Data Curation Implications of Qualitative Data Reuse and Big Social Research

Objective: Big social data (such as social media and blogs) and archived qualitative data (such as interview transcripts, field notebooks, and diaries) are similar, but their respective communities of practice are under-connected. This paper explores shared challenges in qualitative data reuse and big social research and identifies implications for data curation. Methods: This paper uses a broad literature search and inductive coding of 300 articles relating to qualitative data reuse and big social research. The literature review produces six key challenges relating to data use and reuse that are present in both qualitative data reuse and big social research—context, data quality, data comparability, informed consent, privacy & confidentiality, and intellectual property & data ownership. Results: This paper explores six key challenges related to data use and reuse for qualitative data and big social research and discusses their implications for data curation practices. Conclusions: Data curators can benefit from understanding these six key challenges and examining data curation implications. Data curation implications from these challenges include strategies for: providing clear documentation; linking and combining datasets; supporting trustworthy repositories; using and advocating for metadata standards; discussing alternative consent strategies with researchers and IRBs; understanding and supporting deidentification challenges; supporting restricted access for data; creating data use agreements; supporting rights management and data licensing; developing and supporting alternative archiving strategies. Considering these data curation implications will help data curators support sounder practices for both qualitative data reuse and big social research.

Gender Gap in Political Science: An Analysis of the Scientific Publications and Career Paths of Italian Political Scientists

ABSTRACT This article assesses whether a gender gap in political science, identified in the international literature, also is present in the context of Italian political science. The literature has mostly centered on the comparison of female publication rates in international journals with the academic workforce in the United States, but this raises an issue of data comparability. As an alternative strategy to avoid comparability biases, this study focuses on the analysis of a single national case: Italy. The article evaluates to what extent the “glass-ceiling” effect persists for political scientists who intend to publish their contributions. By analyzing data on articles published between 2015 and 2020 by the three major Italian political science journals, this contribution shows that (1) the proportion of published articles written by female authors is lower than that of male authors; (2) the hypothesis that the lower female proportion depends on a lower female presence in the field of political science is refuted; (3) there is little collaboration between men and women; (4) there is a correlation between the presence of female editors in scientific journals and the proportion of female-authored articles; and (5) gender differences are reflected in women’s academic career progression.

Injury characteristics in Norwegian male professional football: a comparison between a regular season and a season in the pandemic

The Coronavirus Disease-19 (COVID-19) pandemic forced the Norwegian male premier league football season to reschedule, reducing the fixture calendar substantially. Previous research has shown that a congested match schedule can affect injury rates in professional football. Therefore, we aimed to investigate whether the Norwegian premier league teams suffered more injuries in the match congested 2020 season than the regular 2019-season. We invited all teams having participated in both seasons to export their injury data. Only teams that used the same medical staff to register injuries in both seasons were included, and to maximise data comparability between seasons, we applied a time-loss injury definition only. Eight of 13 teams agreed to participate and exported their injury data. The 2020 season was 57 days shorter than the 2019 season. The match injury incidence differed insignificantly (incidence rate ratio 0.76 (0.48 to 1.20; p=0.24) in the 2020 season compared to the 2019 season. Furthermore, we found no differences in the number of injuries, days lost to injury, matches missed to injury, or injury severity. We present the first injury data from a complete post-lockdown professional football season. We could not detect any differences between the two seasons, suggesting the congested match calendar in the 2020 season is a safe alternative in future seasons.

Factors Influencing Asia-Pacific Countries’ Success Level in Curbing COVID-19: A Review Using a Social–Ecological System (SES) Framework

Little attention has been paid to the impacts of institutional–human–environment dimen-sions on the outcome of Coronavirus disease 2019 (COVID-19) abatement. Through the diagnosticsocial–ecological system (SES) framework, this review paper aimed to investigate what and howthe multifaceted social, physical, and governance factors affected the success level of seven selectedAsia-Pacific countries (namely, South Korea, Japan, Malaysia, Singapore, Vietnam, Indonesia, andNew Zealand) in combatting COVID-19. Drawing on statistical data from the Our World In Data web-site, we measured the COVID-19 severity or abatement success level of the countries on the basis ofcumulative positive cases, average daily cases, and mortality rates for the period of 1 February 2020to 30 June 2020. A qualitative content analysis using three codes, i.e., present (P), partially present(PP), and absent (A) for each SES attribute, as well as score calculation and rank ordering for govern-ment response effectiveness and the abatement success level across the countries, was undertaken.Not only did the standard coding process ensure data comparability but the data were deemedsubstantially reliable with Cohen’s kappa of 0.76. Among 13 attributes of the SES factors, highfacility adequacy, comprehensive COVID-19 testing policies, strict lockdown measures, imposition ofpenalty, and the high trust level towards the government seemed to be significant in determiningthe COVID-19 severity in a country. The results show that Vietnam (ranked first) and New Zealand(ranked second), with a high presence of attributes/design principles contributing to high-levelgovernment stringency and health and containment indices, successfully controlled the virus, whileIndonesia (ranked seventh) and Japan (ranked sixth), associated with the low presence of designprinciples, were deemed least successful. Two lessons can be drawn: (i) having high number of P forSES attributes does not always mean a panacea for the pandemic; however, it would be detrimentalto a country if it lacked them severely, and (ii) some attributes (mostly from the governance factor)may carry higher weightage towards explaining the success level. This comparative study providingan overview of critical SES attributes in relation to COVID-19 offers novel policy insights, thushelping policymakers devise more strategic, coordinated measures, particularly for effective countrypreparedness and response in addressing the current and the future health crisis.

