This study aims to reveal the Turkish religious music practices of Jawharism, a sect based on Qadiri and Rifai, founded in Bagcilar, Istanbul. The historical process of the establishment of Jawharism was firstly mentioned, and then the musical activities of the "Association for the Promotion and Sustenance of Sufi Music and Culture", which enabled it to spread in a cultural sense, were discussed. As a result of archives, interviews and observations, the relationship of Jawharism with music was determined, the types (...) of music performed in the dhikr and the compositions belonging to the lodge were identified. In addition, through the sound recordings and note archives obtained as a result of the research, the works specific to the lodge were arranged and notated, and it was aimed to introduce the Turkish religious music repertoire to new works. Genres such as salawat, imamet, tasbihât, istighfar, taravih composition, odes and hymns are performed in the lodge, and especially the compositions of salawats and tasbihâts in the maqam of uşşak, rast, hicaz and segah are sung specifically for the lodge. Meşk evenings are also organized and many hymns, suğl, tevşih, nefes, mersiye, etc. are practiced. Composed genres are performed. The problem of this study is, is the relationship between dhikr and music of Jawharism compatible? How is the statues of Jawharism in Turkish religious music?, Qualitative research methods such as source scanning, data collection, sampling, comparison and citing sources were used in our study determined as a method. We can express the importance of this study as the importance of Jawharism's relationship with music, as it used music effectively and trained many musicians and composers. (shrink)

One of the goals of The Patient Protection and Affordable Care Act is the reduction and elimination of health inequities, generally defined as population-level health differences that adversely affect disadvantaged groups. The ACA provides powerful new tools to collect, analyze, and share standardized data on these inequities. Prior to the ACA, disability was marginalized in data collection efforts, limiting our ability to understand and address significant health inequities experienced by millions of Americans. Now, for the first time, we (...) can use these tools to collect valuable new data on the nature and extent of health inequities experienced by people with disabilities across the country. Standardized health data collection is critical to health equity. (shrink)

Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used to train them. While computational techniques are emerging to address aspects of these concerns through communities such as discrimination-aware data mining and fairness, accountability and transparency machine learning, their practical implementation faces real-world challenges. For legal, institutional or commercial reasons, organisations might not hold the data on sensitive attributes such as gender, ethnicity, sexuality or disability needed to diagnose and mitigate emergent (...) indirect discrimination-by-proxy, such as redlining. Such organisations might also lack the knowledge and capacity to identify and manage fairness issues that are emergent properties of complex sociotechnical systems. This paper presents and discusses three potential approaches to deal with such knowledge and information deficits in the context of fairer machine learning. Trusted third parties could selectively store data necessary for performing discrimination discovery and incorporating fairness constraints into model-building in a privacy-preserving manner. Collaborative online platforms would allow diverse organisations to record, share and access contextual and experiential knowledge to promote fairness in machine learning systems. Finally, unsupervised learning and pedagogically interpretable algorithms might allow fairness hypotheses to be built for further selective testing and exploration. Real-world fairness challenges in machine learning are not abstract, constrained optimisation problems, but are institutionally and contextually grounded. Computational fairness tools are useful, but must be researched and developed in and with the messy contexts that will shape their deployment, rather than just for imagined situations. Not doing so risks real, near-term algorithmic harm. (shrink)

IntroductionThis special issue brings together researchers from psychology and linguistics who apply the ethnomethodologically informed analytic technique of conversation analysis (henceforth CA) to examine a range of ethical issues as they emerge in transcribed recordings of interactions collected as part of routine research encounters. The data authors analyse are diverse, including naturalistic audio and video recordings of members’ everyday and professional practices (Mondada 2014), an ethnography of a gynaecology unit in a public hospital in Italy (Fatigante and Orletti 2014), (...) focus group interviews on domestic family life (Alby and Fatigante 2014), and semi-public meetings, recorded as part of an ethnography of ageing, poverty, and social exclusion (Paoletti 2014b). Noting that “ethical issues in research have seldom been the focus of ethnomethodological studies” (Paoletti 2014a: 174; see also Mondada 2014: 182–183), the primary aim of this special issue is to “open a debate on e. (shrink)

Purpose This study advances a reconceptualization of data and information which overcomes normative understandings often contained in data policies at national and international levels. This study aims to propose a conceptual framework that moves beyond subject- and collective-centric normative understandings. Design/methodology/approach To do so, this study discusses the European Union (EU) and China’s approaches to data-driven technologies highlighting their similarities and differences when it comes to the vision underpinning how tech innovation is shaped. Findings Regardless of the (...) different attention to the subject (the EU) and the collective (China), the normative understandings of technology by both actors remain trapped into a positivist approach that overlooks all that is not and cannot be turned into data, thus hindering the elaboration of a more holistic ecological thinking merging humans and technologies. Originality/value Revising the philosophical and political debate on data and data-driven technologies, a third way is elaborated, i.e. federated data as commons. This third way puts the subject as part by default of a collective at the centre of discussion. This framing can serve as the basis for elaborating sociotechnical alternatives when it comes to define and regulate the mash-up of humans and technology. (shrink)

The purpose of this article is twofold: on the one hand, we present the outlines of a history of university collections in Germany. On the other hand, we discuss this history as a case study of the changing attitudes of the sciences towards their material heritage. Based on data from 1094 German university collections, we distinguish three periods that are by no means homogeneous but offer a helpful starting point for a discussion of the entangled institutional and (...) epistemic factors in the history of university collections. In the 19th century, university collections were institutionalized and widely recognized as indispensable in research and teaching. During the 20th century, university collection became increasingly marginalized both on an institutional and theoretical level. Towards the end of the 20th century, the situation of university collections improved partly because of their reconsideration as material heritage. (shrink)

