Challenge statement
Challenge type: If you are working on multiple challenges, please indicate if this is your "big bet" or "exploratory" challenge.
Please note: we ask you to only submit a maximum of 3 challenges - 1x Big Bet, 2x Exploratory. Each challenge must be submitted individually.
EXPLORATORY
Challenge statement: What is your challenge? (Please answer in specific terms: "Our challenge is that...”.)
Our challenge is to continue encouraging the growth of citizen science in Argentina through a portfolio of research and development actions with different internal and external stakeholders.
Background: What is the history of your challenge? What is causing or driving it? Who is involved? How does the current situation look like? What undesired effects does it produce?
This challenge has been promoted since mid-2020 due to its significant growth since we started working with the air measurement pilot project with cyclists in the City of Buenos Aires, jointly carried out with the Ministry of Environment and Sustainable Development of Argentina, the Government of the City of Buenos Aires and Open-Seneca. Due to the potential of citizen science, an alliance was forged with the Argentine Ministry of Science, Technology, and Innovation (MINCYT, by its Spanish acronym) to map initiatives, whose initial focus was the environment, throughout the country. This line of action, which has already mapped more than 55 projects and continues to grow collaboratively, promoted the inclusion of this issue on the Ministry's agenda, which led to the launch of a National Citizen Science Program in 2022. Co_Lab experimented with two citizen science solutions with 4 local governments of the province of Buenos Aires: Mercedes, San Antonio de Areco, Balcarce, and Quilmes in partnership with AppEAR's team of scientists from the University of La Plata. The first experiment was an initiative to separate household waste and evaluate the effects on people's commitment and willingness to care for the environment. The second was an experience mapping aquatic ecosystems through an app, which collects georeferenced environmental data, co-created by the Lab PreseVamos.ar (WePreserve). Along the way, Co_Lab has published three specific knowledge products. The Lab has also organized more than six dissemination campaigns with these products and other content pieces, such as articles and blogs, which allowed us to reach a broader audience. In 2023, we plan to publish two other knowledge products and promote the growth of citizen science in Argentina through a portfolio of research and development actions.
Citizen Science represents an innovative tool to promote development since it helps to strengthen activism in the territories, influence the inclusion of new issues on the public agenda, promote evidence-informed public policies, facilitate the co-creation of innovative solutions, and raise awareness on an issue or underpin behavioral changes. It provides evidence for policy formulation and innovation to address problems, and it generates new information, everything with less effort from public officials. This information, generated by people with different backgrounds and interests, is more plural and diverse. The participatory nature of citizen science has very important governance implications. It allows citizens to express their opinions and points of view, giving policy-makers a more nuanced understanding of how they experience environmental issues.
We value the participatory construction of knowledge, which can include the scientific system in the process, but transcends it. Community knowledge represents a source of evidence. We can all be involved in building a sustainable future, powered by collective evidence. In addition, citizen science can become an instrument to promote awareness about certain issues and/or behavioral changes in people. Especially, we focused on doing a complete learning cycle with exploration of forefront topics and collective intelligence on these topics, mapping more than 55 citizen science projects addressing different thematic areas, and territories, among others. We also tested mapped solutions on two experiments to evaluate a hypothesis based on these solutions and scale them.
By working on citizen science, we wanted to bring the projects closer to decision-makers, highlighting the potential of collaborative, innovative, and economical data collection and analysis. We affirm that citizen science can provide inputs to public policy, and aimed to show it in an agile way.
Quantitative evidence: What (official) data sources do you have on this challenge that better exemplifies the importance and urgency of this frontier challenge? You can add text, a link, or a picture.
The following indicators stand out from the projects mapped in the first edition:
i) Over 15,000 people have participated or are participating in these initiatives,
ii) Although there are still no specific promotion mechanisms for these types of projects, the main financing source for the initiatives is the public sector through 3 government science and technology agencies and 8 national universities, and
iii) The most recurrent Sustainable Development Goals (SDGs) associated with these initiatives were Good Health and Well-being (21%), Sustainable Cities and Communities (19%), Life on Land (13%), and Quality Education (11%).