Challenges to Evidence Synthesis and Identification of Data Gaps in Human Biomonitoring

The increasing number of human biomonitoring (HBM) studies undertaken in recent decades has brought to light the need to harmonise procedures along all phases of the study, including sampling, data collection and analytical methods to allow data comparability. The first steps towards harmonisation are the identification and collation of HBM methodological information of existing studies and data gaps. Systematic literature reviews and meta-analyses have been traditionally put at the top of the hierarchy of evidence, being increasingly applied to map available evidence on health risks linked to exposure to chemicals. However, these methods mainly capture peer-reviewed articles, failing to comprehensively identify other important, unpublished sources of information that are pivotal to gather a complete map of the produced evidence in the area of HBM. Within the framework of the European Human Biomonitoring Initiative (HBM4EU) initiative—a project that joins 30 countries, 29 from Europe plus Israel, the European Environment Agency and the European Commission—a comprehensive work of data triangulation has been made to identify existing HBM studies and data gaps across countries within the consortium. The use of documentary analysis together with an up-to-date platform to fulfil this need and its implications for research and practice are discussed.

Delphi consensus survey on how to document bilingual experience

While most investigations of bilingualism document participants’ language background, there is an absence of consensus on how to quantify bilingualism. The high number of different language background questionnaires used by researchers and practitioners jeopardises data comparability and cross-pollination between research and practice. Using the Delphi method, we asked 132 panellists (researchers, speech and language therapists, teachers) from 29 countries to rate 124 statements on a 5-point agreement scale. Consensus was pre-defined as 75% agreement threshold. After two survey rounds, 79% of statements reached consensus, revealing near-unanimity regarding the need for common methods to quantify bilingualism. Agreement was reached to document: language exposure and use, language difficulties, proficiency (when it cannot be assessed directly), education and literacy, input quality, language mixing practices, and attitudes (towards languages and language mixing). We discuss the implications of these findings for the creation of a new tool to quantify bilingual experience.

A data model for enhanced data comparability across multiple organizations

Organizations may be related in terms of similar operational procedures, management, and supervisory agencies coordinating their operations. Supervisory agencies may be governmental or non-governmental but, in all cases, they perform oversight functions over the activities of the organizations under their control. Multiple organizations that are related in terms of oversight functions by their supervisory agencies, may differ significantly in terms of their geographical locations, aims, and objectives. To harmonize these differences such that comparative analysis will be meaningful, data about the operations of multiple organizations under one control or management can be cultivated, using a uniform format. In this format, data is easily harvested and the ease with which it is used for cross-population analysis, referred to as data comparability is enhanced. The current practice, whereby organizations under one control maintain their data in independent databases, specific to an enterprise application, greatly reduces data comparability and makes cross-population analysis a herculean task. In this paper, the collocation data model is formulated as consisting of big data technologies beyond data mining techniques and used to reduce the heterogeneity inherent in databases maintained independently across multiple organizations. The collocation data model is thus presented as capable of enhancing data comparability across multiple organizations. The model was used to cultivate the assessment scores of students in some schools for some period and used to rank the schools. The model permits data comparability across several geographical scales among which are: national, regional and global scales, where harvested data form the basis for generating analytics for insights, hindsight, and foresight about organizational problems and strategies.

What drives the greater or lesser usage of forbearance measures by banks?

After the subprime crisis, with the worsening of asset quality all around Europe, a lack of harmonization emerged concerning credit classification, monitoring, provisioning and writing-off in the banking industry. A wave of analysis and new regulations by the Supervising Authorities aimed at highlighting best practices and creating a common standard, in order to enhance transparency and accounting data comparability across the European Union. A point of particular attention concerned the usage of forbearance measures and the classification and provisioning of forborne positions. This paper deep-dives into this issue leveraging on the public dataset disclosed by the European Banking Authority, following the 2018 EU-wide Transparency Exercise. The purpose of this paper is twofold. On one side, we want to gauge the extension of the forbearance measures’ usage among a sample of major European banks and the drivers of this usage. On the other side, we want to analyze which main factors impact on the loan loss provisioning of forborne positions.

Using Areal Interpolation to Deal with Differing Regional Structures in International Research

When working with regional data from different countries, issues concerning data comparability need to be solved, including regional comparability. Differing regional unit size is a common issue which influences the results of socio-economic analyses. In this paper, we introduce a strategy to deal with the regional incomparability of administrative data in international research. We propose a methodological approach based on the areal interpolation method, which facilitates the usage of advanced spatial analyses. To illustrate, we analyze spatial patterns of unemployment in seven Central European countries. We use a very detailed spatial (municipal) level to reveal local tendencies. To have comparable units across the whole region, we apply the areal interpolation method, a process of projecting data from source administrative units to the target structure of a grid. After choosing the most suitable grid structure and projecting the data onto the grid, we perform a hot spot analysis to show the benefits of the grid structure for socio-economic analyses. The proposed approach has great potential in international research for its methodological correctness and the ability to interpret results.