BackgroundRandomized controlled trials (RCTs) are often complex and expensive to perform. Less than one third achieve planned recruitment targets, follow-up can be labor-intensive, and many have limited real-world generalizability. Designs for RCTs conducted using cohorts and routinely collected health data, including registries, electronic health records, and administrative databases, have been proposed to address these challenges and are being rapidly adopted. These designs, however, are relatively recent innovations, and published RCT reports often do not describe important aspects of their methodology (...) in a standardized way. Our objective is to extend the Consolidated Standards of Reporting Trials (CONSORT) statement with a consensus-driven reporting guideline for RCTs using cohorts and routinely collected health data.MethodsThe development of this CONSORT extension will consist of five phases. Phase 1 (completed) consisted of the project launch, including fundraising, the establishment of a research team, and development of a conceptual framework. In phase 2, a systematic review will be performed to identify publications (1) that describe methods or reporting considerations for RCTs conducted using cohorts and routinely collected health data or (2) that are protocols or report results from such RCTs. An initial “long list” of possible modifications to CONSORT checklist items and possible new items for the reporting guideline will be generated based on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) and The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statements. Additional possible modifications and new items will be identified based on the results of the systematic review. Phase 3 will consist of a three-round Delphi exercise with methods and content experts to evaluate the “long list” and generate a “short list” of key items. In phase 4, these items will serve as the basis for an in-person consensus meeting to finalize a core set of items to be included in the reporting guideline and checklist. Phase 5 will involve drafting the checklist and elaboration-explanation documents, and dissemination and implementation of the guideline.DiscussionDevelopment of this CONSORT extension will contribute to more transparent reporting of RCTs conducted using cohorts and routinely collected health data. (shrink)

Living organisms are the ultimate survivalists, having evolved phenotypes with unprecedented adaptability, ingenuity, resourcefulness, and versatility compared to human technology. To harness these properties, functional descriptions and design principles from all sources of biodiversity information must be collated − including the hundreds of thousands of possible survival features manifest in natural history museum collections, which represent 12% of total global biodiversity. This requires a consortium of expert biologists from a range of disciplines to convert the observations, data, and (...) hypotheses into the language of engineering. We hope to unite multidisciplinary biologists and natural history museum scientists to maximize the coverage of observations, descriptions, and hypotheses relating to adaptation and function across biodiversity, to make it technologically useful. This is to be achieved by developments in meta‐ taxonomic classification, phylogenetics, systematics, biological materials research, structure and morphological characterizations, and ecological data gathering from the collections − the aim being to identify and catalogue features essential for good biomimetic design. (shrink)

Ethical issues are part of ordinary practices in conducting research involving the collection of interactional data in a variety of disciplines: sociology, linguistics, anthropology, etc. Established codes of practices define acceptable standards of conduct within the profession. Moreover, in many countries, ethics committees, which titles such as the Institutional Review Board (IRB), Research Ethic Board (REB), Research Ethic Committee (REC), have been established, and gaining authorization from such boards has become part of the ordinary activities in carrying out social (...) sciences research.In relation to ethical matters, there is a growing awareness among researchers of the importance of confronting the actual contingencies and the complexities of ethical dilemmas on the ground. Some authors (Fogel 2007; Guillemin and Gillam 2004) find the literature relating to ethics in social sciences research lacking, in particular, in relation to the discussion of ethical problems emerging during. (shrink)

Two different kinds of collections have been used to anticipate influenza pandemics: viral strains and bird specimens. These collections have been organized in museums and data banks to fill the gaps when specimens were decaying or when viral strains were missing. This article asks how collecting practices changed when such collections integrated specimens from China, considered a reservoir of influenza viruses and bird species, following a recurrent critical trope that Chinese specimens were missing. The article shows (...) that techniques for hunting viruses and birds were used to accumulate information so as to mitigate the global threat of species extinction. It suggests that in sentinel territories, museums transform samples and specimens into signs and images of future catastrophic events. (shrink)

Eating is a fundamental part of human life and is, more than anything, a social activity. A new field, known as Computational Commensality has been created to computationally address various social aspects of food and eating. This paper illustrates a study on remote dining we conducted online in May 2021. To better understand this phenomenon, known as Digital Commensality, we recorded 11 pairs of friends sharing a meal online through a videoconferencing app. In the videos, participants consume a plate of (...) pasta while chatting with a friend or a family member. After the remote dinner, participants were asked to fill in the Digital Commensality questionnaire, a validated questionnaire assessing the effects of remote commensal experiences, and provide their opinions on the shortcomings of currently available technologies. Besides presenting the study, the paper introduces the first Digital Commensality Data-set, containing videos, facial landmarks, quantitative and qualitative responses. After surveying multimodal data-sets and corpora that we could exploit to understand commensal behavior, we comment on the feasibility of using remote meals as a source to build data-sets to investigate commensal behavior. Finally, we explore possible future research directions emerging from our results. (shrink)

The potential to collect brain data more directly, with higher resolution, and in greater amounts has heightened worries about mental and brain privacy. In order to manage the risks to individuals posed by these privacy challenges, some have suggested codifying new privacy rights, including a right to “mental privacy.” In this paper, we consider these arguments and conclude that while neurotechnologies do raise significant privacy concerns, such concerns are—at least for now—no different from those raised by other well-understood (...) class='Hi'>data collection technologies, such as gene sequencing tools and online surveillance. To better understand the privacy stakes of brain data, we suggest the use of a conceptual framework from information ethics, Helen Nissenbaum’s “contextual integrity” theory. To illustrate the importance of context, we examine neurotechnologies and the information flows they produce in three familiar contexts—healthcare and medical research, criminal justice, and consumer marketing. We argue that by emphasizing what is distinct about brain privacy issues, rather than what they share with other data privacy concerns, risks weakening broader efforts to enact more robust privacy law and policy. (shrink)

