While the term “reactivity” has come to be associated with specific phenomena in the social sciences, having to do with subjects’ awareness of being studied, this paper takes a broader stance on this concept. I argue that reactivity is a ubiquitous feature of the psychological subject matter and that this fact is a precondition of experimental research, while also posing potential problems for the experimenter. The latter are connected to the worry about distorted data and experimental artifacts. But what (...) are experimental artifacts and what is the most productive way of dealing with them? In this paper, I approach these questions by exploring the ways in which experimenters in psychology simultaneously exploit and suppress the reactivity of their subject matter in order to produce experimental data that speak to the question or subject matter at hand. Highlighting the artificiality of experimental data, I raise the question of what distinguishes a genuine experimental result from an experimental artifact. My analysis construes experimental results as the outcomes of inferences from the data that take material background assumptions as auxiliary premises. Artifacts occur when one or more of these background assumptions are false, such that the data do not reliably serve the purposes they were generated for. I conclude by laying out the ways in which my analysis of data quality is relevant to, and informed by, recent debates about the replicability of experimental results. (shrink)

Data subject rights provide data controllers with obligations that can help with transparency, giving data subjects some control over their personal data. To date, a growing number of researchers have used these data subject rights as a methodology for data collection in research studies. No one, however, has gathered and analysed different academic research studies that use data subject rights as a methodology for data collection. To this end, we conducted a systematic (...) literature review that searched, compiled, and analysed 32 academic studies that use data subject rights as a data collection method. We find that the right of access is the most commonly-used data subject right by researchers, most studies are interested in measuring data subject rights compliance, and that a variety of difficulties exist in conducting research studies with data subject rights. We conclude that researchers should explore other data subject rights for alternative purposes, ease the process of exercising data subject rights, and improve the scalability of these studies. (shrink)

The concept of an individual, liberal data subject, who was traditionally at the centre of data protection efforts has recently come under scrutiny. At the same time, the particularly destructive effect of digital technology on Black people establishes the need for an analysis that not only considers but brings racial dimensions to the forefront. I argue that because Afrofuturism situates the Black struggle in persistent, yet continuously changing structural disparities and power relations, it offers a powerful departure point (...) for re-imagining data protection. Sketching an Afrofuturist data subject then centres on radical subjectivity, collectivity, and contextuality. (shrink)

The typical habitat of overt nominative subjects is in finite clauses. But infinitival complements and infinitival adjuncts are also known to have overt nominative subjects, e.g. in Italian (Rizzi 1982), European Portuguese (Raposo 1987), and Spanish (Torrego 1998, Mensching 2000). The analyses make crucial reference to the movement of Aux or Infl to Comp, and to overt or covert infinitival inflection. This working paper is concerned with a novel set of data that appear to be of a different sort, (...) in that they probably do not depend on either rich infinitival inflection or on movement to C. (shrink)

Modern health data practices come with many practical uncertainties. In this paper, I argue that data subjects’ trust in the institutions and organizations that control their data, and their ability to know their own moral obligations in relation to their data, are undermined by significant uncertainties regarding the what, how, and who of mass data collection and analysis. I conclude by considering how proposals for managing situations of high uncertainty might be applied to this problem. (...) These emphasize increasing organizational flexibility, knowledge, and capacity, and reducing hazard. (shrink)

The first few years of the 21st century were characterised by a progressive loss of privacy. Two phenomena converged to give rise to the data economy: the realisation that data trails from users interacting with technology could be used to develop personalised advertising, and a concern for security that led authorities to use such personal data for the purposes of intelligence and policing. In contrast to the early days of the data economy and internet surveillance, the (...) last few years have witnessed a rising concern for privacy. As bad data practices have come to light, citizens are starting to understand the real cost of using online digital technologies. Two events stamped 2018 as a landmark year for privacy: the Cambridge Analytica scandal, and the implementation of the European Union’s General Data Protection Regulation (GDPR). The former showed the extent to which personal data has been shared without data subjects’ knowledge and consent and many times for unacceptable purposes, such as swaying elections. The latter inaugurated the beginning of robust data protection regulation in the digital age. Getting privacy right is one of the biggest challenges of this new decade of the 21st century. The past year has shown that there is still much work to be done on privacy to tame the darkest aspects of the data economy. As data scandals continue to emerge, questions abound as to how to interpret and enforce regulation, how to design new and better laws, how to complement regulation with better ethics, and how to find technical solutions to data problems. The aim of the research project Data, Privacy, and the Individual is to contribute to a better understanding of the ethics of privacy and of differential privacy. The outcomes of the project are seven research papers on privacy, a survey, and this final report, which summarises each research paper, and goes on to offer a set of reflections and recommendations to implement best practices regarding privacy. (shrink)

“Big Data” and data analytics affect all of us. Data collection, analysis, and use on a large scale is an important and growing part of commerce, governance, communication, law enforcement, security, finance, medicine, and research. And the theme of this symposium, “Individual and Informational Privacy in the Age of Big Data,” is expansive; we could have long and fruitful discussions about practices, laws, and concerns in any of these domains. But a big part of the audience (...) for this symposium is students and faculty in higher education institutions (HEIs), and the subject of this paper is data analytics in our own backyards. Higher education learning analytics (LA) is something that most of us involved in this symposium are familiar with. Students have encountered LA in their courses, in their interactions with their law school or with their undergraduate institutions, instructors use systems that collect information about their students, and administrators use information to help understand and steer their institutions. More importantly, though, data analytics in higher education is something that those of us participating in the symposium can actually control. Students can put pressure on administrators, and faculty often participate in university governance. Moreover, the systems in place in HEIs are more easily comprehensible to many of us because we work with them on a day-to-day basis. Students use systems as part of their course work, in their residences, in their libraries, and elsewhere. Faculty deploy course management systems (CMS) such as Desire2Learn, Moodle, Blackboard, and Canvas to structure their courses, and administrators use information gleaned from analytics systems to make operational decisions. If we (the participants in the symposium) indeed care about Individual and Informational Privacy in the Age of Big Data, the topic of this paper is a pretty good place to hone our thinking and put into practice our ideas. (shrink)

Jason Stanley has argued recently that Epistemic Contextualism (EC) and Subject‐Sensitive Invariantism (SSI) are explanatorily on a par with regard to certain data arising from modal and temporal embeddings of ‘knowledge’‐ascriptions. This paper argues against Stanley that EC has a clear advantage over SSI in the discussed field and introduces a new type of linguistic datum strongly suggesting the falsity of SSI.

