Philosophy Contest: Write a Philosophical Argument That Convinces Research Participants to Donate to Charity

Can you write a philosophical argument that effectively convinces research participants to donate money to charity?

Prize: $1000 ($500 directly to the winner, $500 to the winner's choice of charity)

Background

Preliminary research from Eric Schwitzgebel's laboratory suggests that abstract philosophical arguments may not be effective at convincing research participants to give a surprise bonus award to charity. In contrast, emotionally moving narratives do appear to be effective.

However, it might be possible to write a more effective argument than the arguments used in previous research. Therefore U.C. Riverside philosopher Eric Schwitzgebel and Harvard psychologist Fiery Cushman are challenging the philosophical and psychological community to design an argument that effectively convinces participants to donate bonus money to charity at rates higher than they do in a control condition.

General Contest Rules

Contributions must be no longer than 500 words in length, text only, in the form of an ethical argument in favor of giving money to charities. Further details about form are explained in the next section.

Contributions must be submitted by email to argumentcontest@gmail.com by 11:59 pm GMT on December 31, 2019.

The winner will be selected according to the procedure described below. The winner will be announced March 31, 2019.

Form of the Contribution

Contributions must be the in the form of a plausible argument for the conclusion that it is ethically or morally good or required to give to charity, or that "you" should give to charity, or that it's good if possible to give to charities that effectively help people who are suffering due to poverty, or for some closely related conclusion.

Previous research suggests that charitable giving can be increased by inducing emotions (Bagozzi and Moore 1994; Erlandsson, Nilsson, Västfjäll 2018), by including narrative elements (McVey & Schwitzgebel 2018), and by mentioning an "identifiable victim" who would be benefited (Jenni & Loewenstein 1997; Kogut & Rytov 2011). While philosophical arguments sometimes have such features, we are specifically interested in whether philosophical arguments can be motivationally effective without relying on such features.

Therefore, contributions must meet the following criteria:

Text only. No pictures, music, etc. No links to outside sources.

No mention of individual people, including imaginary protagonists ("Bob"). Use of statistics is fine. Mentioning the individual reader ("you") is fine.

No mention of specific events, either specific historical events or events in individuals' lives. Mentioning general historical conditions is fine (e.g., "For centuries, wealthy countries have exploited the global south...."). Mentioning the effects of particular hypothetical actions is fine (e.g., "a donation of $10 to an effective charity could purchase [x] mosquito nets for people in malaria-prone regions").

No vividly detailed descriptions that are likely to be emotionally arousing (e.g., no detailed descriptions of what it is like to live in slavery or to die of malaria).

Nor should the text aim to be emotionally arousing by other means (e.g., don't write "Close your eyes and imagine that your own child is dying of starvation..."), except insofar as the relevant facts and arguments might be somewhat emotionally arousing even when coolly described.

The text should not ask the reader to perform any action beyond reading and thinking about the argument and donating.

The argument doesn't need to be formally valid, but it should be broadly plausible, presenting seemingly good argumentative support for the conclusion.

[ETA, Oct 28] Entries must not contain deception or attempt to mislead the reader.

If your argument contains previously published material, please separately provide us with full citation information and indicate any text that is direct quotation.

Choosing the Winner

Preliminary winnowing. We intend to test no more than twenty arguments. We anticipate receiving more than twenty submissions. We will winnow the submissions to twenty based on considerations of quality (well written arguments that are at least superficially convincing) and diversity (a wide range of argument types).

Testing. We will recruit 4725 participants from Mechanical Turk. To ensure participant quality and similarity to previously studied populations, participants will be limited to the U.S., Canada, U.K., and Australia, and they must have high MTurk ratings and experience. Each participant (except those in the control condition) will read one submitted argument. On a new page, they will be informed that they have a 10% chance of receiving a $10 bonus, and they will be given the opportunity to donate a portion of that possible bonus to one of six well-known, effective, international charities. If no argument statistically beats the control condition, no prize will be awarded. If at least one argument statistically beats the control condition, the winning argument will be the argument with the highest mean donation. See the Appendix of this post for more details on stimuli and statistical testing.

Award

The contributor of the winning argument will receive $500 directly, and we will donate an additional $500 to a legally registered charity (501(c)(3)) chosen by the contributor.

Unless the contributor requests anonymity, we will announce the contributor as winner of the prize and publicize the contributor's name and winning argument in social media and other publications.

Contributors may submit up to three entries if they wish, but only if those entries are very different in content.

Contributions may be coauthored.

All tested contributions will be made public after testing is complete. We will credit the authors for their contributions unless they request that their contributions be kept anonymous.

Contact

For further information about this contest, please email eschwitz at domain ucr.edu. When you are ready to submit your entry, send it to argumentcontest@gmail.com.