Since its onset, scholars have characterized social media as a valuable source for data collection since it presents several benefits (e.g. exploring research questions with hard-to-reach populations). Nonetheless, methods of online data collection are riddled with ethical and methodological challenges that researchers must consider if they want to adopt good practices when collecting and analyzing online data. Drawing from our primary research project, where we collected passive online data on Reddit, we explore and detail the steps (...) that researchers must consider before collecting online data: (1) planning online data collection; (2) ethical considerations; and (3) data collection. We also discuss two atypical questions that researchers should also consider: (1) how to handle deleted user-generated content; and (2) how to quote user-generated content. Moving on from the dichotomous discussion between what is public and private data, we present recommendations for good practices when collecting and analyzing qualitative online data. (shrink)

Using speech act theory from the Philosophy of Language, this paper attempts to develop an ethical framework for the phenomenon of speech processing. We use the concepts of the illocutionary force and the illocutionary content of a speech act to explain the ethics of speech processing. By emphasizing the different stages involved in speech processing, we explore the distinct ethical issues that arise in relation to each stage. Input, processing, and output are the different ethically relevant stages under which a (...) spoken item or a speech navigates within the range of speech-processing modules. Employing the illocutionary force-content distinction, we specify and characterize the input-related ethical issues, the output-related ethical issues, and the processing-related ethical issues involved in speech processing. Together with illocutionary force-content distinction, we employ the data-information distinction to characterize the stage-wise ethical issues in the phenomenon of speech processing as the ethics of collecting (speech) data, the ethics of contextualizing (speech) data/information, and the ethics of releasing the con-textualized information (processed speech). Immediate ethical issues that arise from the range of speech processing modules are distinguished from distant ethical issues. We also indicate the nature of ethical issues that arise from Speaker Independent speech technologies. (shrink)

In this article, interviewing from a descriptive, phenomenological, human scientific perspective is examined. Methodological issues are raised in relation to evaluative criteria as well as reflective matters that concern the phenomenological researcher. The data collection issues covered are 1) the selection of participants, 2) the number of participants in a study, 3) the interviewer and the questions, and 4) data collection procedures. Certain conclusions were drawn indicating that phenomenological research methods cannot be evaluated on the basis of an (...) empiricist theory of science, but must be critiqued from within a phenomenological theory of science. Some reflective matters, experienced by the phenomenological researcher, are also elaborated upon. (shrink)

In early 2020, in-person data collection dramatically slowed or was completely halted across the world as many labs were forced to close due to the COVID-19 pandemic. Developmental researchers who assess looking time were forced to re-think their methods of data collection. While a variety of remote or online platforms are available for gathering behavioral data outside of the typical lab setting, few are specifically designed for collecting and processing looking time data in infants and young (...) children. To address these challenges, our lab developed several novel approaches for continuing data collection and coding for a remotely administered audiovisual looking time protocol. First, we detail a comprehensive approach for successfully administering the Multisensory Attention Assessment Protocol, developed by our lab to assess multisensory attention skills. The MAAP is administered from a distance by using Zoom, Gorilla Experiment Builder, an internet connection, and a home computer. This new data collection approach has the advantage that participants can be tested in their homes. We discuss challenges and successes in implementing our approach for remote testing and data collection during an ongoing longitudinal project. Second, we detail an approach for estimating gaze direction and duration collected remotely from webcam recordings using a post processing toolkit and demonstrate its effectiveness and precision. However, because OpenFace derives gaze estimates without translating them to an external frame of reference, we developed a machine learning approach to overcome this limitation. Thus, third, we trained a ML algorithm [] to classify gaze estimates from OpenFace with respect to areas of interest on the participant's screen. We then demonstrate reliability between this approach and traditional coding approaches. The combination of OpenFace and ML will provide a method to automate the coding of looking time for data collected remotely. Finally, we outline a series of best practices for developmental researchers conducting remote data collection for looking time studies. (shrink)

Due to advancements in technology such as data science and artificial intelligence, healthcare research has gained momentum and is generating new findings and predictions on abnormalities leading to the diagnosis of diseases or disorders in human beings. On one hand, the extensive application of data science to healthcare research is progressing faster, while on the other hand, the ethical concerns and adjoining risks and legal hurdles those data scientists may face in the future slow down the progression (...) of healthcare research. Simply put, the application of data science to ethically guided healthcare research appears to be a dream come true. Hence, in this paper, we discuss the current practices, challenges, and limitations of the data collection process during medical image analysis (MIA) conducted as part of healthcare research and propose an ethical data collection framework to guide data scientists to address the possible ethical concerns before commencing data analytics over a medical dataset. (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)

Governments around the world collect huge amounts of personal data from their citizens for counterterrorist purposes. While mining this data has arguably increased the security of populations, the practices through which these data are currently collected in many countries have been criticised for violating individuals’ rights to privacy. Yet it is not clear what a permissible data collection regime would look like and thus also how we could reform existing regimes to make them morally acceptable. This (...) article explores a number of ways in which we might justify a data collection regime to those affected in spite of the setbacks to their privacy. In contrast to existing justifications, I argue that individuals can be asked to surrender their personal data as a requirement of reciprocity in a cooperative system in which they gain security from others doing likewise. Relying on this justification, though, has significant implications for how we should reform existing data collection regimes. In particular, more stringent limits will need to be placed on the forms which these regimes can legitimately take. (shrink)

