Citizen participation is a critical component of any Community Based Monitoring (CBM) intervention thus, it is important to understand the factors that either facilitate or hinder participation. I therefore explore these factors in my End-of-Module Paper through a literature search, putting into consideration contextual variation.
The factors affecting citizen participation include; (1) participation bottlenecks (namely; information gaps, lack of attention or rational inattention, high opportunity cost of participation, collective action failure, citizens’ beliefs, and elite capture)[1]; (2) incentives[2]; and (3) perceived political efficacy (citizens’ beliefs in terms of their own capacity and responsiveness of the decisionmakers to their demands, either as individuals or collectively).[3] Moreover, these factors also vary depending on the CBM approach and the focus sector.
I selected the three cases based on variations in the country context (Bangladesh, Afghanistan, and Cambodia) and similarities in the CBM intervention (primary healthcare sector, using the community scorecards approach). The comparison among these three cases is captured in the table below.
In all these cases, perceived political efficacy and at least some of Molina et al. (2017)’s six bottlenecks are considered as factors affecting citizen participation, which means these factors are relevant across the three contexts. Collective action failure did not feature in any of the cases, perhaps because free-riding is less common in sectors providing private goods such as healthcare.[4] I also included inequality and discrimination, security concerns, location or accessibility, and fear of retaliation as additional factors. These emerged in the case studies and in some instances, were only relevant to particular contexts.
It therefore emerges that while some factors are present across all three cases, context is still a big determinant of citizen participation. It is thus important for development actors involved in CBM to conduct context analysis to inform the interventions. Other recommendations include providing relevant information to community members, skilled facilitation, and choosing venues that are accessible to community members, including disadvantaged groups.
Factors affecting citizen participation in the three cases
Note. A cross mark (✘) denotes that the factor does not affect citizen participation in the case, based on the findings of the respective study. Reprinted from “Determinants of citizen participation in community scorecards for primary healthcare services: A comparative case study” [End-of-module paper] by Malabanan (2022), Institute of Development Policy, University of Antwerp.
References
[1] Molina, E., Carella, L., Pacheco, A., Cruces, G., & Gasparini, L. (2017). Community monitoring interventions to curb corruption and increase access and quality in service delivery: a systematic review. Journal of Development Effectiveness, 9(4), 462–499. https://doi.org/10.1080/19439342.2017.1378243
[2] Olson, 1965, as cited in: Dewachter, S., & Holvoet, N. (2017). Intersecting social-capital and perceived-efficacy perspectives to explain underperformance in community-based monitoring. Evaluation, 23(3), 339–357. https://doi.org/10.1177/1356389017716740
[3] Verba et al., 1995; Craig et al., 1990; Manning et al., 2008; Lee, 2006, as cited in Dewachter, & Holvoet, 2017
[4] Olken, B. (2007). Monitoring corruption: evidence from a field experiment in Indonesia. Journal of Political Economy, 115(2), 200–249. https://doi.org/10.1086/517935
Note
This blog post is an excerpt from my End of Module Paper;
Malabanan, Q. D. (2022). Determinants of citizen participation in community scorecards for primary healthcare services: A comparative case study [End-of-module paper]. Institute of Development Policy, University of Antwerp.
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