It has been argued that ethical frameworks for data science often fail to foster ethical behavior, and they can be difficult to implement due to their vague and ambiguous nature. In order to overcome these limitations of current ethical frameworks, we propose to integrate the analysis of the connections between technical choices and sociocultural factors into the data science process, and show how these connections have consequences for what data subjects can do, accomplish, and be. Using healthcare (...) as an example, attention to sociocultural conversion factors relevant to health can help in navigating technical choices that require broader considerations of the sociotechnical system, such as metric tradeoffs in model validation, resulting in better ethical and technical choices. This approach promotes awareness of the ethical dimension of technical choices by data scientists and others, and that can foster the cultivation of 'ethical skills' as integral to data science. (shrink)

Access to data in crime and place research has traditionally been reserved for those who have the means to collect fresh data themselves, pay for access, or obtain data through formal data sharing agreements. Even when access is granted, the usage of these data often comes with conditions that circumscribe how the data can be used through licensing or policy (Kitchin, 2014). Even the public dissemination of findings which emerge from analysis might be subject (...) to restrictions. This can lead to unequal access, controlled usage and curb the diffusion of findings, severely limiting the insight that can be obtained from data. (shrink)

There are long-standing doubts about whether data from subjective scales—for instance, self-reports of happiness—are cardinally comparable. It is unclear how to assess whether these doubts are justified without first addressing two unresolved theoretical questions: how do people interpret subjective scales? Which assumptions are required for cardinal comparability? This paper offers answers to both. It proposes an explanation for scale interpretation derived from philosophy of language and game theory. In short: conversation is a cooperative endeavour governed by various (...) maxims (Grice 1989); because subjective scales are vague and individuals want to make themselves understood, scale interpretation is a search for a focal point (Schelling 1960). A specific focal point it hypothesised; if this hypothesis is correct, subjective data will be cardinally comparable. Four individually necessary and jointly sufficient conditions for cardinal comparability are specified. The paper then argues this hypothesis can be empirically be tested, makes an initial attempt to do so using subjective well-being data, and concludes it is supported. Numerous areas for further research are identified including, at the end of the paper, how certain tests could be used to ‘correct’ subjective data if they are not cardinal. (shrink)

What is data? That question is the fundamental investigation of this dissertation. I have developed a methodology from social-scientific processes to explore how different people understand the concept of data, rather than to rely on my own philosophical intuitions or thought experiments about the “nature” of data. The evidence I have gathered as to different individuals' constructions of data can be used to inform further inquiry of data and the design of information systems. My research (...) demonstrates that people have different constructions of data. The methodology of the SDFN, created for this dissertation, has proven able to probe those understandings. The SDFN, loosely based on a DFD and combined with ideas from SNA, provides a way of discovering practical definitions of hard-to-operationalize terms like data. The process of repeatedly categorizing various items as data allows the methodology to explore how participants actually use the term, rather than relying on theoretical dictionary-based definitions. Analysis of the interviews found three different constructions of data: data as communications, a container for meaning; data as subjective observations, sense-impressions filtered by knowledge; and data as objective facts, measurements revealing the relationships of reality. (shrink)

The public constitutes a major stakeholder in the debate about, and resolution of privacy and ethical The public constitutes a major stakeholder in the debate about, and resolution of privacy and ethical about Big Data research seriously and how to communicate messages designed to build trust in specific big data projects and the institution of science in general. This chapter explores the implications of various examples of engaging the public in online activities such as Wikipedia that contrast with (...) “Notice and Consent” forms and offers models for scientists to consider when approaching their potential subjects in research. Drawing from Lessig, Code and Other Laws of Cyberspace, the chapter suggests that four main regulators drive the shape of online activity: Code (or Architecture), Laws, Markets, and Norms. Specifically, scientists should adopt best practices in protecting computerized Big Data (Code), remain completely transparent about their data management practices (Law), make smart choices when deploying digital solutions that place a premium on information protection (Market), and, critically, portray themselves to the public as seriously concerned with protecting the privacy of persons and security of data (Norms). The community of Big Data users and collectors should remember that such data are not just “out there” somewhere but are the intimate details of the lives of real persons who have just as deep an interest in protecting their privacy as they do in the good work that is conducted with such data. (shrink)

Despite widespread recognition of an emergent politics of data in our midst, we strikingly lack a political theory of data. We readily acknowledge the presence of data across our political lives, but we often do not know how to conceptualize the politics of all those data points—the forms of power they constitute and the kinds of political subjects they implicate. Recent work in numerous academic disciplines is evidence of the first steps toward a political theory of (...) data. This article maps some limits of this emergent literature with an eye to enriching its theoretical range. The literature on data politics, both within political theory and elsewhere, has thus far focused almost exclusively on the algorithm. This article locates a further dimension of data politics in the work of formatting technology or, more simply, formats. Formats are simultaneously conceptual and technical in the ways they define what can even count as data, and by extension who can count as data and how they can count. A focus on formats is of theoretical value because it provides a bridge between work on the conceptual contours of categories and the technology-centric literature on algorithms that tends to ignore the more conceptual dimensions of data technology. The political insight enabled by format theory is shown in the context of an extended interrogation of the politics of racialized redlining. (shrink)

