International Collaboration on Moral & Social Psychology:

Comparing Interventions Targeting Collective Action Against Climate Change 

Led by Dr. Madalina Vlasceanu1, Dr. Kimberly Doell1, and Prof. Jay J. Van Bavel1

1New York University

Countries from which researchers have pledged to collect data as of November 2021. We are still looking for collaborators who can target the remaining countries (in gray).

This is an open invitation for you to join us in conducting another Many-Labs-International-Study. We are planning to compare interventions aimed at stimulating collective action against climate change in 2022. By contributing, you will automatically become an author on our project from this collective effort.

All authors will be encouraged to vote on the interventions we will include in the study, propose additional measures to the study, and contribute to the editing and writing of the manuscript. Additionally, each author will have to contribute in at least one of 3 ways:

1) by collecting data from a country we don’t already have data from (i.e., this includes translating the survey into the local language, funding data collection for at least 500 participants, sending the dataset by specified deadline)

2) by proposing one of the top-five interventions accepted into the study by popular vote. The interventions should be amenable to targeting Dependent Variables such as: voting intentions (e.g., “when evaluating a candidate, how important is their sustainability stance”), sustainable policy support (e.g., “support for green tax”), social media information sharing (e.g., “willingness to share climate change information on social media page”).

3) by funding the data collection for a team in need of funds and helping them conduct their research.

Authorship will be determined using APA guidelines, with people contributing more intellectual work earning higher authorship positions (e.g., analyzing and managing data).

This call is open to any PI, postdoc, or graduate student interested in applying. 

Authorship will be limited to 2 researchers per lab (e.g., PI plus trainee).

As with our prior project, beyond the primary paper on which all collaborators will be a co-author, authors can take the lead on secondary publications via:

  • Publishing the complete dataset (e.g., Nature Scientific Data)
  • Conducting pre-registered analyses of the massive data for secondary publications
  • Including any secondary measures in your home country and using them to produce additional publications (these publications need not include anyone else, but you are free to coordinate measures with other teams).

To apply please follow this link: https://nyu.qualtrics.com/jfe/form/SV_41Sm4VGPxjJftNc


FAQs

  1. What is the timeline of this study?

November 15th, 2021: apply to become a collaborator using this form.

December 1st, 2021: submit the intervention you are proposing, there will be an updated link coming soon (if you have already submitted an intervention to the first form, you will receive an email to the address specified).

December 15th, 2021- January 1st, 2022: vote on the proposed interventions (voting survey will be emailed to you).

Spring, 2022: Teams will be responsible for translating the Qualtrics survey/interventions into their own language and applying for ethics approval. At the same time, we will be piloting, and submitting the main preregistration. 

Summer/Autumn, 2022: Data collection. 

  1. How long will the survey be?

We are planning to set the maximum length of the core survey to 15-20 minutes. For teams interested in adding supplementary measures to their own survey, they can do so at the end of the entire experiment. 

  1. Will the survey need to be implemented online?

Yes, we are going to use Qualtrics to program and deploy the survey. Individual teams will be in charge of copying the main Qualtrics survey, translating it into the appropriate language, and deploying it accordingly. If you do not have access to Qualtrics, please contact us at mov@alumi.princeton.edu.

  1. Can I add additional measures to the survey?

Yes, you may add anything you think is appropriate to your own survey, as long as it is at the very end of the study. 

  1. Is it possible to preselect which participants receive what intervention? 

No, participants will be randomly assigned to each condition.