Since the second half of the twentieth century, biomedical research has made increasing use of epidemiological methods to establish empirical evidence on a population level. This paper is about practices with data in epidemiological research, based on a case study in Denmark. I propose an epistemology of record linkage that invites exploration of epidemiological studies as heterogeneous assemblages. Focusing on data collecting, sampling and linkage, I examine how data organisation and processing become productive beyond the context of (...) their collection. The case study looks at how a local population database established in 1976 to investigate possibilities for the prevention of cardiovascular disease is used thirty years later to test hypotheses on the aetiology of breast cancer. For two breast cancer investigations based on the same core data set, I follow the underlying record linkage practice and describe how research objects such as molecular markers become relevant with respect to public health through information networking. Epidemiological association studies function as tools that performatively enrol different contexts into statistical risk estimation, thereby configuring options for research as well as for clinical testing and public health policy. (shrink)

Tradition wireless sensor networks transmit data by single or multiple hops. However, some sensor nodes close to a static base station forward data more frequently than others, which results in the problem of energy holes and makes networks fragile. One promising solution is to use a mobile node as a mobile sink, which is especially useful in energy-constrained networks. In these applications, the tour planning of MS is a key to guarantee the network performance. In this paper, a (...) novel strategy is proposed to reduce the latency of mobile data gathering in a WSN while the routing strategies and tour planning of MS are jointly optimized. First, the issue of network coverage is discussed before the appropriate number of clusters being calculated. A dynamic clustering scheme is then developed where a virtual cluster center is defined as the MS sojourn for data collection. Afterwards, a tour planning of MS based on prediction is proposed subject to minimizing the traveling distance to collect data. The proposed method is simulated in a MATLAB platform to show the overall performance of the developed system. Furthermore, the physical tests on a test rig are also carried out where a small WSN based on an unmanned aerial vehicle is developed in our laboratory. The test results validate the feasibility and effectiveness of the method proposed. (shrink)

Two experiments were conducted with variants of Wason's (1966) selection task. The common focus was the effect of differences in the sizes of the sets represented by P and not-Q in assertions of the form _If P then Q_ (conditional) or _All P are Q_ (categorical). Results support the conclusion that such set size differences affect the strategies people adopt when asked to determine, efficiently, the truth or falsity of such assertions, but they do not entirely negate the tendency to (...) select the term represented by P (the antecedent of the conditional or the subject of the categorical) in preference to the term represented by not-Q (the complement of the consequent of the conditional or the complement of the predicate of the categorical). Several possible explanations of this perseverance are considered. Results also support the conclusion that people find it easier to assess categorical assertions than logically equivalent conditional assertions. (shrink)

Metacognitive training (MCT) was developed to promote awareness of reasoning biases among patients with schizophrenia. While MCT has been translated into 31 languages, most MCT studies were conducted in Europe, including newer evidence recommending an individualized approach of delivery. As reasoning biases covered in MCT are separable processes and are associated with different symptoms, testing the effect of selected MCT modules would help to develop a targeted and cost-effective intervention for specific symptoms and associated mechanisms. This study tested the efficacy (...) of a 4-session metacognitive training for delusions, MCTd (in Traditional Chinese with cultural adaptations, provided individually), as an adjunct to antipsychotics in reducing severity and conviction of delusions, jumping to conclusions bias and belief inflexibility. Forty-four patients with delusions were randomized into the MCTd or the wait-list control condition. Patients on wait-list received the same MCTd after four weeks of treatment as usual. Assessment interviews took place before and after the treatment, and at 4-week follow-up. There was an additional baseline assessment for the controls. Jumping to conclusions and belief flexibility were measured by the beads tasks and the Maudsley Assessment of Delusions Scale. Attendance rate of the MCTd was satisfactory (84.5%). Compared to treatment as usual, there was a greater reduction in psychotic symptoms, delusional severity and conviction following MCTd. There was a large treatment effect size in improvement in belief flexibility. Improvement in reaction to hypothetical contradiction predicted treatment effect in positive symptoms and delusions. Jumping to conclusions bias was reduced following MCTd, although the treatment effect was not significantly larger than TAU. Our results support the use of process-based interventions that target psychological mechanisms underlying specific psychotic symptoms as adjuncts to more conventional approach. (shrink)

De nouvelles données enfantines pour l’étude du français : réflexions autour de leur collecte et de leur étiquetage.Cet article propose une réflexion autour d’un certain nombre de questions importantes auxquelles un chercheur doit répondre lorsqu’il construit son corpus en vue de recherches sur l’acquisition du langage. Dans ce cadre, deux étapes sont notamment discutées : la collecte des données (choix des informateurs, nombre, représentativité, etc.) et l’étiquetage de ces données, le but étant pour le chercheur de proposer une base de (...) données fiable et efficace à la communauté scientifique. (shrink)

