Measuring the health patterns of the ‘mixed/multiple’ ethnic group in Britain: data quality problems,reporting issues,and implications for policy

The ‘mixed’ group, officially recognised in the 2001 Census, is one of the most rapidly growing ethnic groups in Britain. Although ‘mixed’ categorisation was added to ethnic coding in NHS datasets, our knowledge of health patterns for this population is meagre. Data quality problems remain a key obstacle, including poor reproducibility of the data and constraints on reporting due to sparse data bias. The consequent minimal and indicative evidence base has focused mainly on risky health behaviours, mental health and generic measures of self-rated health, as it has in the U.S.A. and Canada. There is negligible information on the main underlying causes of death, such as neoplasms, heart disease and stroke. Consideration should be given to pooling data across multiple years of health and general purpose surveys to enable reporting for the four ‘mixed’ categories and adjustment for mediating factors and relevant confounders, such as measures of socio-economic status.     

Blood,Sweat, and Tears: Navigating Creepy versus Cool in Wearable Biotech

ABSTRACT

This paper considers how personal data protections figure into the design process of wearable technology. The data question is becoming especially important in the face of recent innovations in biotechnology that capitalize on the new fungibility of biology and electronics, in which new biotech wearables capitalize on the ability to analyze and track changes in blood, sweat, and tears. Interviews and participant observation with wearable tech designers, data scientists, fashion tech entrepreneurs, and select experts in cybersecurity and intellectual property law, reveal a range of approaches to data protection in design within the culture where wearables are beginning to merge with biotech. While a few respondents were extremely vigilant about protecting consumer’s privacy, the majority felt that when consumers ‘opt in’ to data sharing, they should be cognizant of the risks. From their perspective, it is not necessarily the producer’s responsibility to protect user's personal data. These attitudes present a problematic logic, which leaves users vulnerable to data exploitation. The paper concludes by arguing that this laissez-faire culture is the environment in which wearable biotech is being developed and will be deployed. This emerging technology raises issues about bodies, data, and ownership in crucial need of analysis and critique to push its move into the mainstream toward more equitable and inclusive ends.     

Analysis of social innovation on social networking services

ABSTRACT

Social network services are allowing more social connectivity and making possible sharing information and knowledge of a different nature. This article analyses if social workers related to active social policies from Malaga province (Spain) are using social network services to share information and knowledge and if there is a mirror between online and offline relationships. Since it is an experimental model, through virtual ethnography and through social network analysis methodology, we observed the presence, connectivity and analysed the structure of relationships that keep 235 professionals from 52 organizations in Facebook®. Moreover, the model uses the statistical technique of modularity for detecting online communities, which are compared with distribution of professionals in their organizations. Results show how social network services applied to social intervention are massively and frequently used by professionals. On the other hand, the detected communities reflect existence of analogy between online and offline relationships. The online structure shows a high degree of cohesion and how certain professionals have higher capacity of influence and diffusion depending on position in the online structure. It argues about the opportunity to incorporate social network services towards social intervention as a manner of social innovation to improve cooperation and diffusion of information and knowledge.     

Data Science: A Powerful Catalyst for Cross-Sector Collaborations to Transform the Future of Global Health—Developing a New Interactive Relational Mapping Tool (Demo)

ABSTRACT

The increasingly complex and rapidly changing global health and socioeconomic landscape requires fundamentally new ways of thinking, acting, and collaborating to solve growing systems challenges. Cross-sectoral collaborations between governments, businesses, international organizations, private investors, academia, and nonprofits are essential for lasting success in achieving the Sustainable Development Goals (SDGs), and securing a prosperous future for the health and well-being of all people (United Nations, n.d United Nations. (n.d.). SDGs: Sustainable development knowledge platform. Sustainable Development United Nations. Retrieved from https://sustainabledevelopment.un.org/ [Google Scholar].). Our aim is to use data science and innovative technologies to map diverse stakeholders and their initiatives around SDGs and specific health targets—with particular focus on SDG 3 (Good Health & Well Being) and SDG 17 (Partnerships for the Goals)—to accelerate cross-sector and multidisciplinary collaborations. Initially, the mapping tool focuses on Geneva, Switzerland as the world center of global health diplomacy with over 80 key stakeholders and influencers present. As we develop the next level pilot, we aim to build on users’ interests, with a potential focus on non-communicable diseases (NCDs) as one of the emerging and most pressing global health issues that requires new collaborative approaches. Building on this pilot, we can later expand beyond only SDG 3 to other SDGs.     

Researcher reflexivity: exploring the impacts of CAQDAS use

Computer-assisted qualitative data analysis software (CAQDAS) programs are established tools for qualitative research. Making informed decisions when using them requires researchers to understand how they affect research practices and outcomes. In this article we consider the impact of CAQDAS on researcher reflexivity. Reviewing three decades of literature, we identify specific ‘reflexive moments’ experienced by CAQDAS users, the contexts in which they occur, the issues they raise, and the reflexive awareness they generate. The ways in which CAQDAS can enhance or undermine researcher reflexivity are also reported. By doing so, we aim to help researchers and especially research students (and their supervisors) understand the relationship between CAQDAS and reflexivity and the reflexive moments they may encounter when using such software.     