Funding

This contest is funded by a subgrant from the Templeton Foundation.

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APPENDIX

Stimulus

After consenting, each participant (except for those in the control condition) will read the following statement:

Some philosophers have argued that it is morally good to donate to charity or that people have a duty to donate to charity if they are able to do so. Please consider the following argument in favor of charitable donation.

Please read as many times as necessary to fully understand the argument. Only click "next" when you feel that you adequately understand the text. In the comprehension section, you will be asked to recall details of the argument.

The text of the submitted argument will then be presented.

After the reader clicks a button indicating that they have read and understood the argument, a new page will open, and participants will read the following:

Upon completion of this study, 10% of participants will receive an additional $10. You have the option to donate some portion of this $10 to your choice among six well-known, effective charities. If you are one of the recipients of the additional $10, the portion you decide to keep will appear as a bonus credited to your Mechanical Turk worker account, and the portion you decide to donate will be given to the charity you pick from the list below.

Note: You must pass the comprehension question and show no signs of suspicious responding to receive the $10. Receipt of the $10 is NOT conditional, however, on how much you choose to donate if you receive the $10.

If you are one of the recipients of the additional $10, how much of your additional $10 would you like to donate?

[response scale $0 to $10 in $1 increments]

Which charity would you like your chosen donation amount to go to? For more information, or to donate directly, please follow the highlighted links to each charity.

Against Malaria Foundation: "To provide funding for long-lasting insecticide-treated net (LLIN) distribution (for protection against malaria) in developing countries."

Doctors Without Borders / Médecins Sans Frontières: "Medical care where it is needed most."

Give Directly: "Distributing cash to very poor individuals in Kenya and Uganda."

Global Alliance for Improved Nutrition: "To tackle the human suffering caused by malnutrition around the world."

Helen Keller International: "Save the sight and lives of the world's most vulnerable and disadvantaged."

Multiple Myeloma Research Foundation: "We collect, interpret and activate the largest collection of quality information and put it to work for every person with multiple myeloma."

These charities will have been listed in randomized order.

After this question, we will ask the following comprehension question: "In one sentence, please summarize the argument presented on the previous page", followed by a text box. Participants will be excluded if they leave this question blank or if they give what a coder who is unaware of their responses to the other questions judges to be a deficient answer. Participants who spend insufficient time on the argument page will also be excluded.

Based on the submissions, we may add exploratory follow-up questions designed to discover possible mediators and moderators of the effects on charitable donation.

After consenting, participants in the control condition will read the statement:

Please consider the following description of the nature of energy. Please read as many times as necessary to fully understand the description. Only click "next" when you feel that you adequately understand the text. In the comprehension section, you will be asked to recall details of the text.

They will then receive a 445-word description of the nature of energy from a middle school science textbook. After clicking a button indicating that they have read and understood the description, a new page will open, and participants will read the following:

Some philosophers have argued that it is morally good to donate to charity or that people have a duty to donate to charity if they are able to do so.

After the reader clicks a button indicating that they have read and understood the statement, a new page will open containing the same donation question as in the argument conditions.

Statistical Testing

In an initial round, 2500 participants will each be assigned to read one of the twenty arguments. The five arguments with the highest mean donation will be selected for further testing. These five arguments will each be given an additional 350 participants, and 475 participants will be entered into the control condition. If none of the five arguments is statistically better than control, then we will announce that there is no winner. We will pool all 475 participants (minus exclusions) in each of the five selected argument conditions, then we will compare each condition separately with the control group by a two-tailed t-test at an alpha level of .01. If at least one argument is better than control, the award will be given to the argument with the highest mean donation.

Justification: Based on preliminary research, we expect a mean donation of about $3.50, a standard deviation of about $3, and clustering at $0, $5, and $10. In Monte Carlo modeling of twenty arguments with population mean donations in ten cent intervals from $2.60 to $4.50, the argument with the highest underlying distribution was over 90% likely to be among the top five arguments after a sample of 100 participants per argument (allowing 25 exclusions), and after 400 participants per argument (allowing 75 exclusions) the winning argument was about 85% likely to be one of the two with the highest underlying mean.

Given that we will be running five statistical tests, we set alpha at .01 rather than .05 to the reduce the risk of false positives. In preliminary research, McVey and Schwitzgebel found that exposure to a true story about a child rescued from poverty by charitable donation increased average rates of giving by about $1 (d = 0.3). Power analysis shows that an argument with a similar effect size would be 95% likely to be found statistically different from the control group at an alpha level of .01 and 400 participants in each group, while an argument with a somewhat smaller effect size (d = 0.2) would be 60% likely to be found statistically different.

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