Scientific knowledge production is currently affected by the dissemination of data on an unprecedented scale. Technologies for the automated production and sharing of vast amounts of data have changed the way in which data are handled and interpreted in several scientific domains, most notably molecular biology and biomedicine. In these fields, the activity of data gathering has become increasingly technology-driven, with machines such as next generation genome sequencers and mass spectrometers generating billions of data (...) points within hours, and with little need for human supervision. Given the relative ease and low costs with which datasets can be produced (that is, once a laboratory has been able to afford .. (shrink)

Data gathered by investigators are used to test the validity of a specific scientific hypothesis. When the hypothesis relates to the biology of a disease or its treatment, then data sets may contain specific and identifiable medical information. Since the information in a clinical data set was gathered to test a specific hypothesis and there is usually a sponsor interested in the outcome, the issue of who owns the data is a critical one. In my opinion, (...) data from both publicly and privately funded research should be made available, in a format that protects confidentiality and intellectual property rights, to interested and responsible parties within a reasonable period of time after publication. (shrink)

Data activism, promoting new forms of civic and political engagement, has emerged as a response to problematic aspects of datafication that include tensions between data openness and data ownership, and asymmetries in terms of data usage and distribution. In this article, we discuss MyData, a data activism initiative originating in Finland, which aims to shape a more sustainable citizen-centric data economy by means of increasing individuals' control of their personal data. Using data (...) gathered during long-term participant-observation in collaborative projects with data activists, we explore the internal tensions of data activism by first outlining two different social imaginaries – technological and socio-critical – within MyData, and then merging them to open practical and analytical space for engaging with the socio-technical futures currently in the making. While the technological imaginary favours data infrastructures as corrective measures, the socio-critical imaginary questions the effectiveness of technological correction. Unpacking them clarifies the kinds of political and social alternatives that different social imaginaries ascribe to the notions underlying data activism, and highlights the need to consider the social structures in play. The more far-reaching goal of our exercise is to provide practical and analytical resources for critical engagement in the context of data activism. By merging technological and socio-critical imaginaries in the work of reimagining governing structures and knowledge practices alongside infrastructural arrangements, scholars can depart from the most obvious forms of critique, influence data activism practice, and formulate data ethics and data futures. (shrink)

Hunting and gathering is, evolutionarily, the defining subsistence strategy of our species. Studying how children learn foraging skills can, therefore, provide us with key data to test theories about the evolution of human life history, cognition, and social behavior. Modern foragers, with their vast cultural and environmental diversity, have mostly been studied individually. However, cross-cultural studies allow us to extrapolate forager-wide trends in how, when, and from whom hunter-gatherer children learn their subsistence skills. We perform a meta-ethnography, which (...) allows us to systematically extract, summarize, and compare both quantitative and qualitative literature. We found 58 publications focusing on learning subsistence skills. Learning begins early in infancy, when parents take children on foraging expeditions and give them toy versions of tools. In early and middle childhood, children transition into the multi-age playgroup, where they learn skills through play, observation, and participation. By the end of middle childhood, most children are proficient food collectors. However, it is not until adolescence that adults (not necessarily parents) begin directly teaching children complex skills such as hunting and complex tool manufacture. Adolescents seek to learn innovations from adults, but they themselves do not innovate. These findings support predictive models that find social learning should occur before individual learning. Furthermore, these results show that teaching does indeed exist in hunter-gatherer societies. And, finally, though children are competent foragers by late childhood, learning to extract more complex resources, such as hunting large game, takes a lifetime. (shrink)

Farming is undergoing a digital revolution. Our existing review of current Big Data applications in the agri-food sector has revealed several collection and analytics tools that may have implications for relationships of power between players in the food system. For example, Who retains ownership of the data generated by applications like Monsanto Corproation's Weed I.D. “app”? Are there privacy implications with the data gathered by John Deere's precision agricultural equipment? Systematically tracing the digital revolution in agriculture, and (...) charting the affordances as well as the limitations of Big Data applied to food and agriculture, should be a broad research goal for Big Data scholarship. Such a goal brings data scholarship into conversation with food studies and it allows for a focus on the material consequences of big data in society. (shrink)

Educational research is dominated by a particular model: data is gathered and analysed. Much literature on methods concerns either ways of processing data, or ethical issues regarding its collection and handling. The present paper looks beyond these matters to the taken‐for‐granted idea of data itself. What can be meant by ‘data’? How does this connect with ideas of the given? What is the place of giving in education—in teaching and learning, in research itself? These issues are (...) explored in the light of information technology’s impact on research, uncovering ethical dimensions that the seeming naturalness of data otherwise obscures. (shrink)

