A many-analysts approach to the relation between religiosity and well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β=0.120). For the second research question, this was the case for 65% of the teams (median reported β=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates

A Many-analysts Approach to the Relation Between Religiosity and Well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N = 10, 535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β = 0.120). For the second research question, this was the case for 65% of the teams (median reported β = 0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates

Supporting data for 'The level of climate-change mitigation depends on how humans assess the risk arising from missing the 2°C target' ​doi:10.1057/palcomms.2017.27

The level of climate-change mitigation depends on how humans assess the risk arising from missing the 2 °C target. Data supports following publication: http://www.palgrave-journals.com/articles/palcomms20172

Experimental game instructions

In the beginning of our experiment, subjects were asked to read a few pages on their computer screens that would explain the rules of the subsequent game. Here, we provide these instructions, translated from German

Asymmetric Power Boosts Extortion in an Economic Experiment

Direct reciprocity is a major mechanism for the evolution of cooperation. Several classical studies have suggested that humans should quickly learn to adopt reciprocal strategies to establish mutual cooperation in repeated interactions. On the other hand, the recently discovered theory of ZD strategies has found that subjects who use extortionate strategies are able to exploit and subdue cooperators. Although such extortioners have been predicted to succeed in any population of adaptive opponents, theoretical follow-up studies questioned whether extortion can evolve in reality. However, most of these studies presumed that individuals have similar strategic possibilities and comparable outside options, whereas asymmetries are ubiquitous in real world applications. Here we show with a model and an economic experiment that extortionate strategies readily emerge once subjects differ in their strategic power. Our experiment combines a repeated social dilemma with asymmetric partner choice. In our main treatment there is one randomly chosen group member who is unilaterally allowed to exchange one of the other group members after every ten rounds of the social dilemma. We find that this asymmetric replacement opportunity generally promotes cooperation, but often the resulting payoff distribution reflects the underlying power structure. Almost half of the subjects in a better strategic position turn into extortioners, who quickly proceed to exploit their peers. By adapting their cooperation probabilities consistent with ZD theory, extortioners force their co-players to cooperate without being similarly cooperative themselves. Comparison to non-extortionate players under the same conditions indicates a substantial net gain to extortion. Our results thus highlight how power asymmetries can endanger mutually beneficial interactions, and transform them into exploitative relationships. In particular, our results indicate that the extortionate strategies predicted from ZD theory could play a more prominent role in our daily interactions than previously thought

Experimental data

The raw data file containing the experimental decisions of all our study subjects

In the treatment with replacement, double players benefit from being extortionate.

<p>The graph shows cooperation rates (<b>A</b>) and payoffs (<b>B</b>) in the treatment with replacement, depending on whether the double player was classified as extortionate or not. Error bars represent standard errors. Extortionate players were less cooperative than non-extortionate players; nevertheless they received more cooperation from their respective co-players. As a result, extortionate double players outperformed both their direct co-players and non-extortionate double players.</p

Extortioners incentivize their co-players to cooperate, and they obtain an excessive share of the resulting payoffs.

<p>For groups with an extortionate double player in the treatment with replacement, the graph shows how both the single and the double players’ payoffs depend on the single player’s cooperation rate. Each dot corresponds to an outcome of a 10-round block, across the 13 extortionate groups; the two lines represent linear regression curves. Extortioners adopt a strategy such that single players benefit from increasing their cooperation rate within each 10-round block (as the blue line has a positive slope). The more cooperative single players are, the higher is the share of total payoffs that goes to the extortioner (as the distance between the two lines becomes maximal when the single players’ cooperation rate approaches 100%).</p

Overview of the experimental setup.

<p>Players interact in a repeated prisoner’s dilemma over 60 rounds. In each round they choose between the option C (corresponding to cooperation) and the option D (referring to defection). Payoffs are taken from Axelrod [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0163867#pone.0163867.ref016" target="_blank">16</a>]: mutual cooperation yields the reward <i>R</i> = € 0.30 for both players, whereas mutual defection gives the punishment payoff <i>P</i> = € 0.10; if only one player cooperated, the cooperator receives the sucker’s payoff <i>S</i> = € 0.00 and the defector receives the temptation <i>T</i> = € 0.50. Both treatments have in common that the game is asymmetric, as double players have twice as many interactions as single players. But the second treatment adds another source of asymmetry, as only double players have the option to replace one of their co-players by the inactive player. The rules of the game, as well as the strategic options of each player were commonly known (except that subjects were not aware of the exact length of the game). In addition, each subject was informed about the decisions of all other group members after each round. For the statistical analysis we considered groups of players as our statistical unit, and we used non-parametric and two-tailed tests throughout. To compare double players with single players, we pooled the decisions of all active single players within a group. Moreover, as double players had more interactions than single players, we considered payoffs per interaction (unless stated otherwise). For the treatment with replacement, the reported total earnings for single players give the average over all three single players (including the inactive player). For details, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0163867#sec007" target="_blank">Methods</a>.</p