Having a refined understanding of what leads people to participate is one of the main concerns of those working with citizen engagement. But particularly when it comes to participatory democracy, that understanding is only partial and, most often, the cliché “more research is needed” is definitely applicable. This is so for a number of reasons, four of which are worth noting here.
- The “participatory” label is applied to greatly varied initiatives, raising obvious methodological challenges for comparative research and cumulative learning. For instance, while both participatory budgeting and online petitions can be roughly categorized as “participatory” processes, they are entirely different in terms of fundamental aspects such as their goals, institutional design and expected impact on decision-making.
- The fact that many participatory initiatives are conceived as “pilots” or one-off events gives researchers little time to understand the phenomenon, come up with sound research questions, and test different hypotheses over time. The “pilotitis” syndrome in the tech4accountability space is a good example of this.
- When designing and implementing participatory processes, in the face of budget constraints the first victims are documentation, evaluation and research. Apart from a few exceptions, this leads to a scarcity of data and basic information that undermines even the most heroic “archaeological” efforts of retrospective research and evaluation (a far from ideal approach).
- The semantic extravaganza that currently plagues the field of citizen engagement, technology and open government makes cumulative learning all the more difficult.
Precisely for the opposite reasons, our knowledge of electoral participation is in better shape. First, despite the differences between elections, comparative work is relatively easy, which is attested by the high number of cross-country studies in the field. Second, the fact that elections (for the most part) are repeated regularly and following a similar design enables the refinement of hypotheses and research questions over time, and specific time-related analysis (see an example here [PDF]). Third, when compared to the funds allocated to research in participatory initiatives, the relative amount of resources channeled into electoral studies and voting behavior is significantly higher. Here I am not referring to academic work only but also to the substantial resources invested by the private sector and parties towards a better understanding of elections and voting behavior. This includes a growing body of knowledge generated by get-out-the-vote (GOTV) research, with fascinating experimental evidence from interventions that seek to increase participation in elections (e.g. door-to-door campaigns, telemarketing, e-mail). Add to that the wealth of electoral data that is available worldwide (in machine-readable formats) and you have some pretty good knowledge to tap into. Finally, both conceptually and terminologically, the field of electoral studies is much more consistent than the field of citizen engagement which, in the long run, tends to drastically impact how knowledge of a subject evolves.
These reasons should be sufficient to capture the interest of those who work with citizen engagement. While the extent to which the knowledge from the field of electoral participation can be transferred to non-electoral participation remains an open question, it should at least provide citizen engagement researchers with cues and insights that are very much worth considering.
This is why I was particularly interested in an article from a recently published book, The Behavioral Foundations of Public Policy (Princeton). Entitled “Rethinking Why People Vote: Voting as Dynamic Social Expression”, the article is written by Todd Rogers, Craig Fox and Alan Berger. Taking a behavioralist stance, the authors start by questioning the usefulness of the rationalist models in explaining voting behavior:
“In these [rationalist] models citizens are seen as weighing the anticipated trouble they must go through in order to cast their votes, against the likelihood that their vote will improve the outcome of an election times the magnitude of that improvement. Of course, these models are problematic because the likelihood of casting in the deciding vote is often hopelessly small. In a typical state or national election, a person faces a higher probability of being struck by a car on the way to his or her polling location than of casting the deciding vote.”
(BTW, if you are a voter in certain US states, the odds of being hit by a meteorite are greater than those of casting the deciding vote).
Following on from the fact that traditional models cannot fully explain why and under which conditions citizens vote, the authors develop a framework that considers voting as a “self-expressive voting behavior that is influenced by events occurring before and after the actual moment of casting a vote.” To support their claims, throughout the article the authors build upon existing evidence from GOTV campaigns and other behavioral research. Besides providing a solid overview of the literature in the field, the authors express compelling arguments for mobilizing electoral participation. Below are a few excerpts from the article with some of the main takeaways:
- Mode of contact: the more personal it is, the more effective it is
“Initial experimental research found that a nonpartisan face-to-face canvassing effort had a 5-8 percentage point mobilizing effect in an uncontested midterm elections in 1998 (Gerber and Green 2000) compared to less than a 1 percentage point mobilizing effect for live phone calls and mailings. More than three dozen subsequent experiments have overwhelmingly supported the original finding (…)”
“Dozens of experiments have examined the effectiveness of GOTV messages delivered by the telephone. Several general findings emerge, all of which are consistent with the broad conclusion that the more personal a GOTV strategy, the more effective. (…) the most effective calls are conducted in an unhurried, “chatty manner.”
“The least personal and the least effective GOTV communication channels entail one way communications. (…) written pieces encouraging people vote that are mailed directly to households have consistently been shown to produce a mall, but positive, increase in turnout.”
- Voting is affected by events before and after the decision
“One means to facilitate the performance of a socially desirable behavior is to ask people to predict whether they will perform the behavior in the future. In order to present oneself in a favorable light or because of wishful thinking or both, people are generally biased to answer in the affirmative. Moreover, a number of studies have found that people are more likely to follow through on a behavior after they predicted that they will do so (….) Emerging social-networking technologies provide new opportunities for citizens to commit to each other that they will turnout in a given election. These tools facilitate making one’s commitments public, and they also allow for subsequently accountability following an election (…) Asking people to form a specific if-then plan of action, or implementation intention, reduces the cognitive costs of having to remember to pursue an action that one intends to perform. Research shows that when people articulate the how, when and where of their plan to implement an intended behavior, they are more likely to follow through.”
