Challenging dimension of actionable knowledge: legitimacy, credibility and uncertainty

The use of knowledge to produce change is a central concern in contemporary public life and politics. Rising environmental conflicts, eco-social crises, and the current “crisis of truth” intersect with political polarization and widespread disinformation, making the effectiveness of actionable knowledge from Citizen Science (CS) projects increasingly dependent on legitimacy. Legitimacy goes beyond traditional measures such as data accuracy, consistency, accessibility, or timeliness. Instead, it emerges from the interplay of technical, ethical, social, and political factors.

STS scholar Noortje Marres (2018) emphasizes that the concept of “fact” is evolving in contemporary societies. In an era of post-truth, restoring authority alone is insufficient to secure the role of facts in public debate. Instead, knowledge democracy requires that experimental validation of knowledge happens in the public domain, allowing truth claims to be evaluated through shared engagement rather than hierarchical authority. This approach challenges conventional norms and recognizes that authority-based validation alone can reproduce existing power imbalances, legitimizing some knowledge while marginalizing other perspectives.

The concept of cognitive justice (Visvanathan, 2005) addresses this imbalance, highlighting the dominance of Western scientific knowledge and advocating for recognition of diverse ways of knowing, including local, indigenous, and experiential knowledge systems. Similarly, the idea of testimonial injustice (Fricker, 2007) draws attention to how credibility can be unfairly downgraded due to identity-based prejudice, excluding certain voices from knowledge production. Building on these ideas, Barbara Allen (2018) proposes knowledge justice, which seeks to ensure that marginalized communities have access to and participate in the co-production of relevant scientific and technical knowledge. Producing rigorous, locally relevant science with affected communities strengthens claims and empowers citizens in the face of powerful institutional or corporate actors.

Alongside legitimacy and credibility, uncertainty is another defining dimension of actionable knowledge. The concept of post-normal science (Functowicz & Ravetz, 1993) acknowledges that uncertainty is inherent in complex, high-stakes, and value-laden issues, especially in environmental and health contexts. Post-normal situations are characterized by:

• Uncertain facts – no scientific test is perfect; errors are unavoidable, and interpretations depend on the policy context.
• Values in conflict – actors weigh sustainability and social factors differently, creating contested priorities.
• High stakes – decisions have significant consequences for communities, ecosystems, and policy directions.
• Urgency – timely decisions are needed without worsening problems or missing opportunities.

Instead of ignoring uncertainty, post-normal science proposes extended peer communities (Battaglia et al., 2009) to engage a broader circle of stakeholders in knowledge evaluation. These communities, including citizens’ juries, focus groups, or consensus panels – allow for plural perspectives to contribute to knowledge production, ensuring it is socially robust and relevant.

Both Marres’ concept of knowledge democracy and the post-normal science approach converge on the principle of public and plural legitimacy. These frameworks recognize science as contextual, value-sensitive, and inherently complex, moving away from the notion of objective, value-free knowledge.

One of the main strengths of actionable knowledge in Citizen Science (CS) is its potential to influence policymaking and regulation. However, this potential is often challenged by a central issue: uncertainty. Policymakers generally seek data with a high degree of certainty (Durham et al., 2014), while knowledge co-produced with or by citizens may carry multiple layers of ambiguity. Skepticism often arises from concerns about data quality.

Yet, what counts as “quality” is not the same for all stakeholders. For example, it can mean validity, consistency, accuracy, completeness, timeliness, or adherence to standards (Balázs et al., 2021). To address these concerns, researchers have developed various sociotechnical strategies to enhance credibility:

• Peer verification (review by qualified peers within the domain),
• Expert verification (validation by designated experts),
• Automatic quality assessment (software or AI-based tools),
• Model-based assessments (a combination of expert judgment and algorithmic filters).

Uncertainty is also central when CS-generated knowledge is used in legal disputes. Brett (2017) examined the role of volunteer water monitoring data in Florida. While the Environmental Protection Agency (EPA) gradually accepted such data under the Clean Water Act, courts were more skeptical – mainly due to doubts about the “expertise” of citizen scientists. Brett argued that citizens, when demonstrating methodological rigor and long-term engagement, can indeed qualify as experts under certain legal standards.

A powerful illustration of this comes from the Formosa case (Berti Suman & Schade, 2021). In 2019, residents and fishers in San Antonio Bay, Texas, sued the Formosa Plastic Corporation for violating the Clean Water Act. Their evidence –12,000 photos and videos of pollution collected over years – was accepted in court. Supported by expert testimonies, this citizen-produced dataset proved decisive, leading to a legal victory. Here, simple, systematic, and persistent monitoring transformed uncertainty into a strong case for justice.

