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Field
Trial Start Date
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Before
March 08, 2017
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After
May 01, 2017
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Field
Trial End Date
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Before
May 08, 2017
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After
July 01, 2017
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Field
Last Published
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Before
April 24, 2017 12:21 PM
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After
April 24, 2017 12:53 PM
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Field
Intervention (Public)
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Before
Treatment Groups:
Scientific Recognition Treatment: One explanation for voluntary contributions to science is that that people want to be recognized in the scientific community. For instance, in a survey of crowd science contributors, one contributor wrote he/she contributes because “…[I] selfishly hop[e] that I will be the one to discover something completely novel” suggesting a desire to not just contribute but be recognized as a scientific discoverer. In the same survey, over half of contributors reported that they would contribute more to the platform if they had more communication with scientists. Existing evidence on the importance of scientific recognition for motivating discovery is weak, in part because of difficulties associated with people being forthcoming about these types of desires. By testing this in a field setting where contributors do not have to state the desire for scientific recognition, but rather respond to the opportunity to receive it, this treatment group will overcome the difficulty associated with honest self-reporting. To test this, one treatment will offer participants the chance to be acknowledged in an academic presentation on results of the research project. The page will specify that participants who make substantial contributions to the project will be mentioned in a conference presentation. This recognition will indicate to the participants and to the broader scientific community that participants have contributed to science.
Social Reputational Treatment: A second explanation for voluntary contributions to science is that people derive social rewards for doing so either within the voluntary science community or in their broader social networks (e.g., Rege & Telle, 2004; Wasko & Faraj, 2005). To test whether social rewards increase people’s willingness to contribute to science, one project page will have all contributors’ stats (i.e. number of contributions and amount of time spent contributing) posted on the page beside their usernames. In addition, users will be told that they can provide a link to the project from their Facebook account to make the social rewards associated with contributing more salient.
Scientific Framing Treatment: A third explanation for voluntary contributions to science that 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). This is separate from receiving recognition within the scientific community as this will test whether people are motivated by the science itself rather than the potential to be recognized for scientific discovery or for contributions to science. To test this explanation, the scientific contribution of the research project will be emphasized in one of the treatments.
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:
Bergstrom, Theodore, Lawrence Blume, and Hal Varian. "On the private provision of public goods." Journal of Public Economics 29.1 (1986): 25-49.
Rege, Mari, and Kjetil Telle. "The impact of social approval and framing on cooperation in public good situations." Journal of Public Economics 88.7 (2004): 1625-1644.
Stiglitz, Joseph E. "Knowledge as a global public good." Global public goods 1.9 (1999): 308-326.
Wasko, Molly McLure, and Samer Faraj. "Why should I share? Examining social capital and knowledge contribution in electronic networks of practice." MIS quarterly (2005): 35-57.
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After
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.
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Field
Intervention Start Date
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Before
March 08, 2017
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After
May 01, 2017
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Field
Intervention End Date
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Before
May 08, 2017
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After
July 01, 2017
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Field
Randomization Method
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Before
Randomization done by corwd science organization using computer program
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After
Randomization done by crowd science organization using computer program
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Field
Sample size (or number of clusters) by treatment arms
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Before
7,750 individuals control, 7,750 individuals scientific framing, 7,750 scientific recognition, 7,750 social reputational
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After
10,300 receiving the value of contributor output treatment, 10,300 receiving the value of contributor input treatment, 10,300 receiving the control page
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Field
Power calculation: Minimum Detectable Effect Size for Main Outcomes
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Before
Will update once pilot has been run
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After
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%.
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