(Not coincidentally, as noted by Sasha Issenberg in his book The Victory Lab, during the 2010 US presidential election millions of democrats received an email reminding them that they had “made a commitment to vote in this election” and that “the time has come to make good on that commitment. Think about when you’ll cast your vote and how you’ll get there.”)
“ (…) holding a person publicly accountable for whether or not she voted may increase her tendency to do so. (…) Studies have found that when people are merely made aware that their behavior will be publicly known, they become more likely to behaving in ways that are consistent with how they believe others think they should behave. (…) At least, at one point Italy exposed those who failed to vote by posting the names of nonvoters outside of local town halls.”
(On the accountability issue, also read this fascinating study [PDF] by Gerber, Green & Larimer)
- Following the herd: affinitive and belonging needs
“People are strongly motivated to maintain feelings of belonging with others and to affiliate with others. (…) Other GOTV strategies that can increase turnout by serving social needs could involve encouraging people to go to their polling place in groups (i.e., a buddy system), hosting after-voting parties on election day, or encouraging people to talk about voting with their friends, to name a few.”
“(…) studies showed that the motivation to vote significantly increased when participants heard a message that emphasized high expected turnout as opposed to low expected turnout. For example, in the New Jersey study, 77% of the participants who heard the high-turnout script reported being “absolutely certain” that they would vote, compared to 71% of those who heard the low-turnout script. This research also found that moderate and infrequent voters were strongly affected by the turnout information.”
- Voting as an expression of identity
“(….) citizens can derive value from voting through what the act displays about their identities. People are willing to go to great lengths, and pay great costs, to express that they are a particular kind of person. (….) Experimenters asked participants to complete a fifteen-minute survey that related to an election that was to occur the following week. After completing the survey, the experimenter reviewed the results and reported to participants what their responses indicated. Participants were, in fact, randomly assigned to one of two conditions. Participants in the first condition were labeled as being “above-average citizens[s] … who [are] very likely to vote,” whereas participants in the second condition were labeled as being “average citizen[s] … with an average likelihood of voting. (….) These identity labels proved to have substantial impact on turnout, with 87% of “above average” participants voting versus 75% of “average” participants voting.”
For those working with participatory governance, the question that remains is the extent to which each of these lessons is applicable to non-electoral forms of participation. The differences between electoral and non-electoral forms of participation may cause these techniques to generate very different results. One difference relates to public awareness about participation opportunities. While it would be safe to say that during an important election the majority of citizens are aware of it, the opposite is true for most existing participatory events, where generally only a minority is aware of their existence. In this case, it is unclear whether the impact of mobilization campaigns would be more or less significant when awareness about an event is low. Furthermore, if the act of voting may be automatically linked to a sense of civic duty, would that still hold true for less typical forms of participation (e.g. signing an online petition, attending a community meeting)?
The answer to this “transferability” question is an empirical one, and one that is yet to be answered. The good news is that while experiments that generate this kind of knowledge are normally resource intensive, the costs of experimentation are driven down when it comes to technology-mediated citizen participation. The use of A/B testing during the Obama campaign is a good example. Below is an excellent account by Dan Siroker on how they conducted online experiments during the presidential campaign.
Bringing similar experiments to other realms of digital participation is the next logical step for those working in the field. Some organizations have already started to take this seriously . The issue is whether others, including governments and donors, will do the same.
This is an excellent article. Do you think our view of participation is sometimes too narrow? It seems that we are always conceptualizing civic engagement in terms of its electoral and non-electoral forms, as if the electoral process has some type of talismanic significance. However, human beings have been “participating” throughout our entire evolutionary process. Perhaps if we want to promote greater civic engagement, we must first recognize that our primitive brains adapted for cooperation within groups and competition between groups. After all, much of the research here tacitly acknowledges this bias. Moreover, the political polarization and antagonistic debates of our culture wars all seem to trace back to this tribal mentality in some way. Perhaps the future of civic engagement is not found in leveraging these primitive biases but rather exposing them and transcending them.
Thanks a lot for your feedback. I think the conceptual distinction is not in terms of making any value judgement (e.g. electoral x non-electoral). Personally, I prefer to see the distinction between different types of participation merely as a way to enable analytical work while ensuring that we are not comparing apples to oranges. Thanks again and happy new year!
I have the same questions, and in fact I am working with a university research group to evaluate the impact of open data initiatives. Your article has good links on the subject that I will read next, but since I’m here I wanted to ask you for more information on these kind of studies, whether it’s theoretical framework, field notes, research papers or presentations.
The issue I’m trying to decide right now is the scope of the study I should propose: Focus on one or a couple of initiatives and evaluating their usability and effectiveness or doing a broader (but shallower) study on all the available sites and their success stories.
Hi Martin, on the issue of the scope, I think it all depends on your research question: the research question should define the method and not vice-versa. In any case, make sure you are coming up with a good case selection method (e.g. most similar systems design x most different systems design). On the literature, again, I would need to have a clearer idea of what the question is. Thanks a lot for your comment!
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