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)

Those who wish to deny some instance of environmental injustice often attempt to place inappropriate evidentiary burdens on scientists who show disproportionate pollution effects on vulnerable populations. One such evidentiary standard is the epidemiological-evidence rule (EER). According to EER, legitimate causal inferences about pollution-related harm (and actions to reduce probable environmental injustice) require human-epidemiological data, not merely good animal or laboratory data. This article summarizes the grounds for supporting EER, evaluates central scientific problems with EER, assesses key ethical (...) difficulties with EER, then concludes that EER ought not be used either to deny otherwise-probable environmental injustice or to delay possible action to correct well-documented pollution-related harms. (shrink)

Social media commentary, satellite imagery and GPS data are a part of ‘alternative data’, that is, data that originate outside of the standard repertoire of market data but are considered useful for predicting stock prices, detecting different risk exposures and discovering new price movement indicators. With the availability of sophisticated machine-learning analytics tools, alternative data are gaining traction within the investment management and algorithmic trading industries. Drawing on interviews with people working in investment management and (...) algorithmic trading firms utilizing alternative data, as well as firms providing and sourcing such data, we emphasize social media-based sentiment analytics as one manifestation of how alternative data are deployed for stock price prediction purposes. This demonstrates both how sentiment analytics are developed and subsequently utilized by investment management firms. We argue that ‘alternative data’ are an open-ended placeholder for every data source potentially relevant for investment management purposes and harnessing these disparate data sources requires certain standardization efforts by different market participants. Besides showing how market participants understand and use alternative data, we demonstrate that alternative data often undergo processes of prospecting and assetization. We further contend that the widespread embracement of alternative data in investment management and trading encourages a financialization process at the data level which raises new governance issues. (shrink)

The aim of this work is to identify and analyze a set of challenges that are likely to be encountered when one embarks on fieldwork in linguistic communities that feature small, young, and/or non-standard languages with a goal to elicit big sets of rich data. For each challenge, we (i) explain its nature and implications, (ii) offer one or more examples of how it is manifested in actual linguistic communities, and (iii) where possible, offer recommendations for addressing it effectively. (...) Our list of challenges involves static characteristics (e.g., absence of orthographic conventions and how it affects data collection), dynamic processes (e.g., speed of language change in small languages and how it affects longitudinal collection of big amounts of data), and interactive relations between non-dynamic features that are nevertheless subject to potentially rapid change (e.g., absence of standardized assessment tools or estimates for psycholinguistic variables). The identified challenges represent the domains of data collection and handling, participant recruitment, and experimental design. Among other issues, we discuss population limits and degree of power, inter- and intraspeaker variation, absence of metalanguage and its implications for the process of eliciting acceptability judgments, and challenges that arise from absence of local funding, conflicting regulations in relation to privacy issues, and exporting large samples of data across countries. Finally, the ten experimental challenges presented cover a broad typological spectrum, encompassing both spoken and sign, extant and nearly extinct languages. (shrink)

This article analyzes the experiences of ecologists who used data they did not collect themselves. Specifically, the author examines the processes by which ecologists understand and assess the quality of the data they reuse, and investigates the role that standard methods of data collection play in these processes. Standardization is one means by which scientific knowledge is transported from local to public spheres. While standards can be helpful, the results show that knowledge of the local context (...) is critical to ecologists' reuse of data. Yet, this information is often left behind as data move from the private to the public world. The knowledge that ecologists acquire through fieldwork enables them to recover the local details that are so critical to their comprehension of data collected by others. Social processes also play a role in ecologists' efforts to judge the quality of data they reuse. (shrink)