According to contextualism, vast majority of natural-language expressions are context-sensitive. When testing whether this claim is reflected in Folk intuitions, some interesting methodological questions were raised such as: which experimental design is more appropriate for testing contextualism – the within- or the between-subject design? The main thesis of this paper is that the between-subject design should be preferred. The first experiment aims at assessing the difference between the results obtained for within-subjects measurements (where all participants assess all contexts) and between-subject (...) measurements (where respondents evaluating different contexts are distinct groups). It is shown that the within-subject design provides data that seems to support contextualism. However, I present an alternative, invariantist interpretation of these results, therefore showing that the within-subject design does not allow to empirically distinguish between contextualism and invariantism. The second experiment further elaborates the issue of how perceiving the contrast between contexts can affect subjects’ judgments – I show that certain kinds of contexts may elicit opposite intuitions when contrasted with different contexts. (shrink)

Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that the GDPR will legally mandate a ‘right to explanation’ of all decisions made by automated or artificially intelligent algorithmic systems. This right to explanation is viewed as an ideal mechanism to enhance the accountability and transparency of automated decision-making. However, there are several reasons to doubt both the legal existence and the feasibility of such a right. In contrast to (...) the right to explanation of specific automated decisions claimed elsewhere, the GDPR only mandates that data subjects receive meaningful, but properly limited, information (Articles 13-15) about the logic involved, as well as the significance and the envisaged consequences of automated decision-making systems, what we term a ‘right to be informed’. Further, the ambiguity and limited scope of the ‘right not to be subject to automated decision-making’ contained in Article 22 (from which the alleged ‘right to explanation’ stems) raises questions over the protection actually afforded to data subjects. These problems show that the GDPR lacks precise language as well as explicit and well-defined rights and safeguards against automated decision-making, and therefore runs the risk of being toothless. We propose a number of legislative and policy steps that, if taken, may improve the transparency and accountability of automated decision-making when the GDPR comes into force in 2018. (shrink)

The predominant view is that a study using health data is observational research and should require individual consent unless it can be shown that gaining consent is impractical. But recent arguments have been made that citizens have an ethical obligation to share their health information for research purposes. In our view, this obligation is sufficient ground to expand the circumstances where secondary use research with identifiable health information is permitted without explicit subject consent. As such, for some studies the (...) Institutional Review Board/Research Ethics Committee review process should not assess the practicality of gaining consent for data use. Instead the review process should focus on assessing the public good of the research, public engagement and transparency. (shrink)

The inherently subjective nature of consciousness severely limits our ability to make progress on the problem of consciousness. The inability to acquire objective, publicly available data on the phenomenal aspect of consciousness makes evaluating alternative theories very difficult, if not impossible. However, the anomalous nature of subjective states with respect to our conventional theories of the physical world suggests the possibility of considering other anomalous data around consciousness that happen to be objective. For such purposes, I (...) propose that we examine the psi data gathered under laboratory conditions, which generally receive little attention. I wish to consider whether we have theories or frameworks of consciousness that attempt to account for subjective qualia but also fit the psi data. I argue that Russellian monism can be combined with an argument regarding quantum holism to arrive at a version of cosmopsychism that fits very well with the psi data. While I do not argue that such a framework exhausts the theoretical possibilities, I do suggest we can move forward with a framework that has attractive theoretical features and is also consistent with objective data currently on the table. (shrink)

The traditional approach in cognitive sciences holds that cognition is a matter of manipulating abstract symbols followingcertain rules. According to this view, the body is merely an input/output device, which allows the computationalsystem—the brain—to acquire new input data by means of the senses and to act in the environment following its com-mands. In opposition to this classical view, defenders of embodied cognition (EC) stress the relevance of the body inwhich the cognitive agent is embedded in their explanation of cognitive (...) processes. From a representationalist frameworkregarding our conscious experience, in this article, I will offer a novel argument in favor of EC and show that cognitionconstitutively—and no merely causally—depends upon body activity beyond that in the brain. In particular, I will arguethat in order to solve the problem derived from the empirical evidence in favor of the possibility of shifted spectrum,representationalist should endorse the view that experiences concern its subject: the content of experience isde se.Ishow that this claim perfectly matches the phenomenological observation and helps explaining the subjective characterof the experience. Furthermore, I argue that entertaining this kind of representation constitutively depends on bodilyactivity. Consequently, insofar as cognition depends on consciousness, it is embodied. (shrink)

Improvements of the happiness of the rural population are an essential sign of the effectiveness of relative poverty governance. In the context of today’s digital economy, assessing the relationship between digital literacy and the subjective happiness of rural low-income groups is of great practicality. Based on data from China Family Panel Studies, the effect of digital literacy on the subjective well-being of rural low-income groups was empirically tested. A significant happiness effect of digital literacy on rural low-income (...) groups was found. Digital literacy promotes the subjective happiness of rural low-income groups through income increase and consumption growth effects. The observed happiness effect is heterogeneous among different characteristic groups, and digital literacy significantly positively impacts the subjective happiness of rural low-income groups. Decomposition of subjective happiness into life satisfaction and job satisfaction shows that digital literacy significantly positively affects the job and life satisfaction of rural low-income groups. This paper demonstrates that digital literacy induces a practical happiness effect. To further strengthen the subjective welfare effect of digital literacy in the construction of digital villages, the government should focus on cultivating digital literacy among low-income groups from the demand side. The construction of digital infrastructure should be actively promoted from the supply side. (shrink)

Philosophers have justified extant theories of singular thought in at least three ways: they have invoked wide-ranging theories motivated by data from other philosophical areas, they have elicited direct intuitions about which thoughts are singular, and they have subjected propositional attitude reports to tests such as Russellian substitution and Quinean exportation. In these ways, however, we haven’t yet been able to tell what it takes to have singular thoughts, nor have we been able to tell which of our thoughts (...) they are. I propose, therefore, a methodological contribution, a new source of data about singular thought. We can tell whether a thought is singular if we ask what we can coherently deny at the same time at which we agree with the thought. When we agree with a thought that is general, we cannot coherently deny about the thought’s subject a certain description, the one that occurs in the thought’s subject position. To show how to use this new data source, I develop a linguistic method for testing whether a speaker expresses a singular or a general thought. (shrink)