Low levels of public trust in data practices have led to growing calls for changes to data-driven systems, and in the EU, the General Data Protection Regulation provides a legal motivation for such changes. Data management is a vital component of data-driven systems, but what constitutes ‘good’ data management is not straightforward. Academic attention is turning to the question of what ‘good data’ might look like more generally, but public views are absent from (...) these debates. This paper addresses this gap, reporting on a survey of the public on their views of data management approaches, undertaken by the authors and administered in the UK, where departure from the EU makes future data legislation uncertain. The survey found that respondents dislike the current approach in which commercial organizations control their personal data and prefer approaches that give them control over their data, that include oversight from regulatory bodies or that enable them to opt out of data gathering. Variations of data trusts – that is, structures that provide independent stewardship of data – were also preferable to the current approach, but not as widely preferred as control, oversight and opt out options. These features therefore constitute ‘good data management’ for survey respondents. These findings align only in part with principles of good data identified by policy experts and researchers. Our findings nuance understandings of good data as a concept and of good data management as a practice and point to where further research and policy action are needed. (shrink)

There is a well-entrenched schism on the frequency, intensity, and evolutionary significance of warfare among hunter-gatherers compared with large-scale societies. To simplify, Rousseauians argue that warfare among prehistoric and contemporary hunter-gatherers was nearly absent and, if present, was a late cultural invention. In contrast, so-called Hobbesians argue that violence was relatively common but variable among hunter-gatherers. To defend their views, Rousseauians resort to a variety of tactics to diminish the apparent frequency and intensity of hunter-gatherer warfare. These tactics include redefining (...) war, censoring ethnographic accounts of warfare in comparative analyses, misconstruing archaeological evidence, and claiming that outside contact inflates the intensity of warfare among hunter-gatherers. These tactics are subject to critical analysis and are mostly found to be wanting. Furthermore, Hobbesians with empirical data have already established that the frequency and intensity of hunter-gatherer warfare is greater compared with large-scale societies even though horticultural societies engage in warfare more intensively than hunter-gatherers. In the end I argue that although war is a primitive trait we may share with chimpanzees and/or our last common ancestor, the ability of hunter-gatherer bands to live peaceably with their neighbors, even though war may occur, is a derived trait that fundamentally distinguishes us socially and politically from chimpanzee societies. It is a point often lost in these debates. (shrink)

Case Study research is characterized by the employment of multiple data gathering methods. In this paper, I examine the concurrent use of participant observation and qualitative interviews. The question I examine is: what is the rationale behind their combination in case study research? In the literature on case study research, the two most common reasons for using multiple methods appeal to comprehensiveness and convergent confirmation respectively. I argue that there is a third significant, yet overlooked, way to motivate (...) the joint use of participant observation and qualitative interviews: the methods may generate complementary evidence and this puts the researcher in a better position to confirm that her data manifest central epistemic values and so are suitable as basis for providing an adequate answer to her research question. I refer to this as the rationale of blended epistemic value validation. (shrink)

The processing of sensitive information in the health field is subject to rigorous standards that guarantee the protection of information confidentiality. Recently, the Italian Data Protection Authority (Garante per la Protezione dei Dati Personali) stated their formal opinion on a standard procedure in dental offices involving the submission of a questionnaire that includes the patient's health status. HIV infection status is included on the form. The Authority has stated that all health data collection must be in accordance with (...) the current Italian normative framework for personal data protection and respect the patient's freedom. This freedom allows the patient to decide, in a conscious and responsible way, whether to share health information with health personnel without experiencing any prejudice in the provision of healthcare requested. Moreover, data collection must be relevant and cannot exceed the principles of treatment goals with reference to the specific care of the concerned person. However, the need for recording information regarding HIV infection at the first appointment, regardless of the clinical intervention or therapeutic plan that needs to be conducted, should not alter the standard protection measures of the healthcare staff. In fact, these measures are adopted for every patient. (shrink)

In the early days of ethics consultation, two pioneer consultants noted that one of their important functions was to gather missing information and correct misinformation relevant to the facts of t...

Through their transcript products genes regulate the rates at which an immense variety of transcripts and subsequent proteins occur. Understanding the mechanisms that determine which genes are expressed, and when they are expressed, is one of the keys to genetic manipulation for many purposes, including the development of new treatments for disease. Viewing each gene in a genome as a distinct variable that is either on or off, or more realistically as a continuous variable, the values of some of these (...) variables influence the values of others through the regulatory proteins they express, including, of course, the possibility that the rate of expression of a gene at one time may, in various circumstances, influence the rate of expression of that same gene at a later time. If we imagine an arrow drawn from each gene expression variable at a given time to a gene variable whose expression it influences a short while after, the result is a network, technically a directed acyclic graph. For example, the DAG in Figure 1 is a representation of a system in which the expression level of gene G1 at time 1 ) causes the expression level of G2, which in turn causes the expression level of G3. The arrows in Figure 1 which do not have a variable at their tails are “error terms” which represent all of the causes of a variable other than the ones explicitly represented in the DAG. The DAG describes more than associations—it describes causal connections among gene expression rates. A shock to a cell—by mutation, heating, chemical treatment, etc. may alter the DAG describing the relations among gene expressions, for example by activating a gene that was otherwise not expressed, producing a cascade of new expression effects. Although “knockout” experiments can reveal some of the underlying causal network of gene expression levels, unless guided by information from other sources, such experiments are limited in how much of the network structure they can reveal, due to the sheer number of possible combinations of experimental manipulations of genes necessary to reveal the complete causal network. Recent developments have made it possible to compare quantitatively the expression of tens of thousands of genes in cells from different sources in a single experiment, and to trace gene expression over time in thousands of genes simultaneously. cDNA microarrays are already producing extensive data, much of it available on the web. Thus there are calls for analytic software that can be applied to microarray and other data to help infer regulatory networks. In this paper we will review current techniques that are available for searching for the causal relations between variables, describe algorithmic and data gathering obstacles to applying these techniques to gene expression levels, and describe the prospects for overcoming these obstacles. (shrink)