In Roper v. Simmons (2005) the United States Supreme Court announced a paradigm shift in jurisprudence. Drawing specifically on mounting scientific evidence that adolescents are qualitatively different from adults in their decision-making capacities, the Supreme Court recognized that adolescents are not adults in all but age. The Court concluded that the overwhelming weight of the psychological and neurophysiological data regarding brain maturation supports the conclusion that adolescents are qualitatively different types of agents than adult persons. The Supreme Court further (...) solidified its position regarding adolescents as less than fully mature and responsible decisionmakers in Graham v. Florida (2010) and Miller v. Alabama (2012). In each case, the Court concluded that the scientific evidence does not support the conclusion that children under 18 years of age possess adult capacities for personal agency, rationality, and mature choice. This study explores the implications of the Supreme Court decisions in Roper v. Simmons, Graham v. Florida, and Miller v. Alabama for the “mature minor” standard for medical decision making. It argues that the Supreme Court’s holdings in Roper, Graham, and Miller require no less than a radical reassessment of how healthcare institutions, courts of law, and public policy are obliged to regard minors as medical decisionmakers. The “mature minor” standard for medical decision making must be abandoned. (shrink)

Benchmarks against which healthcare ethics consultation (HCEC) services can assess their performance are needed. As first-generation benchmarks continue to be developed, it is the obligation of the field to continually evaluate how these measures reflect the performance of any single HCEC service. This will be possible only with widespread reporting of standardized data points. In their article in this issue of The Journal of Clinical Ethics, Glover and colleagues provide a valuable preliminary approach for assessing appropriate consult volumes for (...) a HCEC service. The limitations of their study read as a call to action for the field of clinical ethics to expand and standardize data reporting so that more robust metrics can be developed. In response to this call by Glover and colleagues, the Cleveland Clinic HCEC service provides consult data from 2015 through 2019 for one of its medical centers, and offers an additional volumebased metric, consult-to-ICU-to-bed ratio (CiBR), that may add nuance to any normative assessment of HCEC service consult volume. Given that volume-based metrics are the native language of the clinical environment, efforts to improve such metrics in the field through transparency and standardization are warranted. However, the expositive power of volume-based metrics is limited; additional domains related to quality and outcomes are needed. (shrink)

Data Transfer Service (DTS) is an open-source project that is developing a document-centric message model for describing a bulk data transfer activity, with an accompanying set of loosely coupled and platform-independent components for brokering the transfer of data between a wide range of (potentially incompatible) storage resources as scheduled, fault-tolerant batch jobs. The architecture scales from small embedded deployments on a single computer to large distributed deployments through an expandable ‘worker-node pool’ controlled through message-orientated middleware. Data (...) access and transfer efficiency are maximized through the strategic placement of worker nodes at or between particular data sources/sinks. The design is inherently asynchronous, and, when third-party transfer is not available, it side-steps the bandwidth, concurrency and scalability limitations associated with buffering bytes directly through intermediary client applications. It aims to address geographical–topological deployment concerns by allowing service hosting to be either centralized (as part of a shared service) or confined to a single institution or domain. Established design patterns and open-source components are coupled with a proposal for a document-centric and open-standards-based messaging protocol. As part of the development of the message protocol, a bulk data copy activity document is proposed for the first time. (shrink)

Surveillance in public health is the means by which people who are responsible for preventing or controlling threats to health get the timely, ongoing, and reliable information they need about the occurrence, antecedents, time course, geographic spread, consequences, and nature of these threats among the populations they serve. “Policy surveillance” is the ongoing, systematic collection, analysis, and dissemination of information about laws and other policies of health importance.

We construct novel measures to assess (i) the extent to which European Union member states are using common standards in recognizing asylum seekers and (ii) the extent to which the responsibilities for asylum applications, acceptances and refugee populations are equally shared among the member states, taking into account population size, gross domestic product (GDP) and GDP expressed in purchasing power parity (GDP-PPP). We track the progression of these measures since the implementation of the Treaty of Amsterdam (1999). These measures (...) display divergent trends and we try to provide an interpretation of the dynamics that are constitutive of these trends. (shrink)

Nowadays, protecting trust in social sciences also means engaging in open community dialogue, which helps to safeguard robustness and improve efficiency of research methods. The combination of open data, open review and open dialogue may sound simple but implementation in the real world will not be straightforward. However, in view of Begley and Ellis’s (2012) statement that, “the scientific process demands the highest standards of quality, ethics and rigour,” they are worth implementing. More importantly, they are feasible to (...) work on and likely will help to restore plausibility to social sciences research. Therefore, I feel it likely that the triplet of open data, open review and open dialogue will gradually emerge to become policy requirements regardless of the research funding source. (shrink)