News about personal data breaches or data abusive practices, such as Cambridge Analytica, has questioned the trustworthiness of certain actors in the control of personal data. Innovations in the field of personal information management systems to address this issue have regained traction in recent years, also coinciding with the emergence of new decentralized technologies. However, only with ethically and legally responsible developments will the mistakes of the past be avoided. This contribution explores how current data management (...) schemes are insufficient to adequately safeguard data subjects, and in particular, it focuses on making these data flows transparent to provide an adequate level of accountability. To showcase this, and with the goal of enhancing transparency to foster trust, this paper investigates solutions for standardizing machine-readable policies to express personal data processing activities and their application to decentralized personal data stores as an example of ethical, legal, and technical responsible innovation in this field. (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)

Scholarship on the politics of new media widely assumes that communication functions as a sufficient conceptual paradigm for critically assessing new media politics. This article argues that communication-centric analyses fail to engage the politics of information itself, limiting information only to its consequences for communication, and neglecting information as it reaches into our selves, lives, and actions beyond the confines of communication. Furthering recent new media historiography on the “information theory” of Shannon and Wiener, the article reveals both the primacy (...) of communication in midcentury information theory, and also a striking resonance between these postwar communication theories and Habermas’s more recent communicative theory of democracy. To achieve a critical perspective beyond communication, the article proposes a media genealogy of the politics of subjects as a methodology for developing an analysis of how information formats us as subjects of data. (shrink)

With the growth of data, data-intensive approaches for sustainability are becoming widespread and have been endorsed by various stakeholders. To understand their implications, in this paper data-intensive approaches for sustainability will be explored by conducting an extensive review. The current data-intensive approaches are defined as an amalgamation of traditional data-collection methods, like surveys and data from monitoring networks, with new data-collection methods that involve new information communication technology. Based on a comprehensive review of (...) the current dataintensive approaches for sustainability, key challenges are identified: the lack of data availability, diverse indicators developed from a narrowly viewed base, diverse definitions and values, skewed global representation, and the lack of social and economic information collected, especially among the business indicators. To clarify the implications of these trends, four major research assumptions regarding dataintensive approaches are elaborated: the methodology, epistemology, normativity, and ontology. Caution is required when data-intensive approaches are masked as “objective”. Overcoming this issue requires interdisciplinary and community-based approaches that can offer ways to address the subjectivities of data-intensive approaches. The current challenges to interdisciplinarity and community-based approaches are also identified, and possible solutions are explored, so that researchers can employ them to make the best use of data-intensive approaches. (shrink)

This paper argues that assessing personal responsibility in healthcare settings for the allocation of medical resources would be too privacy-invasive to be morally justifiable. In addition to being an inappropriate and moralizing intrusion into the private lives of patients, it would put patients’ sensitive data at risk, making data subjects vulnerable to a variety of privacy-related harms. Even though we allow privacy-invasive investigations to take place in legal trials, the justice and healthcare systems are not analogous. The duty (...) of doctors and healthcare professionals is to help patients as best they can—not to judge them. Patients should not be forced into giving up any more personal information than what is strictly necessary to receive an adequate treatment, and their medical data should only be used for appropriate purposes. Medical ethics codes should reflect these data rights. When a doctor asks personal questions that are irrelevant to diagnose or treat a patient, the appropriate response from the patient is: ‘none of your business’. (shrink)

Detecting quality in large unstructured datasets requires capacities far beyond the limits of human perception and communicability and, as a result, there is an emerging trend towards increasingly complex analytic solutions in data science to cope with this problem. This new trend towards analytic complexity represents a severe challenge for the principle of parsimony (Occam’s razor) in science. This review article combines insight from various domains such as physics, computational science, data engineering, and cognitive science to review the (...) specific properties of big data. Problems for detecting data quality without losing the principle of parsimony are then highlighted on the basis of specific examples. Computational building block approaches for data clustering can help to deal with large unstructured datasets in minimized computation time, and meaning can be extracted rapidly from large sets of unstructured image or video data parsimoniously through relatively simple unsupervised machine learning algorithms. Why we still massively lack in expertise for exploiting big data wisely to extract relevant information for specific tasks, recognize patterns and generate new information, or simply store and further process large amounts of sensor data is then reviewed, and examples illustrating why we need subjective views and pragmatic methods to analyze big data contents are brought forward. The review concludes on how cultural differences between East and West are likely to affect the course of big data analytics, and the development of increasingly autonomous artificial intelligence (AI) aimed at coping with the big data deluge in the near future. Keywords: big data; non-dimensionality; applied data science; paradigm shift; artificial intelligence; principle of parsimony (Occam’s razor) . (shrink)

Children continue to be overlooked as a topic of concern in discussions around the ethical use of people’s data and information. Where children are the subject of such discussions, the focus is often primarily on privacy concerns and consent relating to the use of their data. This paper highlights the unique challenges children face when it comes to online interferences with their decision-making, primarily due to their vulnerability, impressionability, the increased likelihood of disclosing personal information online, and their (...) developmental capacities. These traits allow for practices such as hypernudging to be executed on them more accurately and with more serious consequences, specifically by potentially undermining their autonomy. We argue that children are autonomous agents in the making and thus require additional special protections to ensure that the development of their autonomy is safeguarded. This means that measures should be taken to prohibit most forms of hypernudging children and thus ensure that they are protected from this powerful technique of digital manipulation. (shrink)