A research project was conducted which explored LGBT hate crime. Participants were invited to share their narratives and personal experiences of hate crime, discrimination and violence through semi-structured interviews. The study helped us understand how people who experience ‘hate’ responded to, managed and reconciled the identities for which they were victimized. This case study focuses on a situation where a research participant requested a copy of an interview they gave for the hate crime project. The interview copy was to be (...) used for the participant’s own personal purposes. The participant’s request potentially risked the contamination of ethical data collection, with their own covert data gathering. The ethical implications of this scenario raise many questions for ethicists and researchers to discuss. (shrink)

Doctoral graduates in philosophy are an excellent source of information about the discipline: they are at the cutting edge of research trends, have an inside view of researchfocused departments, and their employment prospects provide early insights on the future health of the discipline. We report on the results of a survey sent to recent PhD graduates and current students, as well as data gathering efforts by Academic Placement Data and Analysis that have taken place over the past (...) ten years. In this report we especially focus on demographic representation, program ratings, academic job placement, and non-academic careers. (shrink)

This paper draws lessons from the COVID-19 pandemic for the relationship between data-driven decision making and global development. The lessons are that users should keep in mind the shifting value of data during a crisis, and the pitfalls its use can create; predictions carry costs in terms of inertia, overreaction and herding behaviour; data can be devalued by digital and data deluges; lack of interoperability and difficulty reusing data will limit value from data; (...) class='Hi'>data deprivation, digital gaps and digital divides are not just a by-product of unequal global development, but will magnify the unequal impacts of a global crisis, and will be magnified in turn by global crises; having more data and even better data analytical techniques, such as artificial intelligence, does not guarantee that development outcomes will improve; decentralised data gathering and use can help to build trust – particularly important for coordination of behaviour. (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)

By synthesizing evolutionary, attachment, and acoustic perspectives, Soltis has provided an innovative model of infant cry acoustics and parental responsiveness. We question some of his hypotheses, however, because of the limited extant data on infant crying among hunter-gatherers. We also question Soltis' distinction between manipulative and honest signaling based upon recent contributions from attachment theory.

AbstractAdvances in precision agriculture, driven by big data technologies and machine learning algorithms can transform agriculture by enhancing crop and livestock productivity and supporting faster and more accurate on and off-farm decision making. However, little is known about how PA can influence farmers’ sense of self, their skills and competencies, and the meanings that farmers ascribe to farming. This study is animated by scholarly commitment to social identity research, and draws from socio-cyber-physical systems research, domestication theory, and activity theory. (...) This conceptualization of PA within these theoretical perspectives helps to render visible how big agricultural data and machine learning algorithms can affect meaning, doing, and being for US farmers. Through analysis of data from six focus group discussions and follow-up surveys with stakeholders across the PA value chain, this paper shows that PA tools can necessitate farmers to learn and develop new competencies such as flying drones and interpreting yield maps. At the same time, PA can shape new meaning of farm work and new expectation about a ‘good farmer’, changing what it means to be a ‘successful’ farmer from someone who is not only a data observer or data gatherer but also validators of PA models by using their local knowledge of agronomic and environmental phenomenon. We conclude that PA can alter social expectations about farming by reorienting the role of farmers. Policymakers and agriculture extension and outreach programmers can develop more socially relevant PA knowledge and innovation if they can attend to both new and traditional ‘good farmer’ identities. (shrink)

The relatively recent increase in empirical research conducted in business ethics has been accompanied by a growing literature which addresses its present shortcomings and continuing challenges. Particular attention has been focused on the difficulties of obtaining valid and reliable primary data. However, little or no attention has been paid to the use of secondary data. The aim of this paper is to stimulate the interest of business ethics researchers in using secondary data, either as a substitute or (...) complement for primary data, bearing in mind both the benefits and shortcomings of doing so. It is suggested that secondary data not only offer advantages in terms of cost and effort, as conventionally described in research methods books, but also that in certain cases their use may overcome some of the difficulties that particularly afflict business ethics researchers in the gathering of primary data. In order to help business ethicists respond to this call for greater consideration of the potential offered by secondary data, the wide variety of forms that such data may take is indicated and a number of themes regarding their use discussed. (shrink)

