Citizens’ Engagement Strategies in Planning and Management of Social Infrastructure

Research Question

What are the effective strategies cities use to engage residents in developing social infrastructure (parks and green spaces)?

The research, focusing on the urban parks located in 70 cities and municipalities in the Dallas Fort Worth Metroplex, aims to examine effective strategies that the towns can use to engage citizens in developing urban parks. The study will evaluate the impact of engagement initiatives on decision-making processes as one way of measuring strategy effectiveness. However, there are ambiguities in the methods used to appraise the effectiveness of civic engagement strategies (Berner et al., 2011). Other techniques that will be used to measure the efficacy of civic engagement strategies include estimating the overall citizens’ satisfaction and trust in the government and tracking civic participation rates.

Introduction/Gaps in Literature to be Filled

Humans are social beings that coexist in infrastructures of social life. Social infrastructure has been defined by Latham and Layton (2022) as the facilities, spaces, services, and networks that support the quality of life and well-being of communities. However, it is worth noting that different organizations have varying spectrums of what social infrastructure is depending on their mission, goals, and objectives. Those with narrow views focus on physical spaces. In contrast, those with alternative views connect physical and social spaces with people, emphasizing policies and measures taken to protect and manage social spaces such as parks in urban cities. This work focuses on the latter definition, examining the citizen engagement strategies employed to plan and execute social infrastructures.

Putnam (1993) used the predicament of the farmers in Hume’s parable to amplify the social challenge that communities in many countries continue to endure: lack of cooperation. The author observed that parents continue to call for better education for their children yet fail to collaborate to improve public schools. Social infrastructures, the main agenda for this research, also face a similar challenge; public spaces of sociality face a major crisis characterized by poor management due to lack of resources and cooperation. The problem has been accelerated by the need for more political goodwill and the unwillingness of communities to collaborate for social benefit. According to Putnam (1993), social capital is a major element that determines the success of good planning and management of social infrastructure. Social capital refers to a set of values and shared resources (networks) that facilitate the coordination and cooperation of individuals for mutual benefit, enhancing the benefits of physical and human capital investments. However, the concept of social capital works well in communities blessed with a substantial stock of social capital.

A decline in social capital is an observation that is not only in the social domain but also researched and affirmed by scholars across various spheres. Putman’s (2000) work, Bowling Alone, confirms that America’s social capital has been on the decline for the last five decades, informing that the ability to plan and manage American social spaces has been at a crossroads for the previous fifty years. His work further shows that a decline in civic engagement has accelerated the decline trend in America’s social capital. Using data on voter turnout for government elections, church attendance, and membership in professional organizations such as the American Medical Association and PTA meeting attendance, Putman (2000) observed that civic engagement in America declined by a third in the last quarter of the 20th century. For instance, formal membership in organizations edged downward by 10-20% in the previous 30 years of the century. Putman’s work infers that, indeed, citizen engagement in America faces a major crisis.

Efficient and effective planning and management strategies act as a catalyst in realizing a positive impact of social capital on social infrastructure. According to Layton and Latham (2021), the management teams and officials of urban spaces still need to live up to the dreams of maintaining and protecting urban parks, allowing events and activities that put the physical features and resources of these parks at risk. Park management gives permits to event organizers and artists for entertainment, especially during festive seasons. These events involve long periods where the park’s perimeter is mounted with 12-foot high perimeter fences (Layton & Latham, 2021). Poor planning and management of social infrastructures have been accredited to a need for citizen engagement in implementing policies geared towards protecting and managing urban spaces while holding management accountable. Evidently, there is a research gap regarding ways that urban space and other social infrastructure management can be used to ensure citizen engagement plays a significant role in the planning and management of social infrastructure. This research explores citizen engagement strategies that can improve the planning and management of social infrastructure in 70 cities/municipalities in the Dallas Fort Worth Metroplex.

The Hypotheses to be Tested

Urban parks planning and citizen engagement strategies

Null Hypothesis: Urban parks that strategically engage citizens are well-managed and offer high-quality services

Alternative Hypothesis: Urban parks that do not engage citizens experience planning and management issues and provide low-quality services.