Starting from the observation that data sharing in general and sharing of reusable behavioral data in particular is still scarce in psychology, we set out to develop a curation standard for behavioral psychological research data rendering data reuse more effective and efficient. Specifically, we propose a standard that is oriented toward the requirements of the psychological research process, thus considering the needs of researchers in their role as data providers and data users. To this (...) end, we suggest that researchers should describe their data on three documentation levels reflecting researchers’ central decisions during the research process. In particular, these levels describe researchers’ decisions on the concrete research design that is most suitable to address the corresponding research question, its operationalization as well as a precise description of the subsequent data collection and analysis process. Accordingly, the first documentation level represents, for instance, researchers’ decision on the concrete hypotheses, inclusion/exclusion criteria and the number of measurement points as well as a conceptual presentation of all substantial variables included in the design. On the second level these substantial variables are presented within an extended codebook allowing for the linkage between the conceptual research design and the actually operationalized variables as presented within the data. Finally, the third level includes all materials, data preparation and analyses scripts as well as a detailed procedure graphic that allows the data user to link the information from all three documentation levels at a single glance. After a comprehensive presentation of the standard, we will offer some arguments for its integration into the psychological research process. (shrink)

This thesis provides an introduction to the physics of the Standard Model and beyond, and to the methods used to analyse Large Hadron Collider (LHC) data. The 'hierarchy problem', astrophysical data and experiments on neutrinos indicate that new physics can be expected at the now accessible TeV scale. This work investigates extensions of the Standard Model with gravitons and gravitinos (in the context of supergravity). The production of these particles in association with jets is studied as one of (...) the most promising avenues for researching new physics at the LHC. Advanced simulation techniques and tools, such as algorithms allowing the computation of Feynman graphs and helicity amplitudes are first developed and then employed. (shrink)

Clinicians sometimes disagree about how much to honor surrogates’ deeply held cultural values or traditions when they differ from those of the host country. Such a controversy arose when parents requested a cultural accommodation to let their infant die by withdrawing life saving care. While both the parents and clinicians claimed to be using the Best Interests Standard to decide what to do, they were at an impasse. This standard is analyzed into three necessary and jointly sufficient conditions and used (...) to resolve the question of how much to accommodate cultural preferences and how to treat this infant. The extreme versions of absolutism and relativism are rejected. Properly understood, the Best Interests Standard can serve as a powerful tool in settling disputes about how to make good decisions for those who cannot decide for themselves. (shrink)

In this amazingly prophetic work, done late in his career, Herbert Spencer offers an approach to ethics that anticipates developments throughout the twentieth century. He moves away from the twin evils of ethical doctrines bequeathed to us by an ancient past that are simply no longer feasible but also avoids modern standards of ethical conduct that are simply impossible to attain. "By association with rules that cannot be obeyed," Spencer writes, "rules that can be obeyed lose their authority." The (...) volume opens with three chapters on conduct: its evolution, good and bad, and ways of judgment. This is followed by a series of chapters that examine ethics from a variety of scientific perspectives: physics, biology, psychology, and sociology. The work then moves on to specific issues of deep human concern: the relativity of pleasures and pain, egoism versus altruism in explaining actions, and trial and compromise in decision-making about ethical concerns. Spencer's work anticipates the movement toward pragmatic, naturalistic, and even positivist approaches to ethics. He emphasizes that a relativist approach while in keeping with the spirit of the industrial age, also poses a variety of problems that admit only of empirical solutions. He understands that his critical stance on absolutism should not blind researchers to the ideals assumed by the ancients that assist people in their everyday living. In short, this is a remarkable work, entirely modern, and yet containing a sharp evaluation of how ethical data serve to enhance ethical conduct. (shrink)

When analyzing complex longitudinal data, especially data from different educational settings, researchers generally focus only on the mean part (i.e., the regression coefficients), ignoring the equally important random part (i.e., the random effect variances) of the model. By using Project English Language and Literacy Acquisition (ELLA) data, we demonstrated the importance of taking the complex data structure into account by carefully specifying the random part of the model, showing that not only can it affect the variance (...) estimates, the standard errors, and the tests of significance of the regression coefficients, it also can offer different perspectives of the data, such as information related to the developmental process. We used xxM (Mehta, 2013), which can flexibly estimate different grade-level variances separately and the potential carryover effect from each grade factor to the later time measures. Implications of the findings and limitations of the study are discussed. (shrink)

This book explores how Cross-cultural research and relationships are unavoidable because of the current veracity of globalization and how all research methodologies and relationships are affected given the necessity of interpretation of data collected and differences in cultural values and philosophies in all areas of human activities.