Hunter-gatherer punishment involves costs and benefits to individuals and groups, but the costs do not necessarily fit with the assumptions made in models that consider punishment to be altruistic – which brings in the free-rider problem and the problem of second-order free-riders. In this commentary, I present foragers' capital punishment patterns ethnographically, in the interest of establishing whether such punishment is likely to be costly; and I suggest that in many cases abstentions from punishment that might be taken as defections (...) by free-riders are actually caused by social-structural considerations rather than being an effect of free-rider genes. This presentation of data supplements the ethnographic analysis provided by Guala. (shrink)

The literature on human mate preferences is vast but most data come from studies on college students in complex societies, who represent a thin slice of cultural variation in an evolutionarily novel environment. Here, I present data on the mate preferences of men and women in a society of hunter-gatherers, the Hadza of Tanzania. Hadza men value fertility in a mate more than women do, and women value intelligence more than men do. Women place great importance on men’s (...) foraging, and both sexes rate character as important. Unlike college students, Hadza men place considerable importance on women being hard-working, and Hadza women cite looks about as often as men do. (shrink)

Recently, big data analytics have gained significant attention in healthcare industry due to generation of massive quantities of data in various forms such as electronic health records, sensors, medical imaging, and pharmaceutical details. However, the data gathered from various sources are intrinsically uncertain owing to noise, incompleteness, and inconsistency. The analysis of such huge data necessitates advanced analytical techniques using machine learning and computational intelligence for effective decision making. To handle data uncertainty in healthcare sector, (...) this article presents a novel metaheuristic rough set-based feature selection with rule-based medical data classification technique on MapReduce framework. The proposed MRSFS-RMDC technique designs a butterfly optimization algorithm for minimal rough set selection. In addition, Hadoop MapReduce is applied to process massive quantity of data. Moreover, a rule-based classification approach named Repeated Incremental Pruning for Error Reduction is used with the inclusion of a set of conditional rules. The RIPPER will scale in a linear way with the number of training records utilized and is suitable to build models with data uncertainty. The proposed MRSFS-RMDC technique is validated using benchmark dataset and the results are inspected under varying aspects. The experimental results highlighted the supremacy of the MRSFS-RMDC technique over the recent state of art methods in terms of different performance measures. The proposed methodology has achieved a higher F-score of 96.49%. (shrink)

The paper discusses the problems in the detection of security information in legal and other administrative data. The authors analyse the prospects of the use of datamining in the solution of two key problems: abundance and indirectness of these data. Security research uses two kinds of data. The first one is scientific data, designed and gathered specially for the verification of certain security theories. They are the data of criminological, sociological, psychological surveys, experimental data, (...) etc. The second kind is data that are not designed for security research. Most of the data are the by-products of the national legal system, especially its criminal justice, of national and local institutions responsible for the maintenance of public order, and of other public agencies. All the data provide huge amounts of information destined to control and direct the activities of these institutions. There are two kinds of problems in the use of this information in security study. First, this information has to be ‘decoded’ from data describing the activities of related institutions. Second, data on security are lost in huge amounts of other public data. Thus, they have to be ‘mined’. The paper discusses the prospects of the modern information proceeding method—data-mining in the solution of both problems. A new concept of data mining as a meta-procedure is proposed. The object of this meta-procedure is supposed to be the integration of multiple current theories (for example, criminal security) and related statistical procedures. A general algorithm of such data-mining is proposed. (shrink)

In this paper, we reflect on the disciplinary contours of contemporary sociology, and social science more generally, in the age of ‘big and broad’ social data. Our aim is to suggest how sociology and social sciences may respond to the challenges and opportunities presented by this ‘data deluge’ in ways that are innovative yet sensitive to the social and ethical life of data and methods. We begin by reviewing relevant contemporary methodological debates and consider how they relate (...) to the emergence of big and broad social data as a product, reflexive artefact and organizational feature of emerging global digital society. We then explore the challenges and opportunities afforded to social science through the widespread adoption of a new generation of distributed, digital technologies and the gathering momentum of the open data movement, grounding our observations in the work of the Collaborative Online Social Media ObServatory project. In conclusion, we argue that these challenges and opportunities motivate a renewed interest in the programme for a ‘public sociology’, characterized by the co-production of social scientific knowledge involving a broad range of actors and publics. (shrink)

It is increasingly recognised that evidence generated using “real-world data” is crucial for assessing the safety and effectiveness of health-related interventions. This, however, raises a number of issues, including those related to the quality of RWD, and of the scientific methods used to generate evidence from it, and the potential for those gathering and using RWD be driven by commercial, political, professional or personal self-interest. This article is an application of the framework presented in this issue of ABR. (...) Please refer to that article for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end to demonstrate how those generating or using RWD can make use of values when deliberating about ethical issues. (shrink)