From peaceful marches to violent clashes: a micro-situational analysis

Recent studies point to the relevance of situational factors in the emergence of violence. This paper applies these insights to a systematic analysis of how and why peaceful protest marches transform into violent clashes. It focuses on the micro-situational patterns and emotional dynamics during protests. The exploratory study compares 20 peaceful and violent protests of the Global Justice Movement in the United States and Germany. It employs a triangulation of visual data with document data. The study relies on in-depth qualitative analysis, based on the principles of process tracing. Findings suggest that in those protests where violence emerges, a prior micro-situational pattern is systematically visible. The discussion of exemplary cases shows that two emotional phases precede the outbreak of violence. These phases emerge in a specific temporal danger zone of 1–3 h after the start of a protest. Further, specific triggering moments seem to prompt the outbreak of violence, like the breaking-up of police–protester lines, actors being outnumbered, or falling down. The emotional dynamic between protesters and officers during a protest likewise influences the intensity of violence and how violent situations end. Consequently, the paper suggests that actors need to go through a confrontational micro-situation in a demonstration in order to be able to use violence.     

The methodology of a multi-model project examining how facebook infrastructures social relations

It is the purpose of this paper to make explicit the methodology (the theory of the methods) by which we conducted research for an Economic and Social Research Council-funded research project on the relationship of values to value. Specifically, we wanted to study the imperative of Facebook to monetize social relationships, what happens when one of our significant forms of communication is driven by the search for profit, by the logic of capital. We therefore wanted to ‘get inside’ and understand what capital's new lines of flight, informationally driven models of economic expansion, do to social relations. Taking up the challenge to develop methods appropriate to the challenges of ‘big data', we applied four different methods to investigate the interface that is Facebook: we designed custom software tools, generated an online survey, developed data visualizations, and conducted interviews with participants to discuss their understandings of our analysis. We used Lefebvre's [(2004). Rhythmnanalysis: Space, time and everyday life. London: Continuum] rhythmanalysis and Kember and Zylinska's [(2012). Life after new media: Mediation as a vital process. Cambridge, MA: MIT Press] ideas about ‘lifeness’ to inform our methodology. This paper reports on a research process that was not entirely straightforward. We were thwarted in a variety of ways, especially by challenge to use software to study software and had to develop our project in unanticipated directions, but we also found much more than we initially imagined possible. As so few academic researchers are able to study Facebook through its own tools (as Tufekci [(2014 Tufekci, Z. (2014). Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In ICWSM ‘14: Proceedings of the 8th International AAAI Conference on Weblogs and Social Media, pp. 505–514. [Google Scholar]). Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In ICWSM ‘14: Proceedings of the 8th International AAAI Conference on Weblogs and Social Media (pp. 505–514)] notes how, unsurprisingly, at the 2013 ICWSM only about 5% of papers were about Facebook and nearly all of these were co-authored with Facebook data scientists), we hope that our methodology is useful for other researchers seeking to develop less conventional research on Facebook.     

Comparing the effectiveness of respondent-driven sampling and quota sampling in migration research

We evaluate the effectiveness in empirical migration research of the respondent-driven sampling (RDS) and the quota sampling with regard to four criteria: quality of the data; sociometric diversity of the sample; geographic coverage of the sample; and cost-effectiveness. We review two surveys of ex-USSR migrants, conducted simultaneously in the Warsaw metropolitan area, each undertaken with the use of one of the two sampling methods. We find that although the RDS was considerably costlier, it enabled faster data collection and posed a lower risk of underestimating the cost of the survey. We also find that the RDS generated higher-quality data, and that it was more successful in surveying short-term circular migrants. This comparative evaluation contributes to the literature on social research methods in that it links the sampling methods with the quality and character of the data, and helps assess the usefulness and applicability of RDS in empirical migration studies.     

大数据背景下产业链内部间隙弥补与企业运营效率提升

近年来,电子商务从产生到不断壮大,越来越多地受到相关信息技术和商业模式影响。大数据分析和数据挖掘技术逐渐运用于各行各业,电子商务及相关交易作为典型的经济活动,其相互交融与影响对产业经济发展具有重要意义。然而,渠道完备化的电子商务产业链整合由于部分机制的低效性,其内部存在基于要素与终端、数据融通、需求满足层面的诸多间隙,需要通过大数据等技术支撑及渠道、市场的有效对接实现产业链企业的整合。通过对这些作用机制及优化路径的研究发现：应通过价值提升维度实现大数据在产业链内部企业融通中的应用,提高其在目标群体识别和需求预测中的应用,同时提高大数据在企业布局推广中的应用,以有效提升企业运营效率。     

基于DEA模型的京津冀科技与金融结合效率研究

由于金融业和科学技术的高度融合在较大程度上推动了中国经济社会的发展,科技与金融相结合发展已成为一种创新型发展趋势,文章借鉴现有的评价科技与金融结合效率的指标体系,运用数据包络分析模型对2005—2019年京津冀地区的金融投入与科技产出进行分析,研究其科技与金融相结合的效率,研究结果表明：在2019年京津冀三地科技与金融结合效率良好,均达到了有效状态,北京市科技与金融总体效率有9年未达到有效状态,天津市有13年未达到有效状态,河北省有12年未达到有效状态。根据研究结果,文章对京津冀地区科技与金融服务结合的未来发展提出建议。