The practice of research is full of ethical challenges, many of which might be addressed through the teaching of responsible conduct of research . Although such training is increasingly required, there is no clear consensus about either the goals or content of an RCR curriculum. The present study was designed to assess community standards in three domains of research practice: authorship, collaboration, and data management. A survey, developed through advice from content matter experts, focus groups, and interviews, was (...) distributed in November 2010 to U.S. faculty from 50 graduate programs for each of four different disciplines: microbiology, neuroscience, nursing, and psychology. The survey addressed practices and perceived standards, as well as perceptions about teaching and learning. Over 1,300 responses yielded statistically significant differences in responses to nearly all questions. However the magnitude of these differences was typically small, leaving little reason to argue for community consensus on standards. For nearly all questions asked, the clear finding was that there was nothing approaching consensus. These results may be useful not so much to teach what the standards are, but to increase student awareness of the diversity of those standards in reported practice. (shrink)

This paper explores how data serve as evidence for phenomena. In contrast to standard philosophical models which invite us to think of evidential relationships as logical relationships, I argue that evidential relationships in the context of data-to-phenomena reasoning are empirical relationships that depend on holding the right sort of pattern of counterfactual dependence between the data and the conclusions investigators reach on the phenomena themselves.

The aim of the research is to identify the relationship between the performance criteria and the achievement of the objectives of supervision which is represented in the performance of the job at the Islamic University in Gaza Strip. To achieve the objectives of the research, the researchers used the descriptive analytical approach to collect information. The questionnaire consisted of (22) paragraphs distributed to three categories of employees of the Islamic University (senior management, faculty members, their assistants and members of the (...) administrative board). A random sample of 314 employees was selected, 276 responses were retrieved with a return rate of 88.1%. The SPSS program was used to enter, process, and analyze the data. The results of the study showed a positive relationship between the performance criteria and the achievement of the control objectives represented by the job performance in the Islamic University from the point of view of the members (senior management, faculty and their assistants and the administrative board). The researchers also recommended a number of recommendations, including the provision of an appropriate level of control system components today through the continuous updating and development of performance standards and the need to provide the necessary physical and financial resources to continue the development and achievement within the university. Expand the development of technology in the various activities of the university through the construction of a complete and integrated system to support the control systems in the university to suit its size. The researchers also recommended the follow-up, review of the performance standards and work to modify them in line with the mission of the university and the goals that the university seeks to reach. (shrink)

The movements by national governments, funding agencies, universities, and research communities toward “open data” face many difficult challenges. In high-level visions of open data, researchers’ data and metadata practices are expected to be robust and structured. The integration of the internet into scientific institutions amplifies these expectations. When examined critically, however, the data and metadata practices of scholarly researchers often appear incomplete or deficient. The concepts of “accountability” and “transparency” provide insight in understanding these perceived gaps. (...) Researchers’ primary accountabilities are related to meeting the expectations of research competency, not to external standards of data deposition or metadata creation. Likewise, making data open in a transparent way can involve a significant investment of time and resources with no obvious benefits. This paper uses differing notions of accountability and transparency to conceptualize “open data” as the result of ongoing achievements, not one-time acts. (shrink)

Teaching of responsible conduct of research is largely predicated on the assumption that there are accepted standards of conduct that can be taught. However there is little evidence of consensus in the scientific community about such standards, at least for the practices of authorship, collaboration, and data management. To assess whether such differences in standards are based on disciplinary differences, a survey, described previously, addressing standards, practices, and perceptions about teaching and learning was distributed in (...) November 2010 to US faculty from 50 graduate programs for the biomedical disciplines of microbiology, neuroscience, nursing, and psychology. Despite evidence of statistically significant differences across the four disciplines, actual differences were quite small. Stricter measures of effect size indicated practically significant disciplinary differences for fewer than 10 % of the questions. This suggests that the variation in individual standards of practice within each discipline is at least as great as variation due to differences among disciplines. Therefore, the need for discipline-specific training may not be as important as sometimes thought. (shrink)

