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Research as Leisure: Experimental Evidence on Voluntary Contributions to Science
Last registered on July 19, 2017

Pre-Trial

Trial Information
General Information
Title
Research as Leisure: Experimental Evidence on Voluntary Contributions to Science
RCT ID
AEARCTR-0001854
Initial registration date
December 19, 2016
Last updated
July 19, 2017 12:16 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
UC San Diego
Other Primary Investigator(s)
PI Affiliation
Ivey Business School, Western University
Additional Trial Information
Status
Completed
Start date
2017-06-02
End date
2017-07-18
Secondary IDs
Abstract
Understanding why people have a desire to participate in science has critical implications for policy in public and private organizations, and for economic development and productivity more generally. Despite the importance of how and why people contribute to science, we know very little about these questions beyond the importance of career concerns for professional scientists. With the rise of crowd-sourcing and voluntary digital content provision, the potential for voluntary scientific contributions to advance scientific discovery could be large. Importantly, career concerns are unlikely to be important motivators for these volunteers. In this paper, we investigate why people voluntarily contribute to science and whether this desire can be increased through certain non-monetary incentives and research task modifications by running a field experiment on a voluntary crowd science platform. In particular, we will vary the expected contribution of the project in terms of scientific output in one treatment, and value of inputs in another. We will test how these variations affect the extent and quality of participation relative to an otherwise identical control project.
External Link(s)
Registration Citation
Citation
Lyons, Elizabeth and Laurina Zhang. 2017. "Research as Leisure: Experimental Evidence on Voluntary Contributions to Science." AEA RCT Registry. July 19. https://doi.org/10.1257/rct.1854-7.0.
Former Citation
Lyons, Elizabeth and Laurina Zhang. 2017. "Research as Leisure: Experimental Evidence on Voluntary Contributions to Science." AEA RCT Registry. July 19. https://www.socialscienceregistry.org/trials/1854/history/19658.
Experimental Details
Interventions
Intervention(s)
Treatment Groups:

Scientific Contribution Treatment: One explanation for voluntary contributions to science we will test in this project is that people may derive utility from the belief that they are contributing to a welfare enhancing public good (e.g., Bergstrom et al, 1986; Stiglitz, 1999). More specifically, they may volunteer their time to science because they derive a "warm glow" from participating actively in scientific discovery (Andreoni et al, 1996). To test this explanation, the scientific contribution of the research project will be emphasized in one of the project pages.

Value of Labor Supply Treatment: A related explanation for voluntary contributions to science is that people believe scientific discovery is important, and that their labor supply is more valuable than the money they could donate to buy the equivalent contribution (Andreoni et al, 1996). In this explanation, volunteers may not receive a warm glow from the act of contributing, but rather, they may believe scientific discovery is important and that their labor supply is the best way they can contribute to it. To test this explanation, the value of volunteer labor supply in the project in terms of the amount of paid labor it is substituting for will be emphasized in one of the project pages.

Control Group:
The control group will be sent a version of the project with a basic description and with none of the treatments described above.

References:

Andreoni, James, et al. "Charitable contributions of time and money." University of Wisconsin–Madison Working Paper (1996).

Bergstrom, Theodore, Lawrence Blume, and Hal Varian. "On the private provision of public goods." Journal of Public Economics 29.1 (1986): 25-49.

Stiglitz, Joseph E. "Knowledge as a global public good." Global public goods 1.9 (1999): 308-326.


Intervention Start Date
2017-06-02
Intervention End Date
2017-07-18
Primary Outcomes
Primary Outcomes (end points)
Number of contributors, number of contributions made per contributor, quality of contributions
Primary Outcomes (explanation)
Quality of contributions will be measured as the accuracy of the contributions made
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
To avoid contamination of our study, we will make the design public once the study has been completed.
Experimental Design Details
In order to test why certain types of people have a desire to contribute to science, and whether this desire can be increased through certain non-monetary incentives and research task modifications, we will run a natural field experiment on Zooniverse, the largest voluntary crowd science platform in the world. Specifically, we will post four actual scientific research projects on the Zooniverse platform for platform participants to assist with. The projects will all have the same scientific content but will vary in how they are presented to participants. These variations are described in detail below. The project will be to classify photos of rangelands taken in Northern Kenya as part of a large rangeland condition crowd-sourcing effort. Participants will not be aware that these projects are being used to investigate questions related to the economics of science in addition to the publicly stated objective of the projects. To eliminate concerns about participant selection into a particular project based on an experimental treatment, and to ensure participants are not aware that there are several versions of the same project (i.e., different experimental treatments), each version will be emailed to a randomly selected subset of Zooniverse participants who will be invited to contribute to the projects. Zooniverse will send these emails on our behalf to their population of users. The total population of users who will receive an email is 31,000. Each participant will receive one version of the project. We will control for participant characteristics by administering a short survey on participant age, gender, employment status, educational level, and career goals before they contribute to the project. Treatment Groups: Scientific Contribution Treatment: One explanation for voluntary contributions to science we will test in this project is that people may derive utility from the belief that they are contributing to a welfare enhancing public good (e.g., Bergstrom et al, 1986; Stiglitz, 1999). More specifically, they may volunteer their time to science because they derive a "warm glow" from participating actively in scientific discovery (Andreoni et al, 1996). To test this explanation, the scientific contribution of the research project will be emphasized in one of the project pages. Value of Labor Supply Treatment: A related explanation for voluntary contributions to science is that people believe scientific discovery is important, and that their labor supply is more valuable than the money they could donate to buy the equivalent contribution (Andreoni et al, 1996). In this explanation, volunteers may not receive a warm glow from the act of contributing, but rather, they may believe scientific discovery is important and that their labor supply is the best way they can contribute to it. To test this explanation, the value of volunteer labor supply in the project in terms of the amount of paid labor it is substituting for will be emphasized in one of the project pages. Control Group: The control group will be sent a version of the project with a basic description and with none of the treatments described above. References: Andreoni, James, et al. "Charitable contributions of time and money." University of Wisconsin–Madison Working Paper (1996). Bergstrom, Theodore, Lawrence Blume, and Hal Varian. "On the private provision of public goods." Journal of Public Economics 29.1 (1986): 25-49. Stiglitz, Joseph E. "Knowledge as a global public good." Global public goods 1.9 (1999): 308-326.
Randomization Method
Randomization done by crowd science organization using computer program
Randomization Unit
Individual contributors
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
31,000 individuals will be sent an email, we expect 3,100 will contribute based on uptake averages on the platform
Sample size: planned number of observations
31,000 individuals will be sent an email, we expect 3,100 will contribute based on uptake averages on the platform
Sample size (or number of clusters) by treatment arms
10,300 receiving the value of contributor output treatment, 10,300 receiving the value of contributor input treatment, 10,300 receiving the control page
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
To achieve power on the quality of output based on the pilot quality outcome measured as average agreement in responses across respondents, we need 699 classifications per project page. On our pilot, we achieved 630 classifications with 5,000 emails send out so we expect that with slightly over 10,000, we will achieve between 1,200 and 1,300 per page. The pilot control page average agreement was 60%, with a standard deviation of 0.114. With 699 classifications, we would need the treatment groups to achieve quality levels that differ from the control by 1.4 percentage points to achieve power of 90%.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
UCSD Human Research Protections Program
IRB Approval Date
2016-10-28
IRB Approval Number
Project #161424S
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers