By Giuliana Spadaro, Caroline Graf, Ilaria Tiddi, & Daniel Balliet
The Cooperation Databank (CoDa) contains studies of human cooperation that were conducted in over 70 different countries. Previous theory and research have claimed that cooperation may vary in meaningful ways across different societies. CoDa empowers researchers to explore how the outcomes of studies conducted in different societies can vary according to different economic, institutional, cultural, and ecological factors. Here you can view the cross-societal indicators that are available for analyses using the CoDa platform. We have collected the most relevant indices that have been stressed in prior theory to be important in explaining variation in cooperation across societies, such as religiosity, government effectiveness, and relational mobility. We have also used linked data to obtain an even broader range of variables than discussed in past research to facilitate further exploration of how study results vary across societies.
This data story reports:
- What indicators are available for cross-societal analyses?
- How many indicators were obtained per country/region included in CoDa?
- How many countries/regions are documented per indicator?
- A few examples of how societies vary on different indicators
- A few examples of how societies can change over time on some indicators
This document is a living review that is directly connected to the data in CoDa and will be automatically updated based on the entry of new information (e.g., when new cross-societal indices are added to CoDa).
What indicators are available for cross-societal analyses?
Are there differences in how people cooperate in different societies and cultures? Cooperation could vary across societies according to different institutions (e.g., rule of law, government effectiveness), cultural values and beliefs (e.g., trust, collectivism, survival versus self-expression), ecologies (e.g., relational mobility, historical prevalence of pathogens), and economy (e.g., market competitiveness, wealth inequality). CoDa offers a wide range of indices that measure differences across societies and which can be used to predict differences across societies. Table 1 provides a list of all the indices, including their label, definition, and a link to the source of the data, which can be used to acquire further information about each specific index.
Table 1. The cross-societal indicators included in the CoDa research platform, including their label, definition, and source
How many indicators were obtained per country/region included in CoDa?
Not every country/region included in CoDa is represented for each index. Some countries/regions, such as Oman and Nicaragua, are represented by only a few indicators, while other countries, such as Spain and Argentina, are represented by most all indicators. Figure 1 documents how many indicators were obtained for each country/region included in CoDa.
Figure 1 - Number of indicators that were obtained per country included in CoDa
How many countries/regions are documented per indicator?
Each indicator is only documented for a specific number of countries included in CoDa. Figure 2 reports the number of countries that are reported for each indicator. Some indicators can represent most all countries included in CoDa, such as the control over corruption index and the democracy index. However, other indicators represent very few countries included in CoDa, such as the literacy rate and suicide rate.
Figure 2 - Number of countries that are represented for each indicator included in CoDa
A few examples of how societies vary on different indicators
Figure 3a - Cross-societal variation in Gross Domestic Product per country/region included in CoDa
Figure 3b - Cross-societal variation in rule of law among the countries/regions included in CoDa
Figure 3c - Cross-societal variation in government effectiveness among the countries/regions included in CoDa
Figure 3d - Cross-societal variation in democracy among the countries/regions included in CoDa
A few examples of how societies can change over time on some indicators
Figure 4a - How wealth inequality (GINI z-score) varied over time in China, the Netherlands, and the United States, and compared with worldwide average
Belief in hell of Argentina, Japan, Chile
** Figure 4b ** - How beliefs in hell (z-score) varied over time in Argentina, Chile and Japan, and compared with worldwide average belief in hell.
** How to cite this report: **
Spadaro, G., Graf, C., Tiddi, I., & Balliet, D. (2020, date). Analyzing Cross-Societal Variation in Coopertion. Cooperation Databank. Link.
