Mini Lit Review: Civic Technology and Trust in Government

(Spoiler: It’s complicated and unclear, but there’s stuff we can learn and fix.)

Trust is all the rage these days, in large part because it seems to be a vanishing commodity. And in response, there’s suddenly a lot of interest in whether things like civic technology, open government and e-participation can help (I’ll use civic tech for inclusive shorthand, per usual).

Much of the discourse has been anecdotal or editorial (OGP, 2017), and there’s no obvious evidence base. Even OECD’s work, thorough as ever, coupling rigorous policy explication with a sharp methodological approach, doesn’t present strong evidence for civic tech’s effect on trust in government (Trust and Public Policy: How Better Governance Can Help Rebuild Public Trust, 2017).

So I thought I’d look into it. Here’s a quick and informal review of the literature on civic tech (inclusive) and trust in government. Note that though several studies position trust as a pre-condition for meaningful civic technology (Mcgee et al., 2018; Sieber and Johnson, 2015), this mini-lit review is about trust as an outcome, not an input.

So firstly, as is often the case, there’s some measurement problems.

What are we even talking about? (concepts and measurement)

To begin with, the independent variable here is fuzzy and amorphous. Civic tech, open government, e-participation, tech for accountability, policy informatics—these things overlap and self-identify in weird and confusing ways, both as communities of practice and as fields of study. It’s confusing inside of each one too. Open government is wildly open to interpretation (Francoli and Clarke, 2014; Gonzalez-Zapata and Heeks, 2014; Pomerantz and Peek, 2017), civic tech can’t seem to decide who’s in and who’s out, and e-participation doesn’t seem sure whether it’s really a field (Susha and Grönlund, 2012).

This ambiguity is exacerbated by the fact that project modalities mobilize people and information in such wildly different ways. Is it really possible to say anything general about civic tech and technology that will apply equally to an SMS platform for parliamentary monitoring in Uganda, a US government data science competition, and open contracting in Ukraine? Maybe. Maybe not.

The dependent variable might be even messier. We talk about trust as though everyone agrees on what it is, but you don’t have to scratch far beneath the surface to find that this isn’t the case. Lots of ink has been spilled trying to figure out how to understand trust. One literature reviews tracked 16 different definitions used by scholars (Petts, 2008: 823).

There are some common distinctions, however. Generally, researchers distinguish between inter-personal trust that is interaction-based, and systemic trust, that is institutional-based. There’s much more research on the former than on the latter (Bachmann et al., 2015), though the majority of research inter-personal trust former lacks a governance component. Even otherwise prominent institutional contexts like deliberative and participatory approaches to government decision-making are significantly under-researched compared to the attention paid to trust within communities and the marketplace (Petts, 2008: 822).

This research gap might be less problematic than it first appears though, since the distinction between interaction-based and institutional-based trust isn’t as clear as it first appears. Bachmann and Inkpen’s (2011) work on private sector institutions suggests that “institutional-based trust may generally be seen as a weaker form of trust compared to interaction-based trust,” but that it’s cheaper to generate and pretty much works the same way, by creating “shared explicit and tacit knowledge” between parties (285). Information is the mechanism at play here. So while the interactions are differently structured and actors differently positioned in these two types of trust relationships, in both instances trust is built by securing the information necessary to anticipate outcomes.

Academic scholars of transparency and accountability have emphasized the role of information in trust-building somewhat differently, arguing that civic tech initiatives boost trust because they provide citizens with information, without which citizens would misunderstand about what government does, leading to distrust (Porumbescu, 2015: 822). While that’s hypothetically plausible, it will ring false to most practitioners working on transparency and accountability issues, where trust will often be conceptualized more readily as a byproduct of government’s performance and responsiveness (OGP, 2017).

This more normative understanding of trust finds purchase in OECD’s work on the issue, which conceptualizes trust as driven by perceptions about government values and competence (Trust and Public Policy: How Better Governance Can Help Rebuild Public Trust, 2017). It also resonates with the focus some scholars have placed on process over the content of citizen-state interactions for trust-building (Bloomfield et al., 2001: 510; Petts, 2008: 822-823), and recommendations that governments “enhance trust among the public […] via civic engagement and closing the public–police disengagement gap” (Warren et al., 2014: 291; see also Morgeson et al., 2011). It does not, however, account for increasing evidence that at least in some countries, information and values get trumped by the definitive power of political partisanship and social identity as drivers of trust (Wilkes, 2015).

In any case, there are a lot of ways to conceptualize trust in government. But even if there were conceptual agreement, operationalizations of trust in government are just as diverse. The OECD has mapped out a host of international methods, and makes it clear that  survey instruments vary significantly in both measures and wording (Trust and Public Policy: How Better Governance Can Help Rebuild Public Trust, 2017: 152-158). Some avoid trust altogether and backpedal to individuals’ “predisposition to trust” (Grimmelikhuijsen and Meijer, 2014). It’s a jungle out there.

Perhaps the only safe thing to say is that it’s complicated. But then again, I’ve found only one operational and multi-dimensional measure for trust in a governance context (Grimmelikhuijsen and Knies, 2017). So there’s work to do mapping that terrain.

So what do we know? (evidence)

Does it work?

There is some evidence of civic tech having a positive influence on trust in government, though most results are mixed. In regard to government transparency and information release, for example, Hong (2013) cites several studies to support her claim that

those individuals who use government websites are more likely to perceive the government as transparent and open to citizen monitoring, responsive to citizens’ input, and accessible and accountable to citizens (349),

while Grimmelikhuijsen et al.’s (2013)’s comparative study of South Korea and the Netherlands findings that government transparency negatively affects trust (though in national context plays a definitive role in moderating this effect).

The evidence for interaction over social media and government websites is even more complicated.   Warren et al.’s (2014) survey of Malaysians who interact with government over social media (n=502) finds positive correlation between the online coordination of civic activities and citizens’ propensity for trust in government. Porumbescu’s (2016) survey of South Koreans (n=1100) finds that use of government websites and social media positively affects trust in government, but notes a difference in effects between platforms. He suggests that the simple information often shared over social media is more effective in building trust than transactional exchanges on government websites, and in a later analysis (2017) finds that e-gov websites only effect is a negative effect on “perceptions of trustworthiness [among] those who exercise voice more frequently” (530).

Hong’s (2013) survey (n=+2000, USA) also finds a positive correlation with interaction through both social media and e-government, but distinguishes the effects of  each platform on trust in different levels of government. Specifically, she finds that

informational online services and social media were associated with greater trust in government at the local and state levels, while those [e-government platforms] with transactional online services conveyed greater trust in the federal government,

(though she notes that all in all, “successful experience with the channels was more important than the experience itself”) (346).

This differential is contradicted by a number of studies on e-government that document a positive effect on trust in local government, including Tolbert and Mossberger’s (2006) widely cited survey of e-gov users in the US (n=815) and Morgeson et al.’s (2011) US-based study (cross-sectional sample of 787 e-gov end users).

So yeah, the evidence is clearly mixed. And while it’s tempting to attribute this to a limited scope of countries and research objects (e-gov, transparency and social media), it might have more to do with some of the measurement problems discussed above. Mixed evidence is present in individual studies as well (Grimmelikhuijsen et al., 2013; Welch et al., 2004) after all, and Tolbert and Mossberger (2006) note how scholars have drawn contradictory conclusions from the same survey data on trust and e-government (358).

As such, it’s not surprising to find that caveats and limitations are prominent in many of these studies. For many researchers, they take center stage. One of the key findings from the 4 ½ year Making All Voices Count program, for example, which included more than 120 research and learning publications, is that “technologies alone don’t foster the trusting relationships needed between governments and citizens, and within each group of actors”(Mcgee et al., 2018).

The project’s synthesis report notes “a limited range of conditions” under which technologies were leveraged in MAVC projects to “enable trust-building between citizens and the state,” and references three such projects that used sustained and structured interaction with authorities over SMS and mapping technologies to build trust. The report fails to spell out precisely what those conditions are, however, or to provide any structured data from which to assess the claim (Mcgee et al., 2018: 18-19).

Drivers and contributing factors

When considering factors that drive or moderate the effect of civic tech on trust, academic studies often emphasize individuals’ personal perspectives and pre-dispositions. An online experiment by Grimmelikhuijsen and Meijer (2014), for example, finds that transparency’s effect on trust is moderated by individuals’ predispositions to trust and prior issue knowledge, while Porumbescu (2017) finds that e-government use exacerbates distrust among the politically engaged, and Åström et al.’s (2016) survey of Swedish e-petition users  (n= 1,470 ) finds that engagement with e-petitioning systems does not increase trust generally, but that for users who already consider themselves removed from politics, it reinforces distrust.