Urban parks amenities and accessibility

Null Hypothesis: There is a relationship between urban parks’ amenities and accessibility

Alternative hypothesis: There is no relationship between urban parks’ amenities and accessibility

Urban parks amenities and access inequalities

Null hypothesis: Urban park amenities have a significant influence on parks’ access inequalities

Alternative hypothesis: Urban park amenities do not have a significant influence on parks’ access inequalities

Unit of Analysis

The research will analyze two units, namely citizens and urban parks. Under civic engagement, the study will explore the attributes and perceptions of American citizens and their awareness of civic knowledge and participation. In analyzing urban parks’ outcomes, the research will examine the quality and accessibility of urban parks.

Variables of Interest

The research will include dependent variables, independent variables, and control variables, as shown in the following table. Dependent variable: Number of parks with amenities. Independent variable: Citizen Engagement Strategies Control variables: (Socioeconomic and demographic: population change, population over 65, population under 18, white population, non-white population, unemployment rate, poverty rate)- data source is American Community Survey (Personal income per capita) – data source is City Annual Comprehensive Financial Report (ACFR)

Sources of Data and Measurement Description (Operationalization of Key Variables)

Sources of Data

The research will mainly use secondary data. Primarily, the study will analyze data on voter turnout for government elections to explore citizens’ political engagement. In particular, the International Institute for Democracy and Electoral Assistance (IDEA) electronic database will be used to retrieve data on the civic engagement of American citizens, especially voting. To measure nonpolitical engagement, data from two associations will be analyzed, including PTA and one professional association membership. Data on the quality, quantity, and accessibility of urban parks will be collected to examine social infrastructure outcomes.Trust of Public (TPL) electronic database will be used to analyze the Park Score Index that reflects the park’s quantity, quality, and accessibility ranked across 100 top cities in the U.S.

The primary data source for socioeconomic variables will be the American Community Survey, which will be used specifically for retrieving data on population change, age, and racial percentages. The data source for the socioeconomic variables (personal income per capita) will be the City Annual Comprehensive Financial Report (ACFR) electronic database. Above all, it is important to highlight that various electronic databases will be used to search and retrieve pieces of literature on the research topic. Peer-reviewed journal articles will be prioritized when retrieving articles for review. However, other secondary sources of data that will be considered include surveys, publications by the state and federal governments, books, and even internal records of urban parks.

Measurement Description (operationalization of key variables)

Urban Parks with Amenities

Urban parks with amenities have been identified as the dependent variable of the research. Three aspects of urban park outcomes will be measured, namely park quantity, quality, and accessibility. A number of studies have used the parks’ quantity, quality, and accessibility to examine their outcomes, especially the impact of parks’ amenities on residents’ well-being. These studies include Wang et al. (2021), Rigolon and Flohr (2014), Godbey and Mowen (2011),West et al. (2012),Shanahan et al. (2015), and Larson et al. (2016).

Rigolon and Flohr (2014) measured parks’ accessibility to play opportunities to examine existing inequalities in accessing urban parks and remedies that can be used to reduce or overcome these inequalities. The researchers explored various ways in literature used to measure accessibility and proximity to public amenities. Geographic Information System (GIS) network analysis is one of the methods used in multiple studies to measure distances between residences and public facilities. The method uses a weighted spatial network analysis service area function in a GIS (ESRI’s ArcGIS, version 10) based on a modified version of the minimum distance approach modeled and introduced by Talen and Anselin (1998). The units of analysis in the GIS analysis method used by the researchers included census blocks, parcels, census block groups, and neighborhoods, which, according to Talen and Anselin (1998), may create different results. Census blocks were also used to document household income, the percentage of the non-white population, and the percentage of people less than 18 years old. Parks’ equity of access was also measured in terms of land value and population density. Rigolon and Flohr (2014), however, improvedTalen and Anselin’s (1998) GIS analysis approach by combining census blocks and parcels to measure to examine the percentage of parcels with access within each census block quantified as access ratio calculated by the following formulae;

Wang et al. (2021) explored three approaches used for measuring the spatial accessibility of urban parks, which are all based on the GIS technique. They include the statistical index approach, the spatial proximity approach, and the spatial interaction approach. The statistical index approach measures the quantity, size, or density of parks in a defined geographical area. Conversely, the spatial proximity approach measures travel costs, such as travel time, distance, or monetary cost spent by park users to get to a park. Lastly, the spatial interaction approach (gravity models) measures the force of attraction between the home locations of residents and the park. The three approaches provide almost similar results when used to measure parks’ accessibility. However, Wang et al. (2021) assert that the unit of analysis used in each approach may be different, although the most common variables analyzed under the three approaches include network complexity, distance threshold, transport modes, and choices of destination by park users.

