From Clocks and Clouds VOL. 4 NO. 1
On Global Order: South Africa as a Case Study for the Validity of City-Specific Research in International Development
IN THIS ARTICLE
This study provides an overview of the international development field's attention to urbanization. Despite cities being proven the largest hubs of development for the industrializing world, patterns in urban areas often behave much differently than when assessing aggregate-level data. Assessment of cities as their own spheres of development is necessary. Currently, the development field fails to implement measures addressing the enormity of this phenomenon: while it acknowledges city-specific growth projects are important, very little raw data is available for analysis, and studies comparing multiple cities together are rare. This paper addresses the questions "are city-specific data important, and if so why?" through a mixed methods approach. The use of quantitative analysis highlights existing data found for three indicators of development. Qualitative analysis provides an overview of city-specific development by multiple players in the field, including international organizations, scholars, non-profits, think tanks, and governments. Findings point to the validity of increased attention to city-specific indicators in the future, as well as a need for collaboration on findings between involved actors. The study reveals a gap in the study of international development and calls for a shift in the way scholars view urbanization in our increasingly globalized world.
Our world is changing. No longer are individuals bound to their respective nations as they once were, but instead beginning to identify themselves as global citizens interconnected by commerce, communication, and a common push for economic growth. Increasingly people are joining together, connected by urban hotspots around the world. In fact, urban sites are the principal incubators of development. Cities attract the highest levels of foreign investment, the brightest and most innovative minds, the largest international industries, and the most populous community organizations that can mobilize diverse bodies of people together. Yet a critical oversight in modern scholarship is how we persist in treating cities as completely subordinate to the state. Instead of considering cities as an indicator of development potential, scholars continue to measure output on an aggregate, statewide level. This study explores how urban development diverges from typical notions of international development, using South Africa as a case study. The study focuses on the incredible gap in citywide research, a modality missing from nearly every realm of social science.
In 1800, fewer than 3 percent of our world's population resided in urban areas (Clark 1998). As the industrial revolution took hold of the globe and industries began to sprout up along city borders, this number increased dramatically. Driven by capitalism with the lure of higher wages and improved quality of life, a mass proportion of the world's population migrated away from their farms towards more tightly concentrated urban areas. By 1950 approximately 27 percent of the world were urban dwellers (Clark 1998). The year 2008 marked the first time in history that a majority of the world's population resided in urban areas. By 2050, it is estimated that over 70% of our world will live in cities, with most of this growth projected in developing countries (Population Reference Bureau 2014). This fundamental change in where people live is monumental.
The interdependency of globalization very closely parallels the interdependency that comes from living in closely confined urban areas. Increasing interdependence in every realm of human interaction shifts the way humanity organizes production, competition, and finance. Because of their international nature and lack of spatial boundaries, corporations and investors have the potential to drive economic growth fundamentally more than any government. For these international actors, it is not the resident country but rather "the world cities in which they are located that are the command and control points of the global economy" (Clark 1998, 94). Our world tends to urbanize when localized patterns of investment, production, and employment centralize. The result is a domino effect of labor migration that in turn spurs new growth. The dense population cities possess offers access to a larger labor forces, localized markets, and a demand pool for all types of goods and services available, in turn spurring investment. For the developing world, cities are frequently the only source of large-scale industries, hospitals, universities, transportation hubs, and community facilities ranging from sports arenas to labor unions. Research on urbanization, and in particular city-to-city relationships, is therefore fundamental to understanding modern-day development. Yet international citywide data is nearly non-existent, despite prior acknowledgements that, "urbanization represents the largest shift in the distribution of population in history" (Clark 1998, 94).
While a number of scholars, governments, and international organizations recognize the vital role of cities, virtually none of these entities explore development at city-specific levels in developing nations. When research is available, most studies focus on only focus on an aspect of development that nearly always reflects economics. When there is explicit urban data for a developing country, it is only for the capital or most populous city. Furthermore, articles often speak about the merits of urbanization while using country and regional data to predict growth and prescribe development strategies. Few publications even recognized the need for city-level data. The rare exception was "global" city comparisons but none of these studies examined cities outside of the top metropolises identified by the Global Cities Report (Hales 2012). The importance of city-level data is not confined to developing nations. For example, while developed nations, particularly the United States, tend to have more detailed state-level data, development work in cities are still hindered by a lack of data. Most city research focused only on each state's capital city, rarely furnishing data for other important or populous cities within the state.
Considering that majority of expected growth over the next decade will come from "middleweight" cities, defined as having a population ranging from 150,000 to 1,000,000 people, this contradiction is puzzling (McKinsey Global