Adolescent gender-based violence prevention and sexuality education is a topic of current concern given the increasing numbers of violence directed at girls. International organizations indicate that one in three girls aged 15 to 19 have experienced gender-based violence in their sexual relationships that this risk may be as much as 3–4 times higher for girls with disabilities. Following the good results obtained in the research project “Free_Teen_Desire” led by the University of Cambridge and funded by the Marie Curie Actions Program (...) in the prevention of gender violence in adolescents through Dialogic Feminist Gatherings (DFG), the aim of study is to analyze Its transfer and impact on adolescent girls with intellectual disabilities. The DFGs are here understood as generators of a more dialogic environment for girls in general and we wonder if and how It is extended to the context of girls with disabilities. Thus, the research takes the form of a case study with a communicative approach on a DFGs. The intervention is carried out in a special school located in Valencia during the 2018–2019 and 2019–2020 academic years with a group of 19 non-mixed female students, female teachers, and the mother of one of the students. The study analyzes which are the transfer criteria to incorporate the DFGs in a special education context and what is their impact on the prevention of gender violence in girls with disabilities. The data collection techniques consist of two in-depth interviews, analysis of the field diary of 24 intervention sessions and a focus group with seven teachers. It is demonstrated that DFGs are successfully transferred to the special education context of the case study. The results show how contexts of safety, solidarity and friendship are generated which protect adolescent girls with disabilities from relationships with gender violence. (shrink)

Key to precision medicine is the development of expert database projects that gather data, integrate them in the pre-existing database, and publish the product of their processing for others to make use of. Increasingly, it is required that data infrastructure managers and curators pursue and lead research projects on the data so as to learn about new ways data could be used or information that could be potentially generated from them. I call these efforts “data (...) curation-research” and use the case study of COSMIC, the Catalogue of Somatic Mutations in Cancer, to analyze the contextual factors shaping the science of data curation-research. I build on March’s organizational learning categories of exploitation and exploration to place these factors within a theory of organizational change and innovation, and contribute to a richer picture of the social drivers of cancer genomics. (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)

Discussion of uses of biomedical data often proceeds on the assumption that the data are generated and shared solely or largely within the health sector. However, this assumption must be challenged because increasingly large amounts of health and well-being data are being gathered and deployed in cross-sectoral contexts such as social media and through the internet of things and wearable devices. Cross-sectoral sharing of data thus refers to the generation, use and linkage of biomedical data (...) beyond the health sector. This paper considers the challenges that arise from this phenomenon. If we are to benefit fully, it is important to consider which ethical values are at stake and to reflect on ways to resolve emerging ethical issues across ecosystems where values, laws and cultures might be quite distinct. In considering such issues, this paper applies the deliberative balancing approach of the Ethics Framework for Big Data in Health and Research to the domain of cross-sectoral big data. Please refer to that article for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end. (shrink)

Research in nonindustrial small-scale societies challenges the common perception that human childhood is universally characterized by a long period of intensive adult investment and dedicated instruction. Using return rate and time allocation data for the Savanna Pumé, a group of South American hunter-gatherers, age patterns in how children learn to become productive foragers and from whom they learn are observed across the transition from childhood to adolescence. Results show that Savanna Pumé children care for their siblings, are important economic (...) contributors, learn by doing rather than by instruction, and spend their time principally in the company of other children. This developmental experience contrasts with that of children in postindustrial societies, who are dependent on adults, often well past maturity; learn in formal settings; and spend much of their time in the company of adults. These differences raise questions about whether normative behaviors observed in postindustrial societies are representative of human children. This comparison also identifies the potential mismatch between hunter-gatherer and postindustrial societies in the extent to which children may be well adapted to learn from and teach each other. In particular, spending time in autonomous work and play groups develops the cooperation and coordination skills that are foundational to human subsistence and growing up to be socially and productively adept adults and parents. (shrink)

The potential for biases being built into algorithms has been known for some time, yet literature has only recently demonstrated the ways algorithmic profiling can result in social sorting and harm marginalised groups. We contend that with increased algorithmic complexity, biases will become more sophisticated and difficult to identify, control for, or contest. Our argument has four steps: first, we show how harnessing algorithms means that data gathered at a particular place and time relating to specific persons, can be (...) used to build group models applied in different contexts to different persons. Thus, privacy and data protection rights, with their focus on individuals, do not protect from the discriminatory potential of algorithmic profiling. Second, we explore the idea that anti-discrimination regulation may be more promising, but acknowledge limitations. Third, we argue that in order to harness anti-discrimination regulation, it needs to confront emergent forms of discrimination or risk creating new invisibilities, including invisibility from existing safeguards. Finally, we outline suggestions to address emergent forms of discrimination and exclusionary invisibilities via intersectional and post-colonial analysis. (shrink)

