Jeroen Smits

This paper introduces the Journal Popularity Score (JPS), a usage-based indicator of journal popularity derived from visits to journal pages on the SciRev.org website. Whereas citation-based indicators measure journal status through references to published work, the JPS captures researchers' interest in journals as possible publication outlets. Using SciRev traffic data for 2020-2025, after removing documented and likely bot traffic, we examine how journal visits vary by discipline, citation-based prestige, open access status, publisher type, and region of visiting researchers. The results show that journal popularity is highly unevenly distributed and differs strongly across disciplines. It is positively related to citation-based indicators, but only moderately, indicating that popularity cannot be reduced to citation-based impact alone. Subscription journals still receive the largest share of visits, while open access journals account for almost 30 percent, with notable regional differences. Publisher patterns further show the strong position of large commercial publishers, learned-society journals, and established open access publishers. The JPS therefore adds a new perspective to journal evaluation by capturing researchers’ active interest in journals as possible publication outlets.

This paper introduces the Journal Popularity Score (JPS), a usage-based indicator of journal popularity derived from visits to journal pages on the SciRev.org website. Whereas citation-based indicators measure journal status through references to published work, the JPS captures researchers' interest in journals as possible publication outlets. Using SciRev traffic data for 2020-2025, after removing documented and likely bot traffic, we examine how journal visits vary by discipline, citation-based prestige, open access status, publisher type, and region of visiting researchers. The results show that journal popularity is highly unevenly distributed and differs strongly across disciplines. It is positively related to citation-based indicators, but only moderately, indicating that popularity cannot be reduced to citation-based impact alone. Subscription journals still receive the largest share of visits, while open access journals account for almost 30 percent, with notable regional differences. Publisher patterns further show the strong position of large commercial publishers, learned-society journals, and established open access publishers. The JPS therefore adds a new perspective to journal evaluation by capturing researchers’ active interest in journals as possible publication outlets.

Addressing socioeconomic vulnerabilities is essential for building sustainable societies that can withstand climate change and natural disasters. Yet identifying the areas most at risk is often difficult, because relevant data are typically available only at the national level. To fill this gap, a subnational extension of the GDL Vulnerability Index was recently presented for 1260 areas across the developing world. This GVI is designed to reflect the human dimensions of vulnerability to climate change, natural hazards, and other kinds of shocks. In the present study, we introduce a new database providing comparable subnational data for 490 areas in 48 upper-middle- and high-income countries. Combined with the earlier data, this enables the first overview of subnational vulnerability on a global scale. Our findings show that, since 2000, overall vulnerability in wealthy countries has declined by 27%, while inequality in vulnerability has remained broadly stable. Incorporating subnational variation into the vulnerability profile of these countries raised the total observed variation in vulnerability up to 39%. By highlighting local inequalities in susceptibility, coping capacity and adaptive capacity, the Subnational GVI (SGVI) generates valuable new evidence to improve global monitoring and support policy responses aimed at climate resilience and sustainable development.

To achieve a sustainable society that is resilient to climate change and natural disasters, it is essential that socioeconomic vulnerabilities are addressed. However, within poor countries, hotspots of vulnerabilities are difficult to identify, as for these countries existing vulnerability measures are only available at the national level. Here, we address this issue by presenting a subnational version of the Global Data Lab Vulnerability Index (GVI), a composite index designed to monitor and analyze the human dimensions of vulnerability to climate change, natural disasters, and other kinds of shocks. The Subnational GVI (or SGVI) is available for 1260 regions across 118 Low- and Middle-Income Countries (LMICs), providing an over 10 times more detailed picture of socioeconomic vulnerability than was possible before. Decomposition analyses reveal that this higher resolution increases the observed variation in vulnerability by more than 70 percent in the poorest regions. Since 2000, total vulnerability across LMICs has declined by about 24%, but at the same time the variation in vulnerability has increased, thus highlighting the importance of subnational data. By capturing localized disparities in coping capacity, adaptive capacity, and susceptibility, the SGVI provides vital new insights and data for climate adaptation and sustainable development planning.

