Dominik S. Meier

Monitoring progress on the United Nations Sustainable Development Goals (SDGs) is important for both academic and non-academic organizations. Existing approaches to monitoring SDGs have focused on specific data types; namely, publications listed in proprietary research databases. We present the text2sdg package for the R language, a user-friendly, open-source package that detects SDGs in any kind of text data using different existing or custom-made query systems. The text2sdg package thereby facilitates the monitoring of SDGs for a wide array of text sources and provides a much-needed basis for validating and improving extant methods to detect SDGs from text.

A number of labeling systems based on text have been proposed to help monitor work on the United Nations (UN) Sustainable Development Goals (SDGs). Here, we present a systematic comparison of systems using a va- riety of text sources and show that systems differ con- siderably in their specificity (i.e., true-positive rate) and sensitivity (i.e., true-negative rate), have systematic bi- ases (e.g., are more sensitive to specific SDGs relative to others), and are susceptible to the type and amount of text analyzed. We then show that an ensemble model that pools labeling systems alleviates some of these lim- itations, exceeding the labeling performance of all cur- rently available systems. We conclude that researchers and policymakers should care about the choice of label- ing system and that ensemble methods should be favored when drawing conclusions about the absolute and rela- tive prevalence of work on the SDGs based on automated methods.

The seventeen Sustainable Development Goals (SDGs) were adopted in 2015 and achieving them by 2030 is crucial for human development. However, progress on the goals currently remains short of the requirements. As the third and public sectors play a crucial role in achieving the goals, this study analyzes how the SDG-related third sector and public administration literature has evolved over the last thirty years. I use a state-of-the-art method to map articles to the SDGs. In contrast to previous studies that have found an increase in publications that directly mention the SDGs, I find a decline in the proportion of articles that relate to the SDGs without necessarily mentioning them directly. I also analyze how the SDG-relatedness of an article corresponds to its citation count. While I find mixed results across SDGs and data sources, the relationship between SDG-relatedness and citation count is significantly more positive for work published after the adoption of the SDGs. While the association between SDG-relatedness and citation count is now positive for the third sector literature published after 2015, it is still negative for the public administration literature.

The COVID-19 pandemic affected the provision of voluntary work across the globe. We study informal volunteers who buy and deliver groceries for people in a high-risk group or in quarantine. Using data from a volunteering grocery delivering app in Switzerland that coordinated these volunteers, we are able to track volunteering during the pandemic. Combined with public health data on cases and deaths, we test how the severity of the pandemic affects the provision of voluntary work in the form of neighborhood grocery deliveries. We find a positive effect of the number of deaths on voluntary deliveries. However, in contrast to the literature studying the effect of the severity of the pandemic on giving, this effect is concave. We suggest that this concave effect is due to the signal of risk of infection implied by rising death rates, which is at odds with the signal of need to help others.

People tend to donate more to help a single rather than a group of victims. However, recent studies were able to reverse this compassion fade effect by presenting people with multiple donation appeals with different victim group sizes (joint evaluation) instead of just one donation appeal (separate evaluation). Because practitioners often use the compassion fade effect to boost giving, the reversal of this effect in joint evaluation settings has important implications for fundraising. This study tests whether the reversed compassion fade effect can be replicated in the field by using data from the crowdfunding platform GoFundMe. When browsing projects on GoFundMe, people see multiple projects displayed at once, placing them in a joint evaluation context. I found a concave effect of the perceived victim group size on the amount of funds raised, the number of donations received, and the size of the average donation received by a project.