article addresses how Wikipedia is being used as is, how it is being improved and adapted, and how it is being combined with other structures to create entirely new resources. We identify the research groups and individuals involved, and how their work has developed in the last few years. We provide a comprehensive list of the open-source software they have produced. (shrink)

Spatially situated opinions that can be held with different degrees of conviction lead to spatiotemporal patterns such as clustering (homophily), polarization, and deadlock. Our goal is to understand how sensitive these patterns are to changes in the local nature of interactions. We introduce two different mixing mechanisms, spatial relocation and nonlocal interaction (“telephoning”), to an earlier fully spatial model (no mixing). Interestingly, the mechanisms that create deadlock in the fully spatial model have the opposite effect when there is a sufficient (...) amount of mixing. With telephoning, not only is polarization and deadlock broken up, but consensus is hastened. The effects of mixing by relocation are even more pronounced. Further insight into these dynamics is obtained for selected parameter regimes via comparison to the mean-field differential equations. (shrink)

Motivation: • Breaking barriers in publishing demands a proactive attitude • Open data, open review and open dialogue in making social sciences plausible .

In this paper, I investigate the role of public opinion and De Staël’s liberal principles in relation to her psychological image of human nature. De Staël regarded the French Revolution as a new stage of human progress, in which the French people, for the first time, gained a political voice. From her position as a liberal republican, De Staël argues for political progress in the form of civil equality and liberty confirmed by law and political representation, for which public (...) opinion serves as a political tool. I aim to demonstrate that De Staël developed a multi-layered analysis of public opinion as both an emancipatory tool for more equality, justice, and liberty, as well as a discriminating and harmful tool. According to De Staël, human passions play a crucial role in determining the employment and the effects of public opinion, as becomes clear in the case of the trial of Marie-Antoinette. (shrink)

Expert testimony figures in recent debates over how best to understand the norm of assertion and the domain-specific epistemic expectations placed on testifiers. Cases of experts asserting with only isolated second-hand knowledge (Lackey 2011, 2013) have been used to shed light on whether knowledge is sufficient for epistemically permissible assertion. I argue that relying on such cases of expert testimony introduces several problems concerning how we understand expert knowledge, and the sharing of such knowledge through testimony. Refinements are needed to (...) clarify exactly what principles are being tested by such cases; but once refined, such cases raise more questions than they answer. (shrink)

The paper addresses an exegetical puzzle that is raised by Kant's distinction between opining (Meinen), believing (Glauben), and knowing (Wissen). In presenting his moral arguments, Kant often points out that belief, as he conceives of it, has a unique feature: it requires non-epistemic justification. Yet Kant's official formulation of the tripartite distinction runs counter to this claim. It describes Belief in terms of a set of two features, each of which also pertains to either opinion or knowledge. My aim (...) in this paper is to propose a novel interpretation of Kant’s distinction which dissolves this exegetical puzzle. (shrink)

In this paper, I will try to answer the question: How are we supposed to assess the expert’s opinion in an argument from the position of an outsider to the specialized field? by placing it in the larger context of the political status of epistemic authority. In order to do this I will first sketch the actual debate around the problem of expertise in a democracy and relate this to the issue of the status of science in society. Secondly, (...) I will review how Douglas Walton’s pragma-dialectical approach offers a practical procedure to assess the expert bias from a nonprofessional’s perspective. Thirdly, I will introduce the problem of group bias using insights from Bohman and Fischer and show how Walton’s solution does not address this specific type of bias. Lastly, I will try proposing a revision of Walton’s solution in order to address this problem. In order to make the explanation more easy to follow I will use a case study concerning the medical expertise in the public debate on second-hand smoke. (shrink)

Abstract: Idea mining is an interesting field in the area of information retrieval and it is increasingly becoming important asset for decision makers. Huge volumes of high quality data from various sources such as scanners, mobile phones, loyalty cards, the web, and social media platforms presents enormous opportunity for organization to achieve success in their businesses. It is possible to achieve this by properly analysing data to reveal feature patterns; hence decision makers can capitalize upon the resulting ideas from (...) wealth of information available. Idea mining helps managers to use their time efficiently by grasping ideas from a huge amount of unstructured data with text mining, instead of reading through page by page, it also helps to avoid the danger of overlooking data with useful ideas. The main objective of this survey article is to provide assessment on a number of successful text mining and text classification tools combined with idea mining measures to extract the idea from texts. (shrink)

This chapter provides a systematic overview of topological explanations in the philosophy of science literature. It does so by presenting an account of topological explanation that I (Kostić and Khalifa 2021; Kostić 2020a; 2020b; 2018) have developed in other publications and then comparing this account to other accounts of topological explanation. Finally, this appraisal is opinionated because it highlights some problems in alternative accounts of topological explanations, and also it outlines responses to some of the main criticisms raised by the (...) so-called new mechanists. (shrink)

There is, in some quarters, concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see these developing. We thus (...) designed a brief questionnaire and distributed it to four groups of experts in 2012/2013. The median estimate of respondents was for a one in two chance that high-level machine intelligence will be developed around 2040-2050, rising to a nine in ten chance by 2075. Experts expect that systems will move on to superintelligence in less than 30 years thereafter. They estimate the chance is about one in three that this development turns out to be ‘bad’ or ‘extremely bad’ for humanity. (shrink)