In this paper we describe and present the Subnational Gender Development Database. This database contains for the period 2000-2023 the national and subnational values of the Subnational Gender Development Index (SGDI), the male and female values of the Subnational Human Development Index and the underlying gender-specific education, health and standard of living indices. The subnational values of the indicators were computed on the basis of data from statistical offices and from the Area Database of the Global Data Lab, which contains indicators aggregated from household surveys and census datasets. These subnational values were computed in such a way that their population-weighted national averages are equal to their official national values, as presented by the United Nations Development Program (UNDP) in their Human Development Reports. Subnational values for missing years have been calculated by using interpolation and extrapolation on the basis of real values. The SGDI Database contains values for the SGDI and underlying indicators for 1810 subnational regions in 166 countries.

To achieve a sustainable society that is resilient to climate change and natural disasters, it is essential that socioeconomic vulnerabilities are addressed. However, within poor countries, hotspots of vulnerabilities are difficult to identify, as for these countries existing vulnerability measures are only available at the national level. Here we address this issue by presenting a subnational version of the GDL Vulnerability Index (GVI), a composite index designed to monitor and analyze the human dimensions of vulnerability to climate change, natural disasters, and other kinds of shocks. The Subnational GVI (or SVGI) is available for 1300+ regions across 121 Low- and Middle-Income Countries (LMICs), providing an over 10 times more detailed picture of socioeconomic vulnerability than was possible before. Decomposition analyses reveal that this higher resolution increases the observed variation in vulnerability by more than 70 percent in the poorest regions. Since 2000, total vulnerability across LMICs has declined by about 24%, but at the same time the variation in vulnerability has increased, thus highlighting the importance of subnational data. By capturing localized disparities in coping capacity, adaptive capacity and susceptibility, the SGVI provides vital new insights and data for climate adaptation and sustainable development planning.

In this paper we present the GDL Vulnerability Index (GVI), a new composite index to monitor and analyse the human components of vulnerability to climate change, natural disasters, and other kinds of shocks, for societies and geographic areas across the globe. The GVI is a simple and flexible index designed for use by experts as well as non-experts in the climate field, including researchers, (local) politicians, NGO’s, journalists, advocacy groups and grassroot movements. The GVI is based on an additive formula that summarizes the essence of seven socioeconomic dimensions of vulnerability into a single number. This formula approach sets this index apart from other existing indices. Any person who knows the values of the underlying indicators can compute the vulnerability score of an area by filling in these values in the GVI formula. Validity tests show that the data-driven GVI measures the vulnerability dimensions coping capacity, adaptive capacity and susceptibility as well as major expert-based indices. This offers great prospects for use in situations where no other vulnerability information is available. Here we explain the construction of the GVI, test its validity and present GVI values for (almost) all countries of the world and for major global regions.

This data descriptor presents the Subnational Corruption Database (SCD), which provides data on corruption in 1,473 subnational areas of 178 countries. The SCD includes a comprehensive overall corruption index, the Subnational Corruption Index (SCI), and its two components: the Subnational Grand Corruption Index (SGCI) and Subnational Petty Corruption Index (SPCI). The SCD is constructed by combining data of 807 surveys held in the period 1995–2022 and includes the corruption experiences and perceptions of 1,326,656 respondents along 19 separate dimensions. The data are available for multiple years, allowing longitudinal analyses. At the national level, the SCI correlates strongly with established corruption indices, like the Transparency International Corruption Perceptions Index (CPI) and the World Bank Control of Corruption Index (CCI). We create subnational estimates of the CPI and CCI by superimposing the subnational variation of the SCI around the national averages of these indices. The presentation of subnational data in the SCD and the separation between grand and petty corruption significantly broaden the global knowledge base in the field of corruption.

Current models inadequately address the role of information transfer in explaining the slow fertility decline in sub‐Saharan Africa (SSA) in the 1990s and 2000s. We posit that an important reason for this slow decline was the high level of social isolation of the rural population in the region, as a result of which new ideas regarding fertility had difficulty reaching them. Applying Poisson regression to survey data on 180,000 women across 25 SSA countries spanning 1995–2010, we find clear associations of travel distance to urban areas and TV ownership with desired and actual fertility. Interaction analyses reveal a compensatory relationship between distance and TV ownership, with the effect of distance almost disappearing for households with a TV and the effect of TV disappearing for households close to urban areas. The role of information access is further stressed by the finding that socioeconomic factors, while highly significant overall, offer limited explanatory value for women living at great distance from urban centres or without TV access. If information transfer is indeed as important as our findings suggest, the increasing availability of smartphones and social media in rural SSA might lead to a faster fertility decline in the region than foreseen by the latest UN population estimates.