This paper draws attention to an increasingly common method of using computer simulations to establish evidential standards in physics. By simulating an actual detection procedure on a computer, physicists produce patterns of data (‘signatures’) that are expected to be observed if a sought-after phenomenon is present. Claims to detect the phenomenon are evaluated by comparing such simulated signatures with actual data. Here I provide a justification for this practice by showing how computer simulations establish the reliability of (...) detection procedures. I argue that this use of computer simulation undermines two fundamental tenets of the Bogen–Woodward account of evidential reasoning. Contrary to Bogen and Woodward’s view, computer-simulated signatures rely on ‘downward’ inferences from phenomena to data. Furthermore, these simulations establish the reliability of experimental setups without physically interacting with the apparatus. I illustrate my claims with a study of the recent detection of the superfluid-to-Mott-insulator phase transition in ultracold atomic gases. (shrink)

Following the rediscovery of Mendelian genetics, food supply pressures and the rapid expansion of crop varieties with defined performance characteristics, international systems were set up throughout the 20 C to regulate the trade of seed, the protection of intellectual property and the sale of productive varieties of key agricultural crops. These systems are a highly connected but largely linear set of processes. System changes are slow to be adopted due to the cascade of effects that structural alteration would have globally. (...) Multi-omic technologies and the subsequent proliferation of data types used within modern breeding, offer the possibility to gain deeper insights into the performance characteristics of varieties. Current integration of data, standards and ownership structures limit their applications for wider purposes, both private and public. We explore how data within and between breeding programmes and the varietal approval and monitoring processes could be made FAIR. We examine what role expanded or aligned programmes of data collection and expanded trait evaluation at the point of varietal registration and evaluation, as well as on farm could have in ensuring the best linkage of public and private data to address some of the challenges society faces over the next 30 years with the required, rapid transition to sustainable agricultural systems. (shrink)

Many studies in big data focus on the uses of data available to researchers, leaving without treatment data that is on the servers but of which researchers are unaware. We call this dark data, and in this article, we present and discuss it in the context of high-performance computing facilities. To this end, we provide statistics of a major HPC facility in Europe, the High-Performance Computing Center Stuttgart. We also propose a new position tailor-made for coping (...) with dark data and general data management. We call it the scientific data officer and we distinguish it from other standard positions in HPC facilities such as chief data officers, system administrators, and security officers. In order to understand the role of the SDO in HPC facilities, we discuss two kinds of responsibilities, namely, technical responsibilities and ethical responsibilities. While the former are intended to characterize the position, the latter raise concerns—and proposes solutions—to the control and authority that the SDO would acquire. (shrink)

Nowadays, the quality standards of higher education institutions pay special attention to the performance and evaluation of the students. Then, having a complete academic record of each student, such as number of attempts, average grade and so on, plays a key role. In this context, the existence of missing data, which can happen for different reasons, leads to affect adversely interesting future analysis. Therefore, the use of imputation techniques is presented as a helpful tool to estimate the value (...) of missing data. This work deals with the academic records of engineering students, in which imputation techniques are applied. More specifically, it is assessed and compared to the performance of the multivariate imputation by chained equations methodology, the adaptive assignation algorithm based on multivariate adaptive regression splines and a hybridization based on self-organisation maps with Mahalanobis distances and AAA algorithm. The results show that proposed methods obtain successfully results regardless the number of missing values, in general terms. (shrink)