The behavioral sciences have flourished by studying how traditional and/or rational behavior has been governed throughout most of human history by relatively well-informed individual and social learning. In the online age, however, social phenomena can occur with unprecedented scale and unpredictability, and individuals have access to social connections never before possible. Similarly, behavioral scientists now have access to “big data” sets – those from Twitter and Facebook, for example – that did not exist a few years ago. Studies of (...) human dynamics based on these data sets are novel and exciting but, if not placed in context, can foster the misconception that mass-scale online behavior is all we need to understand, for example, how humans make decisions. To overcome that misconception, we draw on the field of discrete-choice theory to create a multiscale comparative “map” that, like a principal-components representation, captures the essence of decision making along two axes: aneast–westdimension that represents the degree to which an agent makes a decision independently versus one that is socially influenced, and anorth–south dimensionthat represents the degree to which there is transparency in the payoffs and risks associated with the decisions agents make. We divide the map into quadrants, each of which features a signature behavioral pattern. When taken together, the map and its signatures provide an easily understood empirical framework for evaluating how modern collective behavior may be changing in the digital age, including whether behavior is becoming more individualistic, as people seek out exactly what they want, or more social, as people become more inextricably linked, even “herdlike,” in their decision making. We believe the map will lead to many new testable hypotheses concerning human behavior as well as to similar applications throughout the social sciences. (shrink)

Collecting and deploying poverty-related data is an important starting point for leveraging data regarding social determinants of health in precision medicine. However, we must rethink how we collect and deploy such data. Current modes of collection yield imprecise data that is unsuited for research. Better data can be collected by cross-referencing other sources such as employers and public benefit programs, and by incentivizing and encouraging patients and providers to provide more accurate information. Data thus (...) collected can be used to provide appropriate individual-level clinical and non-clinical care, and to systematically determine what share of social resources healthcare should consume. (shrink)

This paper presents social data and knowledge collective intelligence platform for TRaining Ethical AI Models (STREAM) to address the challenge of aligning AI models with human moral values, and to provide ethics datasets and knowledge bases to help promote AI models “follow good advice as naturally as a stream follows its course”. By creating a comprehensive and representative platform that accurately mirrors the moral judgments of diverse groups including humans and AIs, we hope to effectively portray cultural and group (...) variations, and capture the dynamic evolution of moral judgments over time, which in turn will facilitate the Establishment, Evaluation, Embedding, Embodiment, Ensemble, and Evolvement (6Es) of the moral capabilities of AI models. Currently, STREAM has already furnished a comprehensive collection of ethical scenarios, and amassed substantial moral judgment data annotated by volunteers and various popular Large Language Models, collectively portraying the moral preferences and performances of both humans and AIs across a range of moral contexts. This paper will outline the current structure and construction of STREAM, explore its potential applications, and discuss its future prospects. (shrink)

The use of Internet to aid research practice has become more popular in the recent years. In fact, some believe that Internet surveying and electronic data collection may revolutionize many disciplines by allowing for easier data collection, larger samples, and therefore more representative data. However, others are skeptical of its usability as well as its practical value. The paper highlights both positive and negative outcomes experienced in a number of e-research projects, focusing on several common mistakes and (...) difficulties experienced by the authors. The discussion focuses on ethics and review board issues, recruitment and sampling techniques, technological issues and errors, and data collection, cleaning, and analysis. (shrink)

The aim of this article is to assess the impact of Big Data technologies for insurance ratemaking, with a special focus on motor products.The first part shows how statistics and insurance mechanisms adopted the same aggregate viewpoint. It made visible regularities that were invisible at the individual level, further supporting the classificatory approach of insurance and the assumption that all members of a class are identical risks. The second part focuses on the reversal of perspective currently occurring in (...) class='Hi'>data analysis with predictive analytics, and how this conceptually contradicts the collective basis of insurance. The tremendous volume of data and the personalization promise through accurate individual prediction indeed deeply shakes the homogeneity hypothesis behind pooling. The third part attempts to assess the extent of this shift in motor insurance. Onboard devices that collect continuous driving behavioural data could import this new paradigm into these products. An examination of the current state of research on models with telematics data shows however that the epistemological leap, for now, has not happened. (shrink)

Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics has repeatedly been criticized for not revealing the underlying raw data distribution. Remarkably, however, systematic and easy-to-use solutions for raw data visualization using the most commonly reported statistical software package for data analysis, IBM SPSS Statistics, are missing. Here, a comprehensive collection of more than 100 SPSS syntax files and (...) an SPSS dataset template is presented and made freely available that allow the creation of transparent graphs for one-sample designs, for one- and two-factorial between-subject designs, for selected one- and two-factorial within-subject designs as well as for selected two-factorial mixed designs and, with some creativity, even beyond. Depending on graph type, raw data can be displayed along with standard measures of central tendency and dispersion. The free-to-use syntax can also be modified to match with individual needs. A variety of example applications of syntax are illustrated in a tutorial-like fashion along with fictitious datasets accompanying this contribution. The syntax collection is hoped to provide researchers, students, teachers, and others working with SPSS a valuable tool to move towards more transparency in data visualization. (shrink)

Social service organizations have long used data in their efforts to support people in need for the purposes of advocacy, tracking, and intervention. Increasingly, such organizations are joining forces to provide wrap-around services to clients in order to “move the needle” on intractable social problems. Groups using these strategies, called Collective Impact, develop shared metrics to guide their work, sharing data, finances, infrastructure, and services. A major emphasis of these efforts is on tracking clients and measuring impacts. This (...) study explores a particular type of Collective Impact strategy called Promise Neighborhoods. Based on a federal grant program, these initiatives attempt to close the achievement gap in particular geographic communities. Through an analysis of publicly available documents and information, the study analyzes the ways these strategies enact a collective intelligence for the common good. The analysis focuses specifically on issues surrounding data collection and use, youth agency, leadership and governance, and funding streams. Together, these foci develop a story of an increasingly used “intelligence” with a limited sense of “collective” and a narrow vision of a “common good.” Using this as a platform, the paper explores alternatives that might develop more robust practices around these concepts. (shrink)

