Changing What Counts
HOW CAN CITIZEN-GENERATED AND CIVIL SOCIETY DATA BE USED AS AN ADVOCACY TOOL TO CHANGE OFFICIAL DATA COLLECTION?
Jonathan Gray, Danny Lämmerhirt and Liliana Bounegru
In this report, we have looked at how citizens and civil society groups can generate data as an advocacy tool to influence institutional data collection practices. In this final section, we discuss (i) the question of citizen-generated and civil society vs. institutional data; (ii) technologies, methods and strategies for changing what counts; and (iii) risks and limitations; before concluding with (iv) recommendations for civil society organisations, public institutions, policy-makers, funders and others.
Citizen-generated data and civil society data can be used to articulate alternative conceptions of what matters and how things should be organised, optimised and resourced.
Although often created in response to the perceived gaps or limitations of official information, data generated by citizens and civil society groups is often created without an explicit intention to try to influence institutional data collection practices. In some cases, the goals for which these citizen-generated and civil society data infrastructures have been established may be better served if they continue to operate independently from public institutions – whether because of concerns around privacy, surveillance, censorship, manipulation, corruption or repression or simply in order provide alternative perspectives and insights, be they competing or complementary. Sometimes, it may be desirable for civil society as opposed to the public sector to undertake data collection activities.
However, in other cases, securing changes in what and how public institutions count can be a powerful way for civil society groups to obtain official recognition and resources for their issues and concerns. In such cases, citizen-generated and civil society data can be a valuable tool to advocate for changes in what is counted. Citizen-generated and civil society data collection practices can be used to contest, challenge, augment and enrich ways of seeing and ways of knowing that are inscribed within public data infrastructures – including through official practices of counting, classifying, calculating, measuring, mapping, monitoring and evaluating 1
. Extra-institutional data can thus be used to open up space for democratic deliberation between public institutions and civil society actors around the scope, focus and priorities of public data systems – as well as how they might be adjusted, recalibrated and reoriented in accordance with different methods or matters of concern. Citizen-generated and civil society data can be used to articulate alternative conceptions of what matters and how things should be organised, optimised and resourced.
Of course, if changes in official data collection are secured, this does not necessarily imply citizen-generated and civil society data collection should discontinue. Sometimes, if changes are successfully institutionalised, this may obviate the need for data from civil society. In other cases, it may remain valuable to have an additional independent source of data, which might, for example, be combined with other sources of information, bring different kinds of insights or be used for the purposes of comparison with or verification of official data.
In the case studies above, we surveyed how civil society actors had mobilised a broad repertoire of different approaches for using data they had generated in order to change what public institutions count. This included drawing on a wide range of technologies and methods in order to generate this data, including:
These citizen-generated and civil society data collection practices have led to various forms of engagement with public institutions about changing official data collection. Civil society groups in our case studies were successful in eliciting several different kinds of responses from public institutions, including:
The projects featured in this report might serve to inform the development of civil society strategies to influence public data collection. For example:
Advocating for changes in official data collection may not be as straightforward as collecting data independently. It may come with a whole host of uncertainties and risks. Here, we briefly recount a few of the risks and limitations that came up in the course of our studies and interviews.
Some public institutions may have an incentive either not to collect data or not to invest in accurate, comprehensive or timely data collection. For example, in our case studies above, it was noted that institutions in the US systematically under-reported on police killings. European border authorities consider migration deaths beyond their remit of preventing illegal migration.
In cases where citizen-generated and civil society data collection processes have been established in order to contest the agendas of current governance structures, they may need to address the misalignments between their objectives and official policy before their efforts can be officially recognised. While the strategy of using data that is “just good enough” proved successful in at least one of our case studies, in other cases the methodological differences between civil society and public institutional data collection practices may hinder official acceptance.
In some regions and countries, undertaking independent data collection activities may be risky or even illegal. Citizens and activists may risk attracting unwanted attention from public authorities or even fines or imprisonment for their activities. Independent data collection activities may be more difficult in environments with weaker protections for human rights, freedom of expression and independent civil society, or in countries where corruption, clientelism and political persecution are rife. In such environments, digital data collection tools may leave traces that governments could use to identify, track or target individuals or groups associated with activities considered problematic.
Finally, different aspects of the projects examined above will be more or less replicable in different contexts. Contingent external factors at work in the case studies above – whether political, economic, cultural, social, legal or otherwise – should not be underestimated. In some cases, high-profile public controversies increased pressure on institutions to take action (e.g. El Indultómetro, The Counted). In other cases, citizen-generated and civil society data collection activities were strongly aligned with the prerogatives of international development programmes, which likely increased support from local, national and international institutions (e.g. Uwezo and WaterAid).
On the basis of our case studies, interviews and consultations with our reference group (listed in the acknowledgements section), we propose the following recommendations.
We suggest civil society actors who are interested in influencing the data collection practices of public institutions:
We suggest public institutions, policy-makers and funders interested in making public data infrastructures more responsive to the concerns of civil society actors:
Support further research and the development of resources in this area that can be used to make public data infrastructures more responsive to the interests and concerns of civil society.