Elementary preservice teachers (EPTs) substantially impact the quality of mathematics education, and their subject preference and problem-solving performance are essential indicators of their readiness to teach. The study described EPTs’ subject preference and problem-solving performance. Through a sequential explanatory research design, the quantitative inquiry involved 125 random samples, while the qualitative inquiry was participated by 30 non-random samples. Data were obtained by using an online survey and conferencing. Quantitative data were analyzed through descriptive statistics and analysis of variance, (...) whereas qualitative data were themed accordingly. The EPTs displayed unsatisfactory problem-solving performance and preferred to handle subjects other than math. Besides, the analysis found no significant performance differences with the EPTs’ subject preferences. Further, the EPTs who preferred to teach mathematics expressed their confidence in mathematics. Meanwhile, the EPTs who preferred other subjects displayed math avoidance. The study revealed an alarming result indicating that the EPTs are unprepared for teaching. As agents in cultivating the nation’s mathematics education status, these EPTs must be equipped with fundamental content knowledge. It is suggested that educational decision-makers take measures to address the issues identified concerning EPTs’ readiness to teach mathematics successfully. (shrink)

The last two decades have seen the proliferation of the empirical study of philosophy. This dissertation defends the practice and argues that to understand the way contingent features of the practice of philosophy affect the epistemic standing of philosophers, we need to draw upon a wider and more varied set of empirical data than is sometimes supposed. To explore this, the dissertation focuses on two places where the practices of the discipline of philosophy have an effect on the epistemology (...) of philosophy. -/- First, the dissertation discusses the interaction between notable works of philosophy and their readers. In particular, it critiques the method of defending the epistemic standing of philosophers through careful examination of notable works of philosophy to discern the methods in the text. Ultimately this method is epistemically unmotivated. It is instead far more important to study how people have interacted and reacted to works of philosophy. -/- Second, the dissertation defends the use of lexicography in philosophy. Using "intuition" as a case study, the dissertation argues metasemantically and lexicographically that philosophers often use common words with meanings unique to philosophy. -/- Through both discussions it is argued that experimental philosophers and epistemologists of philosophy need to drastically expand the sorts of data they collect and consider in their theorizing. -/- ​. (shrink)

: One of the most active study fields in natural language processing, web mining, and text mining is sentiment analysis. Big data is an important research component in education that is used to advance the value of education by watching students' performance and understanding their learning habits. Real-time student feedback will enable teachers and students to understand teaching and learning challenges in the most user-friendly manner for students. By linking learning analytics to grounded theory, the proposed Deep Convolutional Neural (...) Network (DCNN) analyses students' sentiments and emotions through feedback using a Lexicon-based emotional analysis approach. The sentiment analysis approach is a computer procedure that identifies and classifies subjective information from the source material as good, negative, or neutral. (shrink)

Background Several jurisdictions, including Singapore, Australia, New Zealand and most recently Ireland, have a public interest or public good criterion for granting waivers of consent in biomedical research using secondary health data or tissue. However, the concept of the public interest is not well defined in this context, which creates difficulties for institutions, institutional review boards and regulators trying to implement the criterion. Main text This paper clarifies how the public interest criterion can be defensibly deployed. We first explain (...) the ethical basis for requiring waivers to only be granted to studies meeting the public interest criterion, then explore how further criteria may be set to determine the extent to which a given study can legitimately claim to be in the public interest. We propose an approach that does not attempt to measure magnitude of benefit directly, but rather takes into account metrics that are more straightforward to apply. To ensure consistent and justifiable interpretation, research institutions and IRBs should also incorporate procedural features such as transparency and public engagement in determining which studies satisfy the public interest requirement. Conclusion The requirement of public interest for consent waivers in secondary biomedical research should be guided by well-defined criteria for systematic evaluation. Such a criteria and its application need to be periodically subject to intra-committee and intra-institution review, reflection, deliberation and amendment. (shrink)

Biological ontologies are used to organize, curate, and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple ontologies can be problematic, as they are developed independently, which can lead to incompatibilities. The Open Biological and Biomedical Ontologies Foundry was created to address this by facilitating the development, harmonization, application, and sharing of ontologies, guided by a set of overarching principles. One challenge in reaching these goals was that (...) the OBO principles were not originally encoded in a precise fashion, and interpretation was subjective. Here we show how we have addressed this by formally encoding the OBO principles as operational rules and implementing a suite of automated validation checks and a dashboard for objectively evaluating each ontology’s compliance with each principle. This entailed a substantial effort to curate metadata across all ontologies and to coordinate with individual stakeholders. We have applied these checks across the full OBO suite of ontologies, revealing areas where individual ontologies require changes to conform to our principles. Our work demonstrates how a sizable federated community can be organized and evaluated on objective criteria that help improve overall quality and interoperability, which is vital for the sustenance of the OBO project and towards the overall goals of making data FAIR. Competing Interest StatementThe authors have declared no competing interest. (shrink)

Because obituaries are succinct and explicitly intended to summarize their subjects’ lives, they may be expected to include only the features that the author finds most salient but also to signal to others in the community the socially-recognized aspects of the deceased’s character. We begin by reviewing studies 1 and 2, in which obituaries were carefully read and labeled. We then report study 3, which further develops these results with a semi-automated, large-scale semantic analysis of several thousand obituaries. Geography, gender, (...) and elite status all turn out to be associated with the virtues and values associated with the deceased. (shrink)

This article is a preliminary draft for initiating and commencing a new pioneer dimension of expression. To deal with higher-dimensional data or information flowing in this modern era of information technology and artificial intelligence, some innovative super algebraic structures are essential to be formulated. In this paper, we have introduced such matrices that have multiple layers and clusters of layers to portray multi-dimensional data or massively dispersed information of the plithogenic universe made up of numerous subjects their attributes, (...) and sub-attributes. For grasping that field of parallel information, events, and realities flowing from the micro to the macro level of universes, we have constructed hypersoft and hyper-super-soft matrices in a Plithogenic Fuzzy environment. These Matrices classify the non-physical attributes by accumulating the physical subjects and further sort the physical subjects by accumulating their non-physical attributes. We presented themasPlithogenicAttributiveSubjectivelyWholeHyper-Super-Soft-Matrix(PASWHSS-Matrix)andPlithogenic Subjective Attributively Whole-Hyper-Super-Soft-Matrix (PSAWHSS-Matrix). Several types of views and level-layers of these matrices are described. In addition, some local aggregation operators for Plithogenic Fuzzy Hypersoft Set (PPFHS-Set) are developed. Finally, few applications of these matrices and operators are used as numerical examples of COVID-19 data structures. (shrink)