Online data collection methods are expanding the ease and access of developmental research for researchers and participants alike. While its popularity among developmental scientists has soared during the COVID-19 pandemic, its potential goes beyond just a means for safe, socially distanced data collection. In particular, advances in video conferencing software has enabled researchers to engage in face-to-face interactions with participants from nearly any location at any time. Due to the novelty of these methods, however, many researchers still remain (...) uncertain about the differences in available approaches as well as the validity of online methods more broadly. In this article, we aim to address both issues with a focus on moderated data collected using video-conferencing software. First, we review existing approaches for designing and executing moderated online studies with young children. We also present concrete examples of studies that implemented choice and verbal measures and looking time across both in-person and online moderated data collection methods. Direct comparison of the two methods within each study as well as a meta-analysis of all studies suggest that the results from the two methods are comparable, providing empirical support for the validity of moderated online data collection. Finally, we discuss current limitations of online data collection and possible solutions, as well as its potential to increase the accessibility, diversity, and replicability of developmental science. (shrink)

Reactivity in qualitative data collection occurs when a researcher generates data about a situation with reactivity, that is, a situation in which the ongoing research affects the research participants such that they, say, diverge from their routines when the researcher is present, or tell the researcher what they think she wants to hear. In qualitative research, there are two basic approaches to reactivity. The traditional position maintains that data should ideally be collected in situations without any reactivity. (...) In other words, good data are reactivity free. By contrast, the more recent view holds that data from situations with reactivity are fine as long as the researcher is aware of the occurring reactivity so that she can take it into account when interpreting her data. In this fashion, good data are reactivity transparent. In this paper, I first spell out and defend the more recent approach to reactivity. I argue that qualitative data are reactivity transparent when conjoined with true reactivity assumptions and that, thus supplemented, data are informative about social life independently of its being studied. Next, I examine various issues raised by the requirement to put forth true reactivity assumptions. Lastly, I use my discussion of reactivity transparency as a basis for providing a framework for thinking about good qualitative data. (shrink)

Digital tools may help to study socioeconomic aspects of agricultural development that are difficult to measure such as the effects of new policies and technologies on the intra-household allocation of time. As farm technologies target different crops and tasks, they can affect the time-use of men, women, boys, and girls differently. Development strategies that overlook such effects can have negative consequences for vulnerable household members. In this paper, the time-use patterns associated with different levels of agricultural mechanization during land preparation (...) in smallholder farming households in Zambia were investigated. A novel data collection method was used: a pictorial smartphone application that allows real-time recording of time-use, which eliminates recall bias. Existing studies analyzing the intra-household allocation of resources often focus on adult males and females. This study paid particular attention to boys and girls as well as adults. The study addressed seasonal variations. Compositional data analysis was used to account for the co-dependence and sum constraint of time-use data. The study suggests a strong gender differentiation for land preparation activities among mechanized households; for households using manual labor, such differentiation was not found. There is some evidence that the surplus time associated with mechanization is used for off-farm and domestic work. The study cannot confirm concerns about negative second-round effects: mechanized land preparation is not associated with a higher workload for women and children during weeding and harvesting/processing. The study provides a proof-of-concept that smartphone applications can be used to collect socioeconomic data that are difficult to measure but of high relevance. (shrink)

In this article, I offer a partial analysis of the role of values in qualitative data collection in social research. The partial analysis shows that nonepistemic values have both required and permissible roles to play during this phase of research. By appeal to the analysis, I reject the ideal of value-free science as applied to qualitative data collection, and I demonstrate why two alternative ideals should likewise be dismissed as standards for values in qualitative data collection. Also, (...) I briefly discuss the extent to which the partial analysis carries over to quantitative data collection in social research. (shrink)

This article introduces an important concept: Transparency by way of Humanistic Intelligence as a human right, and in particular, Big/little Data and Sur/sous Veillance, where “Little Data” is to sousveillance as “Big Data” is to surveillance. Veillance is a core concept not just in human–human interaction but also in terms of Human–Computer Interaction. In this sense, veillance is the core of Human-in-the-loop Intelligence, leading us to the concept of “Sousveillant Systems” which are forms of Human–Computer Interaction in (...) which internal computational states are made visible to end users, allowing users to “jump” into the computational feedback loop whenever or wherever they want. An important special case of Sousveillant Systems is that of scientific exploration: not only is data considered, but also due consideration must be given to how data is captured, understood, explored, and discovered, and in particular, to the use of scientific instruments to collect data and to make important new discoveries, and learn about the world. Science is a domain where bottom-up transparency is of the utmost importance, and scientists have the right and responsibility to be able to understand the instruments that they use to make their discoveries. Such instruments must be sousveillant systems! (shrink)

This article discusses the benefits and limitations of collecting electronic data for large-scale thematic content analysis. We will discuss a number of methodological and technical issues. The first one is the construction of a list of relevant keywords that serves as the primary data collecting device. This is not only a technical necessity, but also secures a theoretically and empirically valid collection of data. The second concern is the quality of electronic archive information. Finally, source-specific data (...) characteristics and coding difficulties are dealt with. In conclusion, seven guidelines for electronic data collecting are proposed. (shrink)

This essay details the resurgence of wellness program as employed by large corporations with the aim of reducing healthcare costs. The essay narrows in on a discussion of how Big Data collection practices are being utilized in wellness programs and the potential negative impact on the worker in regards to privacy and employment discrimination. The essay offers an ethical framework to be adopted by wellness program vendors in order to conduct wellness programs that would achieve cost-saving goals without undue (...) burdens on the worker. The essay also offers some innovative approaches to wellness that may well better serve the goals of healthcare cost reduction. (shrink)