Research by Larson et al. (2016) used the Trust of Public (TPL) Park Score Index to examine the relationship between park outcomes and the well-being of park users. The Trust of Public (TPL) produces the annual Park Score Index that ranks park systems in the 100 most populated cities in the U.S. It is widely considered the gold standard for park evaluation, assessing parks based equally on five factors, which include park access, park quality, acreage, park investment, and park amenities. Park access measures the percentage of residents living within a 10-minute walk of a park, while park acreage determines the city’s median park size and the rate of the city’s area dedicated to parks. Park quality compares per capita space and 10-minute walk park access in communities of color versus white communities, as well as low-income neighborhoods versus high-income neighborhoods. Park systems with minimal or non-existent disparities usually have high park equity scores. Park investment measures park spending per resident, while park amenities examine the availability of six popular park features, which include restrooms, splash pads and other water-play structures, recreation and senior centers, playgrounds, off-leash dog parks, and basketball hoops (Trust for Public Land, 2023).

Larson et al. (2016) estimated the park’s quantity by adding all acres of parkland managed by any public park agency under federal, state, or municipal boundaries within the municipality. They divided the result by the municipality’s total area. Trust of Public (TPL) Park Score Index of park quality was used to measure the quality of the parks. Considering that the Park Score Index per capita spending in parks is approximated in dollars per person, the researcher had to convert it to tens of dollars per person to align with the designed model coefficients of the research. Park Score Index of par’s accessibility was also used to examine the accessibility of parks using road networks unobstructed by obstacles such as rivers, fences, and freeways.

Citizen Engagement Strategies 

The research identified civic engagement strategies as the independent variable. A study by Shahid et al. (2022) used data from the International Institute for Democracy and Electoral Assistance (IDEA) and the Institute for Citizens and Scholars to review methods of citizen engagement in health research. Other studies that have used similar data and systematic literature review include Oliver et al. (2008) and Payne et al. (2011). Although the studies did not narrow down to political engagement attributes such as working for a campaign and volunteering, the researchers were able to identify a political engagement trend from the data extracted from IDEA. Data from the Institute for Citizens and Scholars will also be used to analyze cohesion and trust as a measure of civic knowledge awareness. The National PTA electronic database will be used to collect data on PTA meetings in schools within the selected urban parks for the research. The data will help to estimate the civic engagement patterns and trends within schools, which will, in turn, be used to relate citizen engagement and urban park outcomes.

Data Reliability

Data reliability is the completeness and accuracy of data as a measure of how well it is consistent and free from errors. It relates to the truthfulness of the obtained data and the degree to which any measuring tool controls data. There are three main ways that data reliability can be measured, namely, over time, across items, and inter-rater reliability. The overtime reliability is a test-retest reliability where researchers assume that when a construct is consistently measured across time, it is likely to give consistent scores within the research period. The test-retest reliability is based on the correlation between the results of two or more tests performed in similar research conditions and environments. Pearson correlation coefficient is one common statistical model used to measure test-retest reliability (Polit, 2014). Across-item reliability is internal consistency reliability that considers multiple item measures that reflect the same underlying construct. Cronbach’s α and Rosenberg Self-Esteem Scale are the common statistical tools used to measure internal consistency across items (Tinakon & Nahathai, 2012; Heo et al., 2015). Lastly, inter-rater reliability involves a behavioral measure by a rater (Chaturvedi & Shweta, 2015). The research data aligns with inter-rater reliability.

There are a number of studies that have used similar data the research intends to use.Larson et al. (2016) used data from theTrust of Public (TPL) to analyze the quality, quantity, and accessibility of parks across the top 100 cities in the U.S. The Park Score Index was used to rank parks based on five metrics used by TPL. Zeng and Liu (2023) also used TPL’s Park Score Index to benchmark and compare the performance of Chinese and U.S. parks based on the factors that influence park use from geospatial perspectives. Other studies that have used the park’s quantity, quality, and accessibility to the outcome of urban parks include Godbey (2010), West et al. (2010), and Shanahan et al. (2015). Shahid et al. (2015) used civic engagement data to evaluate citizen engagement in healthcare. Other studies that have also used civic engagement as a variable include Mullenbach et al. (2019), Powers et al. (2022), andCampbell et al. (2022).