In the United States, the Presidential Commission for the Study of Bioethical Issues has proposed deliberative democracy as an approach for dealing with ethical issues surrounding synthetic biology. Deliberative democracy might similarly help us as we update the regulation of human subjects research. This paper considers how the values that deliberative democratic engagement aims to realize can be realized in a human subjects research context. Deliberative democracy is characterized by an ongoing exchange of ideas between participants, and an effort to (...) justify decisions that bind participants by appeal to reasons that the participants can understand and share. Even when unanimous agreement is not reached, the active participation of everyone along with the requirement that reasons be made accessible enhances the legitimacy of the ultimate outcome. Importantly, deliberative democratic structures avoid strict hierarchies and place participants, as much as possible, in the position of equals. Human subjects research has some features that may make deliberative democratic principles seem initially unappealing. For one, there are asymmetries in knowledge between expert researchers conducting the research and participants in the research process. For another, statistical validity is made easiest by research paradigms that produce standardized, quantitative data, which can be difficult to achieve if research participants are given the power to deliberatively reshape the research design as it progresses. These and other problems have tended to produce a human subjects research process where subjects do not actively participate in shaping research, but rather consent to a predefined set of interventions designed by expert researchers and vetted by Institutional Review Boards (IRBs). In this paper, I suggest some ways in which human subjects research could do more to realize deliberative democratic values, and, in particular, how a revised Common Rule might help to realize these values. First, research participants could be treated not as passive subjects but instead involved in research design, ethical review, and the ongoing conduct and dissemination of research. Such participation might involve, for instance, including people who have served as research subjects on IRBs, or replacing IRB oversight for certain forms of research exempted from IRB oversight under a revised Common Rule with oversight by a body of community members or research subjects. It might also involve having the oversight of research that uses more participatory models be more participatory and less hierarchical in nature. I also raise questions about the exemption of research on public benefit programs from any research-level oversight and from consent requirements. While IRBs are likely not the correct overseers, there may be good reason to view such research with a critical eye, because of its potential for long-range impacts on the lives of participants. By giving research subjects a greater voice in research that aims at fine-tuning public benefit programs on which subjects rely, a deliberative oversight process has the potential to recast research participation as a form of active democratic participation and to address a “democratic deficit” in public health. Numerous proposals regarding health care have called for greater participation by laypeople and a more nonhierarchical approach to setting health priorities. Involving lay research subjects in the conduct of public benefits research and other forms of public health research may help to further these goals. (shrink)

Increasingly, empirically minded moral philosophers are using data from cognitive science and neuroscience to resolve some longstanding philosophical questions about moral motivation, such as whether moral beliefs require the presence of a desire to motivate. These empirical approaches are implicitly committed to the existence of folk psychological mental states like beliefs and desires. However, data from the neuroscience of decision-making, particularly cellular-level work in neuroeconomics, is now converging with data from cognitive and social neuroscience to explain the (...) processes through which agents are moved to act on the basis of decisions, including decisions about social and moral norms. I argue that these developments are beginning to cast doubt on the prospect of finding nontrivial physical 'realizers' for the FP states invoked in the Humeanism dispute by posing two distinctive challenges that tend to work against each other: belief-desire directionality and causal relevance. (shrink)

Referent Tracking (RT) advocates the use of instance unique identifiers to refer to the entities comprising the subject matter of patient health records. RT promises many benefits to those who use health record data to improve patient care. To further the adoption of the paradigm we provide an illustration of how data from an EHR application needs to be decomposed in order to make it accord with the tenets of RT. We describe the ontological principles on which this (...) decomposition is based in order to allow integration efforts to be applied in similar ways to other EHR applications. We find that an ordinary statement from an EHR contains a surprising amount of “hidden” data that are only revealed by its decomposition according to these principles. (shrink)

The ongoing explosion of interest in artificial intelligence is fueled in part by recently developed techniques in machine learning. Those techniques allow automated systems to process huge amounts of data, utilizing mathematical methods that depart from traditional statistical approaches, and resulting in impressive advancements in our ability to make predictions and uncover correlations across a host of interesting domains. But as is now widely discussed, the way that those systems arrive at their outputs is often opaque, even to the (...) experts who design and deploy them. Is it morally problematic to make use of opaque automated methods when making high-stakes decisions, like whether to issue a loan to an applicant, or whether to approve a parole request? Many scholars answer in the affirmative. However, there is no widely accepted explanation for why transparent systems are morally preferable to opaque systems. We argue that the use of automated decision-making systems sometimes violates duties of consideration that are owed by decision-makers to decision-subjects, duties that are both epistemic and practical in character. Violations of that kind generate a weighty consideration against the use of opaque decision systems. In the course of defending our approach, we show that it is able to address three major challenges sometimes leveled against attempts to defend the moral import of transparency in automated decision-making. (shrink)

In August 2021, Froese et al. published survey data collected from 2,543 respondents on their subjective experiences living under imposed social distancing measures during COVID-19 (1). The questionnaire was issued to respondents in the UK, Japan, and Mexico. By combining the authors’ expertise in phenomenological philosophy, phenomenological psychopathology, and enactive cognitive science, the questions were carefully phrased to prompt reports that would be useful to phenomenological investigation and theorizing (2–4). These questions reflected the various author’s research interests (e.g., (...) technology, grief, time). Between April 7th and July 31st, 2021, a second questionnaire with the same question set was issued to respondents of the original who had agreed to do a follow-up. This was intended to capture subjective reports of life under social distancing measures a year after the initial survey. By this time–depending on their country of residence and health status–respondents had potentially lived with repeated and prolonged lockdowns and a variety of other restrictions on their social lives. When taken together, Survey I and Survey II provide a cross-cultural and longitudinal dataset that allows for analysis of longer-term impacts of imposed social distancing measures on people’s experiences. For researchers working in diverse disciplines, this dataset offers a rich resource that reflects people’s reactions to the imposition of different social restrictions in different countries and over different time periods. (shrink)

