Spring 2019 |
Newsletter Archive |
#CitSci2019 | |
Miistakis recently participated in the 2019 Citizen Science Association Conference - "Growing our Family Tree" in Raleigh, North Carolina. It was a huge gathering of citizen science practitioners from around the globe, with a particular focus this year on citizen science and social justice. The opening keynote, Dr. Max Liboiron was particularly thought provoking and inspirational - you can read her opening address on the CLEAR website. I was struck by the immense diversity in citizen science programming, from geographic scope, desired outcomes, level of participation, and methodological approach. The main similarity between programs is volunteer engagement in science. Pocock et al (2017) reviewed hundreds of citizen science programs and was not able to find clusters of program types (except for a cluster relating to on-line citizen science) but instead found programs fall along two continuums relating to complexity of the citizen science activity and type of methodology (i.e. ranging from mass participation to systematic monitoring). These are important lessons as development of best management practices are likely contextual to where citizen science programs fall along these continuums and the stated program outcomes. No wonder the comment by one presenter "does citizen science even exist?" resonated with me. As the field of citizen science continues to grow, how do we label or group programs to enable dialogue that advances the field of practice. Or as one presenter claims - "stay calm and accept the continuum!" I attended a great session on meta-analysis of citizen science programs - from Zooniverse (on-line classification platform) to co-created programs (community derives research questions). This session explored the synergies between diverse types of citizen science programs spanning outcomes from big data to problem driven community organizing. A diverse set of speakers outlined lessons learned from meta-analysis across projects types and platforms - participants tend to contribute to multiple programs, all programs have learning outcomes but stronger levels of engagement equate to stronger learning outcomes, classifications or data collection tend to be driven by a relatively small number of program participants, and tensions exist between science efficiency and social inclusivity in program structure and design. Meta-analysis represents an important tool for identifying where there are synergies between citizen science program types. It expounded the importance of developing metrics and some consistency in meta-assessment standards. Lastly, I'm still enjoying thinking about the notion of street science... decision-making that draws on community knowledge and contributes to environmental justice. Author: Tracy Lee | |