Law wrangles with setting and applying standards for the practice of medicine in many different arenas. One of the most prominent is medical malpractice litigation in which the trial process examines a physician's performance and measures it against the standard of care. The profession's prevailing custom, with some substantial tolerance for “respectable minority” views, has been the gold standard for scrutinizing physician practice and treatment decisions in the malpractice context. Using the profession's custom as the measure against which a (...) physician's performance is judged defers to the expertise of medicine. Deference to the medical profession is attractive as a tool for reining in law. Reliance on customary practice is criticized, however, for driving physicians to the relative safety of the middle of the herd. Creating such a strong incentive for compliance with customary practice can dampen medical innovation and the diffusion of new clinical knowledge. The safety of the herd can also deprive individual patients of the best care in their particular circumstances.Several current trends are strengthening claims that professional practice patterns are an inappropriate tool for distinguishing between high‐quality and substandard care. In particular, advocacy for evidence‐based medicine aggressively asserts that the traditional way of making medical treatment decisions is largely untethered from scientific method or data, rendering professional judgment, even in the aggregate, suspect. (shrink)

Many studies in big data focus on the uses of data available to researchers, leaving without treatment data that is on the servers but of which researchers are unaware. We call this dark data, and in this article, we present and discuss it in the context of high-performance computing facilities. To this end, we provide statistics of a major HPC facility in Europe, the High-Performance Computing Center Stuttgart. We also propose a new position tailor-made for coping (...) with dark data and general data management. We call it the scientific data officer and we distinguish it from other standard positions in HPC facilities such as chief data officers, system administrators, and security officers. In order to understand the role of the SDO in HPC facilities, we discuss two kinds of responsibilities, namely, technical responsibilities and ethical responsibilities. While the former are intended to characterize the position, the latter raise concerns—and proposes solutions—to the control and authority that the SDO would acquire. (shrink)

This study examines the participation and interaction of relevant individuals in the process of developing an accounting standard for South Korea’s emission trading scheme (ETS). Despite the enormous accounting implications of such schemes, there is a paucity of research on the development and application of ETS accounting. Ulrich Beck’s and Anthony Giddens’s risk society framework is utilised to scrutinise the process of setting accounting standards—from the agenda-setting stage all the way to the final publication of the standard. In this (...) case study, we take an interpretive approach in analysing the rich data collected through face-to-face interviews with prominent standard-setters, accounting experts and representatives of industry and government. Participant observation and relevant documents were also considered. The findings highlight the political nature of accounting standard-setting and identify the risks and responsibilities of the key agents in the process along with the means of sub-political action taken to influence decisions. We reveal that the agents involved in standard-setting attempted to balance their anthropocentric priorities with ecocentric responsibilities and prioritised the production of a standard with minimal impact on economic, reputational, and operational risk. Having authority as a standard-setter, referring frequently to precedents and, perhaps most importantly, engaging actively with the stakeholders throughout the process seem to have contributed to a widely accepted standard, which can serve as a benchmark for future attempts to factor in ETSs. (shrink)

Data exclusivity is a temporary exclusive user right on the clinical data that need to be submitted to the regulatory authorities to prove that a new drug is safe and effective. For the pharmaceutical industry, data exclusivity is an important addition to the patent system, as data exclusivity will de facto delay the market entry of generic drugs until after the exclusive user rights on the clinical data have expired. In order to assess the normative (...) legitimacy of the industry’s demand to include minimum standards for data exclusivity in international agreements, this chapter evaluates the three justifications that have frequently been advanced, depicting data exclusivity as an essential policy tool to promote innovation, a mechanism to prevent the generic industry from ‘free-riding,’ and a legal instrument to protect the industry’s property rights in clinical data. (shrink)

Genetic information is widely thought to pose unique risks of reidentifying individuals. Genetic data reveals a great deal about who we are and, the standard view holds, should consequently be treated differently from other types of data. Contrary to this view, we argue that the dangers of reidentification for genetic and nongenetic data—including health, financial, and consumer information—are more similar than has been recognized. Before different requirements are imposed around sharing genetic information, proponents of the standard view (...) must show that they are in fact necessary. We further argue that the similarities between genetic and nongenetic information have important implications for communicating risks during consent for health care and research. While patients and research participants need to be more aware of pervasive data‐sharing practices, consent forms are the wrong place to provide this education. Instead, health systems should engage with patients throughout patient care to educate them about data‐sharing practices. (shrink)