ArgumentData collections are a hallmark of nineteenth-century administrative knowledge making, and they were by no means confined to Europe. All colonial empires transferred and translated these techniques of serialised and quantified information gathering to their dominions overseas. The colonial situation affected the encounters underlying vital statistics, enquête methods and land surveying. In this paper, two of those data collections will be investigated—a survey on land and a survey on indigenous law, both conducted around 1910 on the Micronesian (...) island of Pohnpei, which had fallen under German colonial influence a decade earlier. Strikingly, there are no enumerators or envoys of the state visiting the doorsteps of Pohnpei. To facilitate the data collection on homesteads, the whole population of the island was called upon to measure their respective plots of land themselves, without resorting to certified land surveyors. The preserved cadastral lists and spreadsheets testify to a rather peculiar contact between the colonizing administration and the colonized peoples. I argue that the production of data made encounters necessary, which are best observed though a methodological focus on data practices. I argue, furthermore, that the Pohnpeians were prompted during the surveys to define their homestead in new terms. This did not only entail new two-dimensional plots but also a new regime of private property. The change in the legal concept can be seen as a continuation of colonial violence by other means, given that it happened in the aftermath of the defeated Pohnpei Rebellion. The argument of the paper is, therefore, that data collection can have formative effects on society, and that measurement and quantified information are often, as Witold Kula argued, a scene of conflict. At its core, the installation of these metric regimes signified a change in patterns of justification, resource management and the unwritten constitution of the Pacific island. (shrink)

In this contribution, we will discuss the opportunities and challenges arising from memory institutions' need to redefine their archival strategies for contemporary collecting in a world of big data. We will reflect on this topic by critically examining the case study of the UK Web Archive, which is made up of the six UK Legal Deposit Libraries: the British Library, National Library of Scotland, National Library of Wales, Bodleian Libraries Oxford, Cambridge University Library and Trinity College Dublin. The UK (...) Web Archive aims to archive, preserve and give access to the UK web space. This is achieved through an annual domain crawl, first undertaken in 2013, in addition to more frequent crawls of key websites and specially curated collections which date back as far as 2005. These collections reflect important aspects of British culture and events that shape society. This commentary will explore a number of questions including: what heritage is captured and what heritage is instead neglected by the UK Web archive? What heritage is created in the form of new data and what are its properties? What are the ethical issues that memory institutions face when developing these web archiving practices? What transformations are required to overcome such challenges and what institutional futures can we envisage? (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)

Socially responsible publishers, such as the BMJ Publishing Group, have demonstrated a commitment to health equity and working towards rectifying the structural racism that exists both in healthcare and in medical publishing.1 The commitment of academic publishers to collecting information relevant to promoting equity and diversity is important and commendable where it leads to that result.2 However, collecting sensitive demographic data is not a morally neutral activity. Rather, it carries with it both known and potential risks. Among these are (...) issues around privacy or data misuse, as well as more basic concerns about how, when or why people should be categorised in certain ways and/or prompted to conceive of themselves or their identities in certain terms.3 If such data are to be collected, therefore, their effectiveness in achieving the stated ends must have a sufficiently compelling evidence base so as to justify the various risks involved. And where possible, these risks must also be identified and minimised. As Varcoe et al 4 argue, > While most leaders and healthcare workers and some patients [in their study] envisioned potential benefits associated with having ethnicity data, these benefits were seen as largely contingent upon action being taken to [actually] ameliorate inequities. Overwhelmingly, however, leaders from ethno-cultural communities and patients of diverse identities anticipated potential harm arising both from having ethnicity data and the process of collection. The analysis illustrates that in today’s sociopolitical context, collecting ethnicity data in clinical contexts may engender considerable harm, particularly for racialized, vulnerable patients. (p1569) Varcoe et al refer to ‘ethnicity’ data, which as they note is an ambiguous concept, potentially encompassing such diverse notions as ancestry, language, religion or culture. It is also a term that is in some contexts—for example, the USA—often used interchangeably with a different, more highly charged term: ‘race’. Data …. (shrink)

The making of music has been sufficiently deep and widespread diachronically and geographically to suggest a genetic imperative. C.G. Jung's 'Collective Unconscious' and the accompanying archetypes suggest that music is a psychic necessity because it is part of the brain structure. Therefore, the present view of aesthetics may need drastic revision, particularly on views of music as pleasure, ideas of disinterest, differences between so-called high and low art, cultural identity, cultural conditioning, and art-for-art's sake.All cultures, past and present, show evidence (...) of music making. Music qua music has been a part of human expression for at least some forty-thousand years and it could well be speculated that the making of music accompanied the arrival of the first human beings. As Curt Sachs states, "However far back we tracemankind, we fail to see the springing-up of music. Even the most primitive tribes are musically beyond the first attempts".Why do humans continuahy create music and include it as an integral part of culture? What is music's driving force? Why do cultures endow music with extraordinary powers? Why do human beings, individuahy and as societies, exercise preferences for specific works and genres of music? In probing these questions, I chose one aspect of Jungian psychology, that of the Collective Unconscious with its accompanying archetypes, as the basis upon which to speculate a world aesthetics of music. Once we dispense with the mechanistic and designer idea of human origins, we have only the investigations of the human psyche to mine for data that could explain the myriad forms of artistic activity found the world over. An examination of human beings, I believe, must lead one ultimately to the study of human behavior and motivations, in short, to the psychology of human ethos. This study wih take the following course: first, a discussion of consciousness and the Collective Unconscious, plus a discussion of archetypes; then, a description of musical archetypal substance; and finally, what I beheve is implied to form a world aesthetics of music.By comparison to Jung, Freud gives us little in the way of understanding artistic substance because for him, all artistic subject matter stems purely from the personal experiences of the artist. In comparing Freud and Jung, Stephen Larsen states that "Where Freud was deterministic, Jung was teleological; where Freud was historical, Jung was mythological". Jung drew on a much wider cross-cultural experiential and intellectual base than Freud. His interests in so-cahed primitive peoples led him to Tunis, the Saharan Desert, sub-Saharan Africa, and New Mexico in the United States to visit the Pueblo Indians; visits to India and Ceylon and studies of Chinese culture all contributed to his vast knowledge of human experience. Jung constructed the cohective unconscious as a major part of the psyche with the deepest sense of tradition and myth from around the world. He was criticized because of his interests in alchemy, astrology, divination, telepathy and clairvoyance, yoga, spiritualism, mediums and seances, fortunetelling, flying saucers, religious symbolism, visions, and dreams. But he approached these subjects as a scientist, investigating the human psyche and what these subjects revealed about mental process, particularly what might be learned about the collective unconsciousness. Jung's ideation, in my view, is sufficiently comprehensive to support the probe of a world aesthetics of music. (shrink)