Link: https://www.undp.org/es/argentina/publicaciones/mapeo-de-soluciones-ciencia-ciudadana-argentina
Also, as part of the exploration, we found that in Argentina, there are more than 20 academics with extensive experience who actively work on citizen science projects with an emphasis on environmental and social issues.
Link:
https://www.undp.org/es/argentina/publicaciones/ciencia-ciudadana-una-exploracion-sobre-sus-tendencias-y-su-rol-en-el-desarrollo-sostenible
Results from a portfolio of experiments: https://www.undp.org/es/argentina/blog/simple-solution-complex-problem-citizen-science-environmental-policies-and-awareness
We conducted two experiments in which we tested two environmental citizen science solutions, which demonstrate the potential of this approach. The first was an initiative to separate household waste to evaluate its effects on the commitment and predisposition of people to care for the environment. Throughout the experiment, there were indications of a positive correlation between age, educational level, and the existence of pro-environmental behaviors in the participants prior to treatment. We found a positive relationship between the maximum level of education achieved and the environmental predispositions index before treatment, with a statistically significant correlation in participants with an incomplete graduate education, who had an index 21 points higher than the base category (incomplete primary). This coefficient is statistically significant at 10%. The fact that the effect of the correlation is smaller in the complete graduate category is worthy of attention, but since this coefficient is not statistically significant, the possibility that this result may arise from random effects cannot be ruled out. These results are in line with previous findings that indicate a positive correlation between pro-environmental behavior (Sharpe et al., 2021) and education (there are mixed findings in relation to education (Casaló Ariño & Escario, 2018; Hornsey et al., 2016)). We did not find statistically significant effects for age or gender. The variable that explains variation in the index with statistical significance is the decision to take part in the weighting experience. We found that volunteers that agreed to participate in the treatment had a value for the index 5 points greater than the ones who did not before treatment. This result is statistically significant at 5%. Therefore, it reinforces the theory that people with greater environmental awareness have a greater tendency to participate in citizen science experiences. Although there were no effects observed in the variation of post-treatment environmental engagement, this can be linked to the self-selection bias of the volunteers who participated. Unlike what was expected, the control group showed an increase in their environmental engagement. This increase may be related to the participation of both groups in a survey on environmental issues which, given the lower pro-environmental bias of the control group, could have had an effect in this regard. Another result suggests correlations between education, age, and the increase in post-treatment environmental engagement, but the evidence was not conclusive.
The second experiment was a crowdsourcing experience in aquatic ecosystems, using a mobile app that creates georeferenced environmental quality indicators. This sought to learn about the effects of citizen science on environmental governance, on increasing the quantity and quality of information obtained, and on promoting innovation in local environmental policies. In all three cities where the app was deployed, it helped collect valuable information about the state of their aquatic ecosystems. In addition, we obtained qualitative evidence of greater coordination across government areas to work on these policies. In the city where citizens took part in the mapping, the resulting data reflected a greater diversity of views and experiences on the natural environment. During the three weeks of the experiment, the app was downloaded 72 times, 61 persons signed up (including 4 from AppEAR), and it collected a total of 185 ‘reports’ among all municipalities. Civil servants from the three cities used the app to collect information, with similar results —51 reports for the ‘Control city’, and 61 for the Treatment 1 city. In Treatment 2, we observed a low app use by civil servants when compared to the other cities, explained by adverse weather conditions and the resignation of the Environment Area Director a few days prior to the start of the action. However, the final number of reports collected (60) was similar, thanks to the citizens’ engagement. The mean values for the environmental index obtained were 70.9 for the Control group, 79.4 for Treatment 1 (scientists and local officials), and 66.8 for Treatment 2 (all three actors). When we split these figures by user, it can be observed that both in Treatment 1 and 2 the average index produced similar results between scientists and local government officials. In Treatment 1, the average index value was 78.8 among local government officials and 85.2 among scientist users. In Treatment 2, this value was 76.0 for the first group and 77.1 for the second. When looking at the average index obtained by citizens, we can see that it is not only significantly lower (63.2) than the ones corresponding to the other types of users, but it also shows an increased variability, which could indicate that citizens have a more critical view of their environment on average, with widely differing perceptions.
These results point in the direction of citizens having a different perception of what constitutes a healthy natural environment, increasing the diversity of environmental data collected and its rigor. Next, in order to measure the effort needed to create the mappings, we evaluated the number of mappings done per capita in each city. The Control group had a mapping effort of 10.2 mappings per capita, while Treatment 1 had a value of 11.17. Treatment 2 showed the lowest value, with 2.91 mappings per capita. A Kruskall-Wallis test proved that the mapping effort was significantly different across all groups and that the involvement of citizenship in Treatment 2 lowered the effort needed to create useful evidence for the government by threefold (p-value< 0.05).
Qualitative evidence: What weak signals have you recently spotted that characterizes its urgency? Please provide qualitative information that better exemplifies the importance and urgency of this frontier challenge. You can add text, a link, or a picture.
During the exploration, relevant weak signals were spotted, such as: the use of artificial intelligence for greater speed and efficiency in the analysis of information, the use of gamification to encourage participation, and affordable low-cost and easy-to-develop sensors.
We made an effort to build knowledge from qualitative data extracted from the interviews and focus groups involving the key stakeholders engaged in the Citizen Science projects. We gathered data on air quality in one project using citizen science itself and created behavioral data as an output of one of our experiments.
During the solutions mapping, the qualitive qualitative evidence exhibited the following patterns regarding the motivations that drive people to participate in these projects: we believe that environmental issues are linked to people’s health and quality of life and that the implementation of citizen science projects is often coordinated, in practice, with educational communities. Other types of motivations are linked to the possibility of recording biodiversity, promoting conservation, or as a way of pursuing personal interests or claims that involve some type of activism. In terms of data, these projects enable us— through specific instruments— to collect data in a participatory manner and increase outreach; they use new technologies and allow access to data. In addition, they are based on collective construction and exchange. Hence, when the approach is local, participating communities are usually part of the research from the very definition stage of the research problem. The projects also often challenge people who are already working in the territories (from fishermen to professional photographers), and they are called upon to participate actively. These types of initiatives also usually include opportunities for exchange between scientists and the participating community. Moreover, the implementation of citizen science projects is not free of tensions and challenges associated with: trust building processes; diversity of interests that may arise in the same territory/community; the possibility of understanding each other and generating horizontal spaces; the necessary considerations when calling on citizens to collect data; high costs of developing and updating technology; the sustainability of participation; scientific evaluation systems; expectations linked to mediation, and evidence as a factor that does not necessarily ensure the design of informed public policies.
The qualitative information generated for the experiment focused on the preconditions of the municipalities, it is how they approached environmental policies and specifically aquatic ecosystems. To gather these data, we developed specific tools and guides for in depth interviews and gathered information from different local sources. We conducted in depth interviews with the responsible people of the environmental areas of eight municipal governments. We then selected three from this pool to conduct the experiment. Here is a summary of the results of the interviews and the complementary information for these three selected cities. The municipalities interviewed to be included in the PreserVamos (WePreserve) project have mentioned, in general, that they have similar environmental issues, such as urban solid waste management, the effects of flflooding in urban areas, green spaces, and natural reserves management, and industrial impact. Strategies for obtaining drinking water from groundwater, and recreational, touristic, sporting, and fishing uses of water bodies were also mentioned.
These are the lessons we draw from the experiments:
• The effects of citizen science vary according to different sociodemographic variables, such as age or educational level. This suggests that it would be better to adopt segmented strategies to harness all the potential of citizen science, directing them towards certain groups or allowing the groups to interact and encourage each other.
• Citizen science activities can shape the approach to the issues they address. In one of our experiments, the systematic approach to aquatic ecosystems provided an opportunity for greater coordination between different areas of government dealing with specific aquatic ecosystem issues.
• Citizen science encourages innovation in policies to take on their responsibilities in the care of aquatic ecosystems (duties shared with another level of government).
• The effort invested in developing user-friendly tools that allow citizens, with or without prior knowledge, to collect data leads to a high probability that these will be adopted and used by governments, regardless of citizen participation. Sharing these tools with governments can help them in their daily activities.
• Citizen science reduces the effort of governments to generate new data.
• The data collected by citizens is more diverse, as it reflects their concerns and experiences with the topic of the citizen science activity. As a result, this information provides governments with a better understanding of how these types of problems affect citizens and how they experience them.
• Citizen science is a mechanism for participation that citizens who usually do not participate can use. It provides governments with a different form of dialogue and mutual understanding to listen to citizens’ points of view and demands about the issue that the citizen science activity addresses, and also about other topics.
Value proposition: What added value or unique value proposition is your Accelerator Lab bringing to solving this challenge? Why is it your Lab that needs to work on this challenge and not other actors within UNDP, other stakeholders in the country respectively? Why is it worth investing resources to this challenge?
After working on this issue uninterruptedly, our AccLab has become a benchmark within the citizen science ecosystem at the national level and today is a strategic stakeholder in the growth of this type of participatory knowledge building. From our work, strategic opportunities are emerging. The following are highlighted below:
• Support the Government of the City of Buenos Aires to promote a Citizen Science Program in primary and secondary schools that involves instances of co-creation with the school community in its different projects through:
- The interaction among teachers, students, and stakeholders from the scientific and technological world.
- The implementation of training workshops for teachers, students, and technical assistants.
- The assessment of the adequacy of school curriculums for each educational level.
Three projects will be deployed in 69 schools with the following goals:
- Measure the city's air quality using diffusion tubes installed in schools strategically distributed throughout the city;
- Work on weather warning, monitoring, and forecast; risk knowledge; and communication and dissemination for the ownership of information on hydro-meteorological events that affect each neighborhood;
- Map the Earth's magnetic field using a program developed for mobiles.
• Develop a specific mapping line focused on ancestral knowledge as a continuation/expansion of the citizen science line with the Argentine Ministry of Science, Technology, and Innovation. We will probably try to identify traditional ecological knowledge.
• Participate in the Advisory Commission of the National Citizen Science Program. We expect these two key possibilities: i) be part of the evaluation commission of the call for citizen science projects, and ii) contribute to the design of the National Citizen Science Conference.
• Encourage the growth of citizen science mapping in the region. Progress is being made through conversations with the Perú AccLab in this regard.
• Publish two knowledge products. The first will be a paper titled “Environmental Citizen Science and its Effects on Participants, Governance, and Innovation. Evidence from two small-scale experiments” that compiles the findings of the two experiments carried out. The second is a document that will summarize the AccLab learning loop on citizen science and the portfolio of research and development actions, which first started with the air quality measurement project with cyclists.
Short “tweet” summary: We would like to tweet what you are working on, can you summarize your challenge in a maximum of 280 characters?
Co_Lab is part of a collective movement that develops citizen science in Argentina and promotes a portfolio of actions based on the lessons learned, from territorial actions to public policies. It’s the unusual suspects’ time to stand out.
Learning questions
Learning question: What is your learning question for this challenge? What do you need to know or understand to work on your challenge statement?
How to implement citizen science in the classroom? What type of experiences are best adapted to the method of didactic sequences with which teachers usually work? Is citizen science useful to promote scientific careers? Can science generate interest in STEM among girls and young women? Is citizen science helpful to encourage multidisciplinary integration? How is the interface between citizen science and ancestral knowledge in Argentina? How can the systematization of citizen science initiatives be promoted at the regional level?
To what stage(s) in the learning cycle does your learning question relate?
Grow
Usage of methods: Relating to your choice above, how will you use your methods & tools for this learning question? What value do these add in answering your learning question?
We will continue to map citizen science solutions and pay attention to traditional ecological knowledge solutions to create a specific chapter. In addition, we will carry out the Citizen Science in Schools pilot project. This pilot will work, in some way, as a prototype that may need adjustments as it is implemented. If it has a good result, we will advocate for the project’s growth.
Existing data gaps: Relating to your choice above, what existing gaps in data or information do these new sources of data addressing? What value do these add in answering your learning question?
From the beginning of this learning loop, we have been providing information in contexts where there was a void in terms of national production. In this sense, we were able to carry out a systematic initiative record that keeps growing and identifies both existing tensions and patterns, providing empirical evidence of the potential to address citizen science in local governments, among other issues. Through this record, the Lab is systematizing the lessons that citizen science can share in different contexts: Public policies, citizen engagement, etc.
4Quality education
11Sustainable cities and communities
13Climate action
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