Methodological Issues and Remedies

One major methodological issue that the research is likely to face is the variation in temporal and spatial scales of measurement. Various data sources have different scales of measurement, which is a challenge in aligning the data for analysis. For instance, the data used by TPL for the Park Score Index and that provided by the Bureau of the Census used by IDEA have varying metrics, which can give rise to inconsistencies when analyzing data. Richardson et al. (2012) reiterate that varying measuring scales reduce the reliability of data collected and the degree of generalizability of the research. However, converting the retrieved data into a standardized geographical unit that encompasses an identical sample population can help to overcome inconsistencies when analyzing the data.

Estimation Methods

The research will use interval estimates. Interval estimation is the evaluation of a research parameter, such as population mean, by computing a range of values known as intervals within which the research parameter is most likely to lie. The advantage of interval estimation is that it gives researchers the power to estimate the unknown parameter of the population based on the research sample. It further provides a range of plausible values with how confident (confidence interval) the researcher can be in the estimated range of the parameter of interest (Hoekstra et al., 2014). To be precise, a 95% confidence interval will be used to accept or reject the null hypothesis.

Contributions and Limitations

Contributions

Major urban parks in U.S. cities are publicly managed social infrastructures that depend on social capital for survival. Unfortunately, American social capital has been on a downward trajectory, threatening social infrastructures such as public urban parks that rely on communities, municipals, and state and federal governments for financial resources. The research aims to contribute to knowledge in the public domain about the significance of citizen engagement strategies in planning and managing urban parks. Engaging citizens in the planning and management of urban parks can play an important role in improving governance by selecting qualified personnel and holding them accountable while participating in policy formulation, such as increasing resource allocation towards the planning and management of urban parks.

Limitations

The study will be limited by the fact that it will consider data collected at the national level, mainly from 100 top cities in America. However, site-based research and data gathered from emerging cities and towns may provide a unique perspective, trend, or pattern that is yet to be explored and that may make an immense contribution to research. The research setting may limit the researcher’s ability to explore all aspects that influence the research variables. Secondly, the research only focuses on examining the relationship between dependent and independent variables. For this reason, it may be a challenge to identify and even verify the causation of the trends and patterns that will be observed between the research variables. Thirdly, the population sample of the research may limit the validity of the data collected.The research will consider 70 cities/municipalities in the Dallas Fort Worth Metroplex. This is a small number compared to the total number of parks found within the research area. The number of urban parks to be analyzed therefore, represents a relatively small percentage of the total urban parks in Dallas. Low validity may also affect the generalizability of the research.

Reference List

Berner, M. M., Amos, J. M., & Morse, R. S. (2011). What constitutes effective citizen participation in local government? Views from city stakeholders. Public Administration Quarterly, pp. 128–163.

Campbell, L. K., Svendsen, E., Johnson, M., & Landau, L. (2022). Activating urban environments as social infrastructure through civic stewardship. Urban Geography, 43(5), 713–734.

Chaturvedi, S. R. B. H., & Shweta, R. C. (2015). Evaluation of inter-rater agreement and inter-rater reliability for observational data: an overview of concepts and methods. Journal of the Indian Academy of Applied Psychology, 41(3), 20-27.

Godbey, G., & Mowen, A. (2011). The benefits of physical activity provided by park and recreation services: The scientific evidence. Australasian Parks and Leisure, 14(1), 26-29.

Heo, M., Kim, N., & Faith, M. S. (2015). Statistical power as a function of Cronbach alpha of instrument questionnaire items. BMC Medical Research Methodology, pp. 15, 1–9.

Hoekstra, R., Morey, R. D., Rouder, J. N., & Wagenmakers, E. J. (2014). Robust misinterpretation of confidence intervals. Psychonomic Bulletin & Review, 21, 1157-1164.

Larson, L. R., Jennings, V., & Cloutier, S. A. (2016). Public parks and well-being in urban areas of the United States. PLoS one, 11(4), e0153211.