Abstract When new methods of generating information about individuals leave the confined space of research application the possibility of morally dubious application arises. The current propagation of neuroscientific diagnostics leads to new possibilities of misuse and accordingly new needs for the protection of individual privacy emerge. While most current privacy discussion focuses on sensationalist applications which aim/claim to gather information about psychological traits or even the content of thoughts, the more sober but much more realistic endeavour to gather health (...) class='Hi'>data from research or medical imaging studies is widely neglected. I will try to answer the question if and in how far data from neuroscientific imaging technologies require special protection. Two developments form the background of the ethical discussion: the increased diagnostic power of neuroimaging techniques and the wider distribution of this technology beyond specialized medical offices and clinics. The first development is likely to broaden the scope of data, which are considered relevant for health care and related decisions. The latter is likely to widen the scope of persons who might have access to diagnostic results without at the time taking the role of a doctor towards the person diagnosed. I will argue that neuroimaging data are currently primarily medical data and that the associated standards of consent and confidentiality are worth protecting. Even nonmedical applications of neuroimaging technology inherit too much of the diagnostic power for which they were originally invented, for it to be advisable to drop the accompanying consent and confidentiality requirements. (shrink)

Challenging the posthumanist canon which celebrates the pre-eminence of matter, Ruth Miller, inFlourishingThoughtargues that what nonhuman systems contribute to democracy is thought. Drawing on recent feminist theories of nonhuman life and politics, Miller shows that reproduction and flourishing are not antithetical to contemplation and sensitivity. After demonstrating processes of life and processes of thought are indistinguishable, Miller finds that four menacing accumulations of matter and information--global surveillance, stored embryos, human clones, and reproductive trash--are politically productive rather than threats to democratic (...) politics. As a consequence, she questions the usefulness of individual rights such as privacy and dignity, contests the value of the rational metaphysics underlying human-centered political participation, and re-evaluates the gender relations that derive from this type of participation. Ultimately, in place of these human-centered structures, Miller posits a more meditative mode of democratic engagement. Miller's argument has shattering implications for the debates over the proper use and disposal of embryonic tissue, alarms about data gathering by the state and corporations, and other major ethical, social, and security issues. (shrink)

Scientific research on consciousness is attempting to gather data about the relationship between consciousness and the physical world. The basic procedure is to measure consciousness through first-person reports, measure the physical world and look for correlations between these sets of measurements. While this work has focused on neural correlates of consciousness, it has also been proposed that information states in the brain might be linked to consciousness. This paper uses Floridi’s distinction between dedomena, data and information to state (...) this claim more precisely and suggests that the best starting point for this work is the potential correlation between data patterns and consciousness. Floridi’s method of levels of abstraction is used to understand how data can be measured at different levels of abstraction in the brain and the paper examines a number of problems with this work, which could make it difficult to prove that data patterns are correlated with consciousness. (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)

Lewis et al. (2011) attempted to restore the reputation of Samuel George Morton, a 19th century physician who reported on the skull sizes of different folk-races. Whereas Gould (1978) claimed that Morton's conclusions were invalid because they reflected unconscious bias, Lewis et al. alleged that Morton's findings were, in fact, supported, and Gould's analysis biased. We take strong exception to Lewis et al.’s thesis that Morton was “right.” We maintain that Gould was right to reject Morton's analysis as inappropriate and (...) misleading, but wrong to believe that a more appropriate analysis was available. Lewis et al. fail to recognize that there is, given the dataset available, no appropriate way to answer any of the plausibly interesting questions about the “populations” in question (which in many cases are not populations in any biologically meaningful sense). We challenge the premise shared by both Gould and Lewis et al. that Morton's confused data can be used to draw any meaningful conclusions. This, we argue, reveals the importance of properly focusing on the questions asked, rather than more narrowly on the data gathered. (shrink)

As the recent inaugural Ethical, Legal, and Social Issues 2.0 conference made clear, the effects of information communication technology are pervasive in biomedical research. Data initiatives are arising in all corners of biomedicine. Data sharing efforts already promised to surpass even the ambitious goals of the National Human Genome Research Institute, only 5 years after publication of its 10-year vision. ELSI research was established, in part, to address challenges of open data access and data sharing. However, (...) by and large, ELSI research projects address particular concerns of a given population, jurisdiction, type of research practice or type of data. This does not necessarily facilitate coherent data policy for sustainable data stewardship. Forward-looking, data friendly strategies need to be considered. Orchestration strategies are needed which overcome barriers to collective action. Here we present challenges policymakers face, and suggest three basics steps towards meeting them. First, policymakers must recognise the systematic change that occurs when ICT enables dataflow itself to become an organising principle of biomedical research. Second, methods for identifying and gathering types of metadata suitable for ELSI research ought to be developed and regulated. Third, policymakers need to organise in ways that mirror the new vision for data-enabled research that data technologies are making possible, as ELSI 2.0 encourages researchers to do. Taking these steps will help ensure research evolves in ways that warrants trust of the public while still supporting widespread ethical access to necessary data, research subjects, samples and findings. (shrink)