ArgumentCollecting data about people with mental disorders living outside of asylums became a heightened concern from the early nineteenth century onwards. In Germany, so-called “insanity counts” targeted the number and sometimes the type the mentally ill who were living unattended and untreated by professional care throughout the country. An eagerly expressed assumption that the “true” extent of the gathered numbers must be much higher than the surveys could reveal came hand in glove with the emerging task of “managing” insanity (...) and its potential dangers in a modern society. The doorstep of the family home became a crucial site in psychiatrists’ and enumerators’ efforts to register the most sensitive of personal data. This article traces the ever more diligent methods that were employed to obtain the desired information, as well as the hidden agenda of the postulate of missing data itself. It also addresses the profound impact that the presumption of having only incomplete data has had on the practice of counting and surveying, as well as on the understanding of the need for professional monitoring of mental illness. (shrink)

Data-sharing is a desired default in the field of public health and a source of much ethical deliberation. Sharing data potentially contributes the largest, most efficient source of scientific data, but is fraught with contextual challenges which make stakeholders, particularly those in under-resourced contexts hesitant or slow to share. Relatively little empirical research has engaged stakeholders in discussing the issue. This study sought to explore relevant experiences, contextual, and subjective explanations around the topic to provide a rich (...) and detailed presentation of what it means to different stakeholders and contexts to share data and how that can guide practice and ethical guidance. A qualitative design involving interviews was undertaken with professionals working in public health institutions endowed with data, ethics committees, and advisory agencies which help shape health research in Africa. A descriptive form of thematic analysis was used to summarize results into six key themes: The role of HDSSs in research using public health data and data-sharing; Ownership and funding are critical factors influencing data-sharing; Other factors discourage data-sharing; Promoting and sustaining data-sharing; Ethical guidance structures; and Establishing effective guidance. The themes reveal factors regarding the willingness or not to share and an intricate ethical system that current discourse could reflect. Many of the concerns resonate with the literature, but a whole other gamut of people and process issues; commitments, investments, careers, and the right ethical guidance are needed to realize a sustainable goal of reaching ‘share’ as a default. (shrink)

Life on earth is bound together by a common heritage, centered around a molecule that is present in almost every living cell of every living creature. Deoxyribonucleic acid (DNA), composed of four base pairs, the nucleic acids thymine, adenine, cytosine, and guanine, encodes the data that directs, in conjunction with the environment, the development and metabolism of all nondependent living creatures. Except for some viruses that rely only on ribonucleic acid (RNA), all living things are built by the interaction (...) of DNA and RNA within cells and their environments. There is no worldwide consensus yet as to whether portions of the human genome should be granted intellectual property protection, as indeed they are in the United States and a number of other nations. DNA posed numerous challenges to the legal framework for patent protection and may suggest developing an entirely new social and legal category recognizing its uniqueness. (shrink)

An extensive body of research details the lack of discussion and collaboration occurring in K12 classrooms in the United States. This study seeks to examine this issue by exploring the associations preservice social studies teachers make between the underlying principles of democratic education and the use of discussion in the social studies classroom. The present qualitative multi-case study uses a collection of field-based data and university coursework to examine how six preservice social studies teachers at a large southeastern university (...) conceptualize and value discussion as a pedagogical approach. Findings suggest that preservice social studies teachers do see value in the use of discussion and associate it with broad themes of democratic education. However, because their understandings of democratic education are often vague and unclear, the associations being made often do not reflect the work being conducted within academia in regards to social justice. (shrink)

All scientific activity involves some method of observation and some method of recording what is observed. These activities can be carried out in ways that involve little interaction between subject and object, as is the case when a telescope observes a far-away star. At the other end of the scale are experiments in modern high energy physics in which there is little distinction between the observer and the observed, and the process of observation materially affects the data that are (...) recorded. In this regard, research on human phenomena resembles modern physics more than it does classical astronomy.Research on human phenomena, however, differs from modern physics in the way in which it affects that which is observed. Both the procedures and the findings of research on human phenomena alter the modes of thinking and the self-awareness of the objects of study. (shrink)

All scientific activity involves some method of observation and some method of recording what is observed. These activities can be carried out in ways that involve little interaction between subject and object, as is the case when a telescope observes a far-away star. At the other end of the scale are experiments in modern high energy physics in which there is little distinction between the observer and the observed, and the process of observation materially affects the data that are (...) recorded. In this regard, research on human phenomena resembles modern physics more than it does classical astronomy.Research on human phenomena, however, differs from modern physics in the way in which it affects that which is observed. Both the procedures and the findings of research on human phenomena alter the modes of thinking and the self-awareness of the objects of study. (shrink)