Latham, A., & Layton, J. (2022). Social Infrastructure: Why it matters and how urban geographers might study it. Urban Geography, 43(5), 659–668.

Layton, J., & Latham, A. (2021). Social Infrastructure and Public Life – Notes on Finsbury Park, London. Urban Geography, 43(5), 755–776. https://doi.org/10.1080/02723638.2021.1934631

Mullenbach, L. E., Baker, B. L., Benfield, J., Hickerson, B., & Mowen, A. J. (2019). Assessing the relationship between community engagement and perceived ownership of an urban park in Philadelphia. Journal of Leisure Research, 50(3), 201-219.

Oliver, S. R., Rees, R. W., Clarke‐Jones, L., Milne, R., Oakley, A. R., Gabbay, J., … & Gyte, G. (2008). A multidimensional conceptual framework for analyzing public involvement in health services research. Health Expectations, 11(1), 72–84.

Payne, J. M., D’Antoine, H. A., France, K. E., McKenzie, A. E., Henley, N., Bartu, A. E., … & Bower, C. (2011). Collaborating with consumer and community representatives in health and medical research in Australia: results from an evaluation. Health Research Policy and Systems, 9, 1–14.

Polit, D. F. (2014). Getting serious about test–retest reliability: a critique of retest research and some recommendations. Quality of Life Research, p. 23, 1713-1720.

Powers, S. L., Webster, N., Agans, J. P., Graefe, A. R., & Mowen, A. J. (2022). The power of parks: How interracial contact in urban parks can support prejudice reduction, interracial trust, and civic engagement for social justice. Cities, 131, 104032.

Putnam, R. D. (1993). The prosperous community. The American Prospect, 4(13), 35–42.

Putnam, R. D. (2000). Bowling alone: The collapse and revival of American community. Simon and Schuster.

Richardson, E. A., Mitchell, R., Hartig, T., De Vries, S., Astell-Burt, T., & Frumkin, H. (2012). Green cities and health: a question of scale? Journal of Epidemiology and Community Health, 66(2), 160-165.

Rigolon, A., & Flohr, T. L. (2014). Access to parks for youth as an environmental justice issue: access inequalities and possible solutions. Buildings, 4(2), 69-94.

Shahid, A., Lalani, I. N., Rosgen, B. K., Sept, B. G., Longmore, S., Parsons Leigh, J., … & Fiest, K. M. (2022). A scoping review of methods to measure and evaluate citizen engagement in health research: Research Involvement and Engagement, 8(1), 72.

Shanahan, D. F., Fuller, R. A., Bush, R., Lin, B. B., & Gaston, K. J. (2015). The health benefits of urban nature: How much do we need? BioScience, 65(5), 476–485.

Talen, E., & Anselin, L. (1998). Assessing spatial equity: an evaluation of measures of accessibility to public playgrounds. Environment and Planning A, 30(4), 595-613.

Tinakon, W., & Nahathai, W. (2012). A comparison of reliability and construct validity between the original and revised versions of the Rosenberg Self-Esteem Scale. Psychiatry Investigation, 9(1), 54.

Trust for Public Land. (2023). Washington, DC, Park System Ranked Nation’s Best in Trust for Public Land’s Annual ParkScore® Index; Saint Paul Places Second, Minneapolis Third, Irvine Surges to Fourth. Retrieved from https://www.prnewswire.com/news-releases/washington-dc-park-system-ranked-nations-best-in-trust-for-public-lands-annual-parkscore-index-saint-paul-places-second-minneapolis-third-irvine-surges-to-fourth-301832823.html

Wang, S., Wang, M., & Liu, Y. (2021). Access to urban parks: Comparing spatial accessibility measures using three GIS-based approaches. Computers, Environment and Urban Systems, 90, 101713.

West, S. T., Shores, K. A., & Mudd, L. M. (2012). Association of available parkland, physical activity, and overweight in America’s largest cities. Journal of Public Health Management and Practice, 18(5), 423–430.

Zeng, L., & Liu, C. (2023). Exploring factors affecting urban park use from a geospatial perspective: A big data study in Fuzhou, China—International Journal of Environmental Research and Public Health, 20(5), 4237.