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Created on Aug 13th, 2019
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Analyzing Cross-Societal Variation in Cooperation

Created 2 years ago

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:

  1. What indicators are available for cross-societal analyses?
  2. How many indicators were obtained per country/region included in CoDa?
  3. How many countries/regions are documented per indicator?
  4. A few examples of how societies vary on different indicators
  5. 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).

How did cooperation research change over time?

Created 3 years ago

by Daniel Balliet, Giuliana Spadaro, Benny Markovitch, & Wouter Beek

The Cooperation Databank (CoDa) contains studies about human cooperation using social dilemmas that were conducted between 1958 and 2017. Social dilemmas may be one of the longest used standardized methods to study human social behavior. This research tradition began with the use of the prisoner’s dilemma. Although researchers continue to use this method, several other paradigms have been developed to study cooperation, including public goods dilemmas and resource dilemmas. Also, the participants involved in these studies may have changed over time. And certainly the topics (e.g., independent variables) that researchers have focused on has changed over the past 60 years.

For example, earlier research was based mostly on student samples in psychology laboratories, but more recent years may have seen changes in terms of student samples and the country of participants. Early research focused on a few topics, such as communication and individual differences, but the topics have expanded across the years to include other variables that can explain cooperation. Here, we report how methods, samples, and topics have changed over the course of 60 years of research on human cooperation using social dilemmas.

Importantly, this review is a living document that will be automatically updated with the entry of new studies to CoDa.

This data story will address the following questions:

  1. Did methods change over time?
  2. Did samples change over time?
  3. How did research topics change over time?

In this data story we do not define the many different method characteristics, sample characteristics, and independent variables used in cooperation research. You can learn about the definitions and values of these variables at the CoDa website and using the ontology explorer in the CoDa platform.

Did methods change over time?

We begin by plotting studies over time (year of data collection) according to the different types of social dilemma paradigms. As displayed in Figure 1, studies began using the prisoner's dilemma, but since 2000, relatively more studies have been conducted using the public goods dilemma. Resource dilemmas have received relatively much less attention in the history of research on cooperation.

What's in the Databank?

Created 3 years ago

by Daniel Balliet, Giuliana Spadaro, Benny Markovitch, & Wouter Beek

The Cooperation Databank (CoDa) includes an annotated history of empirical studies on human cooperation in social dilemmas. Social dilemmas are situations that involve a conflict of interests and people must choose between a behavior that is best for themselves and a behavior that is best for the collective. Cooperation is choosing to do a behavior that is best for the collective. CoDa contains six decades of studies on individual decision making in dyads and groups facing social dilemmas.

The studies have been annotated by domain experts according to differences in the samples, study characteristics, and for the variables used to predict cooperation within the studies. Here we report an overview of the history of research on cooperation and how studies vary according to each of these variables. Effect sizes have also been documented on the relation between different variables predicting cooperation. When using the CoDa platform to search the Databank and conduct meta-analyses, you can use these variables to search and select studies and to predict variance in effect sizes.

One benefit of CoDa is that we can write living reviews on the history of research on cooperation, which are directly connected to the data, become updated when new studies are added to the Databank, and that allow people to interact with the data. Our first living review (i.e., data story) using CoDa describes the data in the Databank. In this data story we address:

  1. How many papers, studies, effects and treatments are annotated in the Databank?
  2. How did the field of cooperation research grow over time?
  3. How do studies vary according to sample and study characteristics?
  4. How do effect sizes and standard errors vary across studies?
  5. Which variables are used to predict cooperation within the studies?
  6. Learn how CoDa can be used to study trends in research over time.
  7. Learn about the meta-study data in CoDa, such as publication status, prolific authors, and country.

Each of these topics provide interactive figures that allow you to efficiently acquire information for own your research, casually browse the information in the Databank, and explore for yourself the trends in research on cooperation.

In this data story we do not define all of the variables used in cooperation research. You can learn about the definitions and values of these variables at the CoDa website and using the ontology explorer in the CoDa platform.