The accuracy of financial data within electronic accounting information systems plays a vital role in improving business efficiency. This paper investigates how the accuracy of data on financial information systems moderates the relationship between these systems and business efficiency. A questionnaire survey was applied to a sample of companies that specialise in the field of accounting information systems. The gathered data was analysed using partial least squares structural equation modelling. To be precise, financial data accuracy shows (...) a higher positive return on electronic accounting information systems in the alignment of business capabilities. To achieve the highest possible level of automated accounting systems, financial information accuracy is crucial. Data analysis techniques and overall improvement of the accounting information systems industry can achieve this. (shrink)

As we move our social institutions from paper and ink based operations to the electronic medium, we invisibly create a type of surveillance society, a panopticon society. It is not the traditional surveillance society in which government officials follow citizens around because they are concerned about threats to the political order. Instead it is piecemeal surveillance by public and private organizations. Piecemeal though it is, It creates the potential for the old kind of surveillance on an even grander scale. The (...) panopticon is the prison environment described by Foucault in which prison cells are arranged in a large circle with the side facing the inside of the circle open to view. The guard tower is placed in the middle of the circle so that guards can see everything that goes on in every cell. When we contemplate all the electronic data that is now gathered about each of us as we move through our everyday lives --- intelligent highway systems, consumer transactions, traffic patterns on the internet, medical records, financial records, and so on --- there seems little doubt that we are moving into a panopticon. The social issues that arise from this are too numerous to detail here, but data retention is an important part of it. In the paper-and-ink world, documents are filed, files are boxed, boxes are put away or thrown away. The capacity for data retrieval and manipulation is, thereby, limited by the sheer difficulty and cost of storing, finding, searching, and manipulating large numbers of paper files. This inconvenience functions as a mechanism whereby the system forgets past information, not unlike the way we ourselves forget. However, the story is very different in the digital world; digital information is easy to store, easy to search and manipulate, and inexpensive to keep over extensive periods of time. Digitalized information systems tend, therefore, to collect extensive ancillary information and to retain this information indefinitely. Such lack of forgetfulness is likely to hamper the ability of individuals to shed their past, and start over with a clean slate. Concerns about data retention were expressed in the early literature on the social impact of computing, but for the most part the issue has dropped from sight. Rarely, has the social good of discarding accumulated personal data been addressed. In this paper, we want to make the case by examining diverse cases in which retention of information by either business or governmental institutions hinders the ability of individuals to start over or to act autonomously. We hope our argument for the good of forgetfulness will challenge the standard framework in which such issues have traditionally been debated. The privacy debate exemplifies the traditional framework insofar as it has been characterized as involving an inherent tension between, on the one hand, the needs of organizations and institutions for more accurate and efficient information systems so as to further their goals and, on the other hand, the desire of individuals to have information about them kept private. Regan argues against this framing of the privacy issue in favor of one that recognizes the social importance of personal privacy. We will examine the non-forgetfulness of information systems as a problem threatening not just individual interests but social good as well. Cryptography is often cited as the technology that will give us privacy and mediate against surveillance. One of the uses of cryptography, encryption, will allow us, some hope, to create confidentiality and relationships of trust that will facilitate many of the social arrangements we now have and perhaps make them even more secure than they are now. Electronic cash, for example, could be created in such a form that it would have the anonymity associated now with hard cash Others are less optimistic of the potential for cryptography to re-create relationships of trust in the new medium. One important point that already seems clear is that even if encryption technology will protect the confidentiality and integrity of electronic transactions and data, it will NOT stop the observation of traffic patterns on networks. This seems an important distinction to put on the table. Our patterns of communication will continue to be available, no matter what is encrypted, and an amazing amount of information can be gleaned from this data. In a sense, it means content integrity but no anonymity. This will indubitably impact how we interact and with whom we interact. (shrink)

When making a decision, humans consider two types of information: information they have acquired through their prior experience of the world, and further information they gather to support the decision in question. Here, we present evidence that data from search engines such as Google can help us model both sources of information. We show that statistics from search engines on the frequency of content on the Internet can help us estimate the statistical structure of prior experience; and, specifically, we (...) outline how such statistics can inform psychological theories concerning the valuation of human lives, or choices involving delayed outcomes. Turning to information gathering, we show that search query data might help measure human information gathering, and it may predict subsequent decisions. Such data enable us to compare information gathered across nations, where analyses suggest, for example, a greater focus on the future in countries with a higher per capita GDP. We conclude that search engine data constitute a valuable new resource for cognitive scientists, offering a fascinating new tool for understanding the human decision-making process. (shrink)