The COVID-19 pandemic demonstrated the benefits of international data sharing. Data sharing enabled the health care policy makers to make decisions based on real-time data, it enabled the tracking of the virus, and importantly it enabled the development of vaccines that were crucial to mitigating the impact of the virus. This data sharing is not the norm as data sharing needs to navigate complex ethical and legal rules, and in particular, the fragmented application of the (...) General Data Protection Regulation (GDPR). The introduction of the draft regulation for a European Health Data Space (EHDS) in May 2022 seeks to address some of these legal issues. If passed, it will create an obligation to share electronic health data for certain secondary purposes. While there is a clear need to address the legal complexities involved with data sharing, it is critical that any proposed reforms are in line with ethical principles and the expectations of the data subjects. In this paper we offer a critique of the EHDS and offer some recommendations for this evolving regulatory space. (shrink)

The study was conducted to explore teachers’ experiences in the delivery of science subjects during the first school year of implementation of distance learning. The teachers’ experiences in the delivery of science subjects served as a reference for formulating innovation to make learning effective in distance learning modality. The data for this study were collected through an interview schedule. It was done through one-on-one in-depth interviews with each participant with the observance of COVID-19 safety protocols. The interviews with all (...) participants were audio-recorded. The data were transcribed verbatim by repeatedly listening to the recorded audio recording. Transcribed verbatim responses were then translated into English. After that, significant statements were determined from all participants’ responses. Lastly, themes and sub-themes were generated from the participants’ significant statements. Based on the result of this study, the following themes have been generated: preparation experiences, adjustment experiences, and unpleasant experiences. Preparations experienced by the participants were professional development, learning resource preparations, and aligning lessons to MELCs. The participants also had adjustment experiences, including content modification and ICT utilization. Also, unpleasant experiences by the participants were an overwhelming workload, complex communication, problems with assessment, and poor student learning. All the teachers’ experiences identified by the Hilongos National Vocational School junior high school teachers serve as the basis for formulating an innovation project. An innovation project for the new normal will address the unpleasant experiences of the teachers. Hence, the innovation project on improving students’ learning for science subjects in a distance learning modality must be utilized to cater to the needs of the school’s clients, the learners. The study concluded that an innovation project on improving students’ learning of science subjects is necessary to equip the Science Teachers of Hilongos National Vocational School with skills to improve the delivery of science subjects in the new normal. It is also recommended to alleviate teachers’ workload, strengthen communications, address problems in assessment, and improve students’ learning. (shrink)

Obituaries are an especially rich resource for identifying people’s values. Because obituaries are succinct and explicitly intended to summarize their subjects’ lives, they may be expected to include only the features that the author(s) find most salient, not only for themselves as relatives or friends of the deceased, but also to signal to others in the community the socially-recognized aspects of the deceased’s character. We report three approaches to the scientific study of virtue and value through obituaries. We begin by (...) reviewing studies 1 and 2, in which obituaries were carefully read and labeled. We then report study 3, which further develops these results with a semi-automated, large-scale semantic analysis of several thousand obituaries. Finally, we present the results of study 4 in which individuals were asked to write prospective obituaries. Geography, gender, and elite status all turn out to influence the virtues and values associated with the deceased. (shrink)

Previous research has extensively analysed teachers' and students' Facebook use for instructional engagement, writing, research dissemination and e-learning. However, Facebook as a data collection mechanism for research has scarcely been the subject of previous studies. The current study addressed these gaps by analysing students' awareness, willingness, and utilisation of Facebook for research data collection [RDC]. This study aimed to predict students’ Facebook use for research data collection based on their awareness and willingness and to determine age and (...) gender differences in such predictions. A sample of 11,562 students of tertiary institutions participated in an online survey. The researchers designed and validated the online survey. Exploratory Factor Analysis was used for dimensionality. Average Variance Extracted [AVE] was used for convergent validity, whilst the Fornel-Larcker criterion and Heterotrait-Monotrait ratio were used for discriminant validity. Composite reliability indices of .97, .94 and .90 proved the instrument’s three sub-scales usable. One sample t-test and multigroup analysis were conducted using SPSS 27 and Smart PLS 3. The study found high awareness but low usage of Facebook for RDC among Nigerian university students. Younger and male students showed higher willingness and actual use of Facebook for RDC. Awareness directly impacted by awareness, and acted as Facebook usage for RDC, with stronger impacts for males and students aged 19 to 28. Willingness was positively impacted and acted as a negative mediator between awareness and usage for some age groups and genders. These findings provide important insights into using Facebook for RDC among students in Nigerian universities and highlight the need to consider the impact of demographic factors such as age and. (shrink)