Of course, individuals’ experiences interacting with government and civic technology is also important. Hong (2013) finds that user experiences of tech platforms matter more for trust in government than the interactions those platforms facilitate (346), and longitudinal evaluations of participatory budgeting initiatives show trust in those initiatives decreasing with dissatisfaction in the initiative’s own performance (Barros and Sampaio, 2016).

These experiences, moreover, will inevitably be influenced just as much by contextual factors occurring external to those interactions, and this may be particularly elusive in a developing country context. As Mcgee et al. (2018) note, when citizen-state interactions in the MAVC portfolio succeeded in building trust, they relied on experienced intermediaries, and “it was the repeated interactions and behaviours that made the difference – and these were largely offline” (Mcgee et al., 2018: 18-19).

There is, in any case, little research on how the design of civic technology initiatives influences their effect on trust in government. This may be due to a lack of attention to civic technology generally. Indeed, a cross-disciplinary literature review highlights seven drivers of trust in public administration (govt effectiveness, policy consistency, etc) and makes no mention of technology or information exchange (Hamm et al., 2016), though it does reference a study suggesting that “trust in government tends to be promoted under certain institutional designs such as those that include citizen participation mechanisms” (Mizrahi et al., 2009).

Again, when asking why there is so little evidence on how the programmatic design of civic tech influences trust in government, it’s hard not to notice how little research there is on civic technology at all, and how hard it would be to compare civic tech initiatives and their effects across contexts.

So what does it mean? (implications)

This lit review is brief, informal and unsystematic. Yet it is still possible to draw some tentative conclusions about the evidence base and what it means.

1. There is no clear or consistent evidence that civic technology, open data, e-participation or citizen-state interaction writ large have a positive impact on citizens’ trust in government.
2. Variations in contexts and programmatic modalities are likely to make evidence for such broad claims impossible.

No clear evidence is the main headline here, but this doesn’t necessarily suggest pulling the plug on anything. Absence of evidence is not evidence of absence. There may indeed be a strong relationship and even a consistent causal effect between civic tech and trust that simply hasn’t been measured yet, due to all the complicated methodological and conceptual issues mentioned above. To meet this challenge, future research should be deliberate about a few things.

3. Address the breadth and ambiguity in scholarly literature. Don’t pretend there is clarity or consensus when there’s not. That does no one any favors.
4. Move beyond research on transparency portals, social media interactions and e-gov websites. Pursue research in a wider variety of country contexts and test for moderation effects.
5. Pursue research objects defined by the structure of interactions and information exchanges that they facilitate, not according to whether they enjoy e-participation, civic hacking, or open data labels.
6. Apply quant, qual or mixed methods deliberately. There’s a lot of survey data and associated analysis out there already, and applying qual methods to this work could usefully complicate and clarify their mixed results. Qualitative studies of cases without a demonstrated systematic effect might be less useful. If quant is your bag, don’t be afraid to utilize existing data sources, there are oodles of survey data on trust (see the OECD appendix), whose incorporation might strengthen the external validity of discrete studies.

Lastly, it’s possible to read some strategic lessons for program design and practical work out of the above. Inferences from parallel research or inconclusive studies can complement on-the-ground contextual information, and help to inform the design of practical initiatives.

7. Information that influences expectations is likely the primary mechanism by which trust is built through civic technology.
8. Differences between tech platforms matter, but the structure of interactions they facilitate likely matters more.
9. Negative experiences with technology and user interfaces can negatively influence trust outcomes in civic tech.
10. You can’t escape populism and social identity. Anticipate how users self-identity and try to build their predispositions into trust-building efforts.

References

As always, let me know if you need help getting copies to any or all of these.

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Bachmann R and Inkpen AC (2011) Understanding institutional-based trust building processes in inter-organizational relationships. Organization Studies 32(2): 281–301.

Bachmann R, Gillespie N and Priem R (2015) Repairing Trust in Organizations and Institutions: Toward a Conceptual Framework. Organization Studies 36(9): 1123–1142.

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