These examples highlight that uncertainty is not merely a limitation; it is a transversal factor shaping the impact of actionable knowledge. It can be addressed through credibility-building strategies, but it must also be understood, communicated, and embraced.

In this regard, insights from environmental and health (EH) literacy are useful. Research shows that non-experts often struggle with uncertainty, preferring absolute explanations that can distort risk perception (Bonaccorsi & Lorini, 2021). The ability to navigate uncertainty depends on previous experiences, emotional context, level of engagement, and perception of risk. Thus, effective communication of uncertainty requires developing both cognitive and social skills, building trust without disorienting stakeholders.

Epidemiologist Liliana Cori (2021), drawing on her experience with CS projects in Italy, suggests fostering a “sensitivity to uncertainty” through participatory activities such as seminars and dialogues with stakeholders. Importantly, uncertainty should not be communicated through a vertical model of knowledge transfer, where experts “deliver” knowledge to passive audiences. Instead, following Functowicz and Ravetz’s (1993) notion of post-normal science, Cori emphasizes a horizontal, dialogic approach—transparent, inclusive, and circular.

By engaging citizens and institutions in this way, uncertainty becomes not an obstacle but a resource for trust, co-production of knowledge, and improved decision-making. Far from undermining credibility, embracing uncertainty can strengthen both the scientific and social impact of Citizen Science.

In summary, for actionable knowledge to be effective in complex situations, it must be socially robust:

• Plurally produced, incorporating diverse perspectives and experiences.
• Context-sensitive, tailored to local realities and socio-political dynamics.
• Explicit in its values, acknowledging conflicts and trade-offs.
• Able to confront and manage uncertainty, rather than ignoring it.

By attending to legitimacy, credibility, and uncertainty, Citizen Science can ensure that knowledge is not only produced but also trusted, relevant, and capable of driving meaningful change.

References

Allen, B. L. (2018). Strongly participatory science and knowledge justice in an environmentally contested region. Science, Technology, & Human Values. https://doi.org/10.1177/0162243918758380

Balázs, B., Mooney, P., Nováková, E., Bastin, L., & Jokar Arsanjani, J. (2021). Data quality in citizen science. In K. Vohland et al. (Eds.), The science of citizen science (pp. 123–138). Springer. https://doi.org/10.1007/978-3-030-58278-4_8

Battaglia, R. (2021). Diritti di cittadinanza scientifica. In A. Cori et al. (Eds.), Comunicare ambiente e salute. Aree inquinate e cambiamenti climatici in tempi di pandemia. Edizioni ETS.

Berti Suman, A., & Schade, S. (2021). The Formosa case: A step forward on the acceptance of citizen-collected evidence in environmental litigation? Citizen Science: Theory and Practice, 6(1), 16, 1–13. https://doi.org/10.5334/cstp.367

Bonaccorsi, G., & Lorini, C. (2021). L’alfabetizzazione sanitaria e la comunicazione dell’incertezza. In A. Cori et al. (Eds.), Comunicare ambiente e salute. Aree inquinate e cambiamenti climatici in tempi di pandemia. Edizioni ETS.

Brett, A. E. (2017). Putting the public on trial: Can citizen science data be used in litigation and regulation? Villanova Environmental Law Journal, 28, 163–190. https://digitalcommons.law.villanova.edu/elj/vol28/iss2/1

Cori, L. (2021). Cittadini e scienza, dalla consultazione alla coproduzione. In A. Cori et al. (Eds.), Comunicare ambiente e salute. Aree inquinate e cambiamenti climatici in tempi di pandemia. Edizioni ETS.

Durham, E., Baker, H., Smith, M., Moore, E., & Morgan, V. (2014). The BiodivERsA stakeholder engagement handbook. BiodivERsA. Paris.

Fricker, M. (2007). Epistemic injustice: Power and the ethics of knowing. Oxford University Press.

Funtowicz, S., & Ravetz, J. R. (2003). Post-normal science. Institute for the Protection and Security of the Citizen (IPSC), European Commission – Joint Research Centre (EC-JRC), TP 268. Research Methods Consultancy.

Marres, N. (2018). Why we can’t have our facts back. Engaging Science, Technology, and Society, 4, 423–443. https://doi.org/10.17351/ests2018.179

Visvanathan, S. (2005). Knowledge, justice and democracy. In M. Leach, I. Scoones, & B. Wynne (Eds.), Science and citizens: Globalization and the challenge of engagement (pp. 83–94). Zed Books.