The purpose of college and university ranking mainly resides to assist with the students in choosing their schools and programs at the level they wish to study. The US News and World Report (USNWR) graduate programs ranking is notable that evaluates the graduate level programs uniquely and in contrast with other general subject rankings. Along with the reputation of source, this specificity enables to enjoy a number of subscribers in making an application decision about which school or program is competitive (...) and personally fits. Given the study of national research council is most exhaustive and authoritative ranking source on research doctorates, called Ph.Ds, the ranking of professional schools, for instance, law schools, medical schools, nursing schools and on, as presented to the students in USNWR is very determinative in deciding which school I choose. In this light, the following tables show a ranking that has been yielded on the diversity and quality of graduate and research doctorate programs as well as law studies specifically. Therefore, the tables can be referred to a vast of interested people on the graduate studies in the United States. The last part of reference can be referred not only by JD students, but also by researchers in the graduate law programs. Since some small or exclusively JD-oriented law schools are not available of LL.M or graduate study, the users of table are expected to read consciously. The ranking table has a threshold to qualify so as to be enlisted that the top 44 law schools in all specialties exclusively had been selected and ranked according to the average of two subjects. As said, it could be used secondarily to refer in deciding the schools on the application of general LL.M program. Given the junior scholarly nature of LL.M. or graduate law programs, it is considered that the legal writing program is half factored to select the schools. The column 1 and 2 transcribes the US ranking, which are added for a sum in column 3. Least number is placed at top and less number attains a high ranking correspondingly thorough the end of institution. The first and second parts of this work show the top universities according to the number of programs, whose possible highest rating is placed within the range 1st -17th in either R or S rank of most recent 2010 NRC assessment and roughly same range in the USNWR graduate programs ranking. They are prepared from the revised NRC report published in 2011, which is most recent as well as based on the 2021 version of USNWR. Both data will be incorporated into my current project concerning the American higher education and graduate studies. (shrink)

Gignac and Zajenkowski (2020) find that “the degree to which people mispredicted their objectively measured intelligence was equal across the whole spectrum of objectively measured intelligence”. This Comment shows that Gignac and Zajenkowski’s (2020) finding of homoscedasticity is likely the result of a recoding choice by the experimenters and does not in fact indicate that the Dunning-Kruger Effect is a mere statistical artifact. Specifically, Gignac and Zajenkowski (2020) recoded test subjects’ responses to a question regarding self-assessed comparative IQ onto a (...) linear IQ scale when a normal IQ scale would likely have been more appropriate. More generally, researchers studying self-assessed intelligence should be aware of potential measurement problems that may arise when transforming an ordinal scale onto an interval scale. (shrink)

The purpose of this study was to evaluate the differentiated learning training program at the mathematics subject teachers' meeting (MGMP). A descriptive quantitative approach was used to identify the successes of the program and areas that require improvement. The sample included 21 mathematics teachers in Sub Rayon 2 of Lebak District. The instruments used were questionnaires in which data on participants' responses to resource persons, materials, and suggestions for future activities were collected, and the results of direct observations. (...) class='Hi'>Data analysis was carried out using descriptive statistical methods to describe the overall evaluation results. Based on the findings, it is expected to provide an in-depth view of the differentiated learning program, contribute to the development of the program in the future, and become a guideline for improving the quality of mathematics learning in the Lebak district. The results of this training program evaluation show that the differentiated learning training activities have been well implemented in MGMP Mathematics Sub Rayon 2 Lebak District. This is evidenced by the level of teacher satisfaction in participating in the training, the majority of which were at scores 4 and 5, namely agreeing and strongly agreeing. This was also the case with the resource persons, materials, and training facilities, and organization. It is hoped that in the future continue to carry out ongoing training related to differentiated learning by current needs and to improve the competence of mathematics teachers in particular, as well as teachers of other subjects in general. (shrink)

En sciences sociales, les scientifiques utilisent les rapports des sujets sur leurs propres états mentaux dans leurs démarches expérimentales. Ainsi, l’introspection, ou la capacité des sujets à former des croyances sur leurs propres états mentaux, y joue un rôle important. Selon les tenants de l’introspectionnisme, l’introspection est une méthode, certes privée, mais qui permet de justifier directement des hypothèses scientifiques. Ainsi, contrairement aux méthodes utilisées dans les sciences de la nature qui se fondent uniquement sur des données publiques, les sciences (...) sociales utiliseraient des données subjectives pour justifier leurs hypothèses. Contre l’introspectionnisme, nous défendons que l’introspection n’est pas utilisée pour justifier directement les hypothèses, mais que sa place est plutôt similaire à celle d’un instrument de mesure des états et processus mentaux des sujets, susceptible d’être calibré, à la façon dont les instruments de mesure utilisés dans les sciences... (shrink)

Human-sciences research often focuses on social problems to create tools for solving them. Yet, in using common prejudices in gathering and sorting data on their subjects, they risk propagating those same prejudices. This article proposes that a major subject matter of human sciences is human concepts themselves. Concepts about “what we are,” individually and as a species, are deeply embedded, if not essential. It concludes that for greater precision, practitioners in human sciences must take maximum advantage of this characteristic (...) of the subject, making individuals’ concepts about what they consider themselves to be integral criteria of data gathering and sorting. (shrink)

With the current improvement of development towards pharmaceutical, distinctive ultrasound methodologies are open to find the fetal prosperity. It is analyzed with diverse clinical parameters with 2-D imaging and other test. In any case, prosperity desire of fetal heart still remains an open issue due to unconstrained works out of the hatchling, the minor heart appraise and inadequate of data in fetal echocardiography. The machine learning strategies can find out the classes of fetal heart rate which can beutilized for (...) earlier evaluating. With this background, we have utilized Cardiotocographic Fetal heart rate dataset removed from UCI Machine Learning Store for predicting the fetal heart rate health classes. The Prediction of fetal health rate are achieved in six ways. Firstly, the data set is preprocessed with Feature Scaling and missing values. Secondly, exploratory data investigation is done and the dispersion of target feature is visualized. Thirdly, the raw data set is fitted to all the classifiers and the performance is analysed before and after feature scaling. Fourth, the raw data set is subjected to undersampling methods like ClusterCentroids, RepeatedENN, AllKNN, CondensedNearestNeighbour, EditedNearestNeighbours, InstanceHardnessThreshold and NearMiss. Fifth, the undersampled dataset by above mentioned methods are fitted to all the classifiers and the performance is analyzed before and after feature scaling. Sixth, performance analysis is done using metrics like Precision, Recall, F-score, Accuracy and running time. The execution is done using python language under Spyder platform with Anaconda Navigator. Experimental results shows that the Decision Tree classifier tends to retain 98% before and after feature scaling for the underrsampling with EditedNearestNeighbours, RepeatedENN and AllKNN methods. (shrink)