SummaryNormative data are reported for intelligence, height and head circumference for a sample of 1553 6- to 15-year-olds in Saudi Arabia, and for the correlations between these variables. Intelligence was tested with the Standard Progressive Matrices, on which the Saudi sample obtained a British IQ of 76.2. There were no significant differences in means between boys and girls and differences in variability were inconsistent. The heights of the Saudi sample were generally lower than those of the American norms. The (...) differences in head circumferences between the Saudi children and the American norms were inconsistent. Correlations between IQ and height were weaker than those found in other studies but correlations between IQ and head circumference were positive. (shrink)

First-person data have been both condemned and hailed because of their alleged privacy. Critics argue that science must be based on public evidence: since first-person data are private, they should be banned from science. Apologists reply that first-person data are necessary for understanding the mind: since first-person data are private, scientists must be allowed to use private evidence. I argue that both views rest on a false premise. In psychology and neuroscience, the subjects issuing first-person reports (...) and other sources of first-person data play the epistemic role of a (self-) measuring instrument. Data from measuring instruments are public and can be validated by public methods. Therefore, first-person data are as public as other scientific data: their use in science is legitimate, in accordance with standard scientific methodology. (shrink)

This work tests two conflicting views about double standards: whether they reflect evolved sex differences in behavior or a manipulative morality serving male interests. Two questionnaires on jealous reactions to mild (flirting) and serious (cheating) sexual transgressions were randomly assigned to 172 young women and men. One questionnaire assessed standards for appropriate behavior and perceptions of how young women and men usually react. The second asked people to report how they had reacted or, if naive, how they would (...) react. The questions concerned anger at and blame of partner and rival and the self-oriented responses of loss of self-esteem, feelings of hurt, and fear of losing the partner. As predicted by the idea of manipulative morality, both sexes advanced sets of double standards that serve the interests of their own sex at the expense of the opposite sex. Much of the data contradict the idea of a match between double standards and evolved sex differences. First, subjects who set self-serving double standards did not perceive gender differences in jealous reactions. Second, there were few gender differences in judgments regarding jealous responses. Third, in contrast with the familiar double standard, women were more aggressively reactive to a flirting rival than men. Fourth, self-reports of the strength of aggressive jealous reactions suggest that women’s behavior is stronger than the prescriptions for it. These data suggest that double standards represent a communication strategy which assists men’s control of women. The data on jealous reactions were interpreted in terms of the degree of threat to fitness posed by infidelity in different situations. (shrink)

The aim of the article is to explain the relationship between the ethical evaluation of scientific research involving personal data and the assessment of compliance with data protection law. The article presents the mutual relationship between the protection of personal data and scientific activity from a dogmatic perspective, the legal regulation of the processing of personal data in scientific research, and the so-called research exceptions that apply when data are processed for scientific research. It also (...) covers the importance of meeting the ethical requirements of scientific research in order to profit from the indicated exceptions. Finally, it provides a comparison between the ethical and the legal systems of personal data protection in research (objectives, criteria, authorities, and procedures). (shrink)

Archival data processing consists of cleaning and formatting data between the moment a dataset is deposited and its publication on the archive’s website. In this article, I approach data processing by combining scholarship on invisible labor in knowledge infrastructures with a Marxian framework and show the relevance of considering data processing as factory labor. Using this perspective to analyze ethnographic data collected during a six-month participatory observation at a U.S. data archive, I generate a (...) taxonomy of the forms of alienation that data processing generates, but also the types of resistance that processors develop, across four categories: routine, speed, skill, and meaning. This synthetic approach demonstrates, first, that data processing reproduces typical forms of factory worker’s alienation: processors are asked to work along a strict standardized pipeline, at a fast pace, without acquiring substantive skills or having a meaningful involvement in their work. It reveals, second, how data processors resist the alienating nature of this workflow by developing multiple tactics along the same four categories. Seen through this dual lens, data processors are therefore not only invisible workers, but also factory workers who follow and subvert a workflow organized as an assembly line. I conclude by proposing a four-step framework to better value the social contribution of data workers beyond the archive. (shrink)