Health research increasingly relies on organized collections of health data and biological samples. There are many types of sample and data collections that are used for health research, though these are collected for many purposes, not all of which are health-related. These collections exist under different jurisdictional and regulatory arrangements and include: 1) Population biobanks, cohort studies, and genome databases 2) Clinical and public health data 3) Direct-to-consumer genetic testing 4) Social media 5) Fitness (...) trackers, health apps, and biometric data sensors Population biobanks, cohort studies, and genome databases Clinical and public health data Direct-to-consumer genetic testing Social media Fitness trackers, health apps, and biometric data sensors Ethical, legal, and social challenges of such collections are well recognized, but there has been limited attention to the broader societal implications of the existence of these collections. Although health research conducted using these collections is broadly recognized as beneficent, secondary uses of these data and samples may be controversial. We examine both documented and hypothetical scenarios of secondary uses of health data and samples. In particular, we focus on the use of health data for purposes of: Forensic investigations Civil lawsuits Identification of victims of mass casualty events Denial of entry for border security and immigration Making health resource rationing decisions Facilitating human rights abuses in autocratic regimes Forensic investigations Civil lawsuits Identification of victims of mass casualty events Denial of entry for border security and immigration Making health resource rationing decisions Facilitating human rights abuses in autocratic regimes Current safeguards relating to the use of health data and samples include research ethics oversight and privacy laws. These safeguards have a strong focus on informed consent and anonymization, which are aimed at the protection of the individual research subject. They are not intended to address broader societal implications of health data and sample collections. As such, existing arrangements are insufficient to protect against subversion of health databases for non-sanctioned secondary uses, or to provide guidance for reasonable but controversial secondary uses. We are concerned that existing debate in the scholarly literature and beyond has not sufficiently recognized the secondary data uses we outline in this paper. Our main purpose, therefore, is to raise awareness of the potential for unforeseen and unintended consequences, in particular negative consequences, of the increased availability and development of health data collections for research, by providing a comprehensive review of documented and hypothetical non-health research uses of such data. (shrink)

Future mobility planning to cope with ongoing environmental challenges such as air pollution has to be anchored in the work of every public authority worldwide. One recent trend that could support public authorities to meet the European Union’s sustainability targets is the creation and sharing of transport and mobility “big” data between public authorities via tools such as crowdsourcing. While the benefits of the use of big data to increase public authorities’ efficiency and effectivity and their citizens’ lives (...) is well understood, examples from the public sector that highlight public authorities’ engagement in such sharing activities is still missing. To date relevant literature has highlighted issues around the capacity of public authorities that hinder shared activities. In this paper we want to raise distrust as a key reason for lack of engagement. Based on comprehensive data collected over the period of 4 years via several workshops and semi-structured interviews with seven public authorities in Europe, we are able to demonstrate that a major obstacle for not providing and sharing data via crowdsourcing for mutual benefit lies primarily in the hands of the public authority’s servants of the middle and high-level management. Our results show firstly, that distrust may emerge toward different referents such as the community, particular individuals, or the technology itself and thus, managerial implications have to be very specific to overcome distrust. Secondly, we show how distrust may spread from one referent to another through negative reciprocity and which, if unchecked may lead to an all-encompassing state that affects the whole sharing economy framework and inhibits potential benefits. (shrink)

This commentary reflects on recent instances of anti-Asian violence and state responses to redress violence through data-driven strategies. Data collection often presents itself as an appealing strategy, due to impacted communities’ desires for evidence and metrics to substantiate political claims. Yet, data collection can bolster the carceral state. This commentary takes an antagonistic approach to policing, including the ongoing creation of data infrastructures by—and for—law enforcement through hate crimes legislation. We critically discuss the challenges and possibilities (...) in building towards anti-carceral responses amidst ongoing racial violence and crisis. (shrink)

Investigating the influence of perception on the control of visually guided action typically involves controlled experimentation within the laboratory setting. When appropriate, however, behavioral research of this nature may benefit from the use of methods that allow for remote data collection outside of the lab. This study tested the feasibility of using remote data collection methods to explore the influence of perceived target size on visually guided cursor movements using the Ebbinghaus illusion. Participants completed the experiment remotely, using (...) the trackpad of their personal laptop computers. The task required participants to click on a single circular target presented at either the left or right side of their screen as quickly and accurately as possible, or to emphasize speed or accuracy. On each trial the target was either surrounded by small or large context circles, or no context circles. Participants’ judgments of the targets’ perceived size were influenced by the illusion, however, the illusion failed to produce differences in click-point accuracy or movement time. Interestingly, the illusion appeared to affect participants’ movement of the cursor toward the target; more directional changes were made when clicking the Perceived Large version of the illusion compared to the Perceived Small version. These results suggest the planning of the cursor movement may have been influenced by the illusion, while later stages of the movement were not, and cursor movements directed toward targets perceived as smaller required less correction compared to targets perceived as larger. (shrink)

Qualitative fieldwork research on sensitive topics sometimes requires that interviewees be granted confidentiality and anonymity. When qualitative researchers later publish their findings, they must ensure that any statements obtained during fieldwork interviews cannot be traced back to the interviewees. Given these protections to interviewees, the integrity of the published findings cannot usually be verified or replicated by third parties, and the scholarly community must trust the word of qualitative researchers when they publish their results. This trust is fundamentally abused, however, (...) when researchers publish articles reporting qualitative fieldwork data that they never collected. Using only publicly available information, I argue that a 2017 article in an Elsevier foreign policy and international relations journal presents anonymised fieldwork interviews that could not have occurred as described. As an exercise in post-publication peer review (PPPR), this paper examines the evidence that calls into question the reliability of the putative fieldwork quotations. I show further that the 2017 article is not a unique case. The anonymity and confidentiality protections common in some areas of research create an ethical problem: the protections necessary for obtaining research data can be used as a cover to hide substandard research practices as well as research misconduct. (shrink)