Introduction on four main modes of participation

Citizen Science (CS) is built on a consistent principle: the active involvement of the public in scientific research. However, what counts as Citizen Science can vary widely depending on the context. Projects labeled as CS may employ different research approaches and modes of engagement, drawing inspiration from practices such as community-based participatory research, “street-science” (Corburn, 2005), popular epidemiology (Allen, 2003), community-engaged research (Israel et al., 2010), or consensus conferences (Guston, 1999). While these approaches differ in method, they all share common ground with CS in creating opportunities for meaningful social change.

To better understand how citizens can participate in science, Haklay (2013) proposed a framework with four levels of engagement:

1. Crowdsourcing – Citizens mainly act as contributors of information or data. For example, participants might record bird sightings or upload photos of local species.
2. Distributed Intelligence – Citizens are involved in interpreting or classifying data, often with guidance from experts. A well-known example is volunteers helping to identify galaxies in astronomical images.
3. Participatory Science – Citizens collaborate more deeply, taking part not only in data collection but also in shaping research questions and defining the problems under study.
4. Strongly Participatory Science – Citizens lead the process: they define the problem, collect and analyze data, and use the findings to advocate for change.

These levels reflect increasing degrees of citizen empowerment and ownership of knowledge production. Each mode offers distinct opportunities for generating knowledge, but their potential differs, especially in contexts where science and policy intersect.

Scholar Barbara Allen (2017, 2018) has emphasized that “extreme” or strongly participatory forms of Citizen Science can be particularly powerful in contested or urgent situations. In her participatory studies of two polluted towns in southern France, citizens worked alongside researchers to investigate local health problems. This full-spectrum involvement – defining the research, collecting data, and analyzing findings – resulted in actionable knowledge that gave citizens a stronger voice. The outcomes not only informed public understanding but also empowered residents to advocate for environmental change, prompting institutions to respond.

This case highlights an important lesson: the depth of citizen participation directly influences the kind of knowledge produced and its potential to drive real-world impact. By situating science within the lived experiences of communities, Citizen Science at its highest level fosters robust, context-sensitive knowledge that can shape both social and environmental futures.

References

Allen, B. L. (2003). Uneasy alchemy: Citizens and experts in Louisiana’s chemical corridor. MIT Press.

Allen, B. L. (2017). Participatory research and environmental health justice: Lessons from community-based studies in southern France. Environmental Justice, 10(4), 115–124.

Allen, B. L. (2018). Citizen science and the co-production of actionable knowledge. Science, Technology, & Human Values, 43(6), 1012–1035. https://doi.org/10.1177/0162243918759560

Corburn, J. (2005). Street science: Community knowledge and environmental health justice. MIT Press.

Guston, D. H. (1999). Evaluating the first U.S. consensus conference: The impact of the citizens’ panel on telecommunications and the future of democracy. Science, Technology, & Human Values, 24(4), 451–482. https://doi.org/10.1177/016224399902400402

Haklay, M. (2013). Citizen science and volunteered geographic information: Overview and typology. In D. Sui, S. Elwood, & M. Goodchild (Eds.), Crowdsourcing geographic knowledge (pp. 105–122). Springer.

Israel, B. A., Eng, E., Schulz, A. J., & Parker, E. A. (2010). Methods in community-based participatory research for health (2nd ed.). Jossey-Bass.