In this paper, we discuss several problems with current Big data practices which, we claim, seriously erode the role of informed consent as it pertains to the use of personal information. To illustrate these problems, we consider how the notion of informed consent has been understood and operationalised in the ethical regulation of biomedical research (and medical practices, more broadly) and compare this with current Big data practices. We do so by first discussing three types of problems that (...) can impede informed consent with respect to Big data use. First, we discuss the transparency (or explanation) problem. Second, we discuss the re-repurposed data problem. Third, we discuss the meaningful alternatives problem. In the final section of the paper, we suggest some solutions to these problems. In particular, we propose that the use of personal data for commercial and administrative objectives could be subject to a ‘soft governance’ ethical regulation, akin to the way that all projects involving human participants (e.g., social science projects, human medical data and tissue use) are regulated in Australia through the Human Research Ethics Committees (HRECs). We also consider alternatives to the standard consent forms, and privacy policies, that could make use of some of the latest research focussed on the usability of pictorial legal contracts. (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)

The setting of evidential standards is a core practice of scientific assessment for policy. Persuaded by considerations of inductive risk, philosophers generally agree that the justification of evidential standards must appeal to non-epistemic values but debate whether the balance of non-epistemic reasons favours varying evidential standards versus maintaining fixed high evidential standards in assessment, as both sets of standards promote different and important political virtues of advisory institutions. In this paper, I adjudicate the evidential (...) class='Hi'>standards debate by developing a novel argument from justice, drawing on the IPCC’s assessment of climate impacts as a case study. I argue that in assessments marked by background evidential inequality, maintaining fixed high evidential standards results in an unequal distribution of ‘epistemic power’ among stakeholders, producing a ‘powerful assessment’ for the data-rich (a high rate of findings) and a ‘weak assessment’ for the data-poor (a low rate of findings). Where such inequalities of epistemic power disadvantage those in data-poor regions with respect to fundamental interests, such as basic human rights, we have decisive reasons of justice to vary evidential standards. (shrink)

The Health Level 7 Reference Information Model (HL7 RIM) is lauded by its authors as ‘the foundation of healthcare interoperability’. Yet even after some 10 years of development work, the RIM is still subject to a variety of logical and ontological flaws which have placed severe obstacles in the way of those who are called upon to develop implementations. We offer evidence that these obstacles are insurmountable and that the time has come to abandon an unworkable paradigm.

There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene (...) on semantic information, and misinformation is not a tyoe of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates the important implications of the revised definition for the analysis of the deflationary theories of truth, the standard definition of knowledge and the classic, quantitative theory of semantic information. (shrink)

There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske‐Grice approach: meaningful and well‐formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth‐values do not (...) supervene on semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo‐information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo‐information. As a consequence, SDI is revised to include a necessary truth‐condition. The last section summarises the main results of the paper and indicates some interesting areas of application of the revised definition. (shrink)

n the analytic tradition, the appeal to intuition has been a common philosophical practice that supposedly provides us with epistemic standards. The authoress argues that the high epistemological standards of traditional analytic philosophy cannot be pursued by this method. Perhaps within a naturalistic, reliable frame intuitions can be evoked more coherently. Philosophers can use intuition as scientists do, in hypothesis- construction or data- collection. This is an ironic conclusion: Traditional analytic epistemologists rely on the appeal to intuition, (...) but cannot justify it. Naturalists, on the other hand, are not those who need such a method; yet they can better accommodate it within their view. (shrink)

This edited volume focuses on big data implications for computational social science and humanities from management to usage. The first part of the book covers geographic data, text corpus data, and social media data, and exemplifies their concrete applications in a wide range of fields including anthropology, economics, finance, geography, history, linguistics, political science, psychology, public health, and mass communications. The second part of the book provides a panoramic view of the development of big data (...) in the fields of computational social sciences and humanities. The following questions are addressed: why is there a need for novel data governance for this new type of data?, why is big data important for social scientists?, and how will it revolutionize the way social scientists conduct research? With the advent of the information age and technologies such as Web 2.0, ubiquitous computing, wearable devices, and the Internet of Things, digital society has fundamentally changed what we now know as "data", the very use of this data, and what we now call "knowledge". Big data has become the standard in social sciences, and has made these sciences more computational. Big Data in Computational Social Science and Humanities will appeal to graduate students and researchers working in the many subfields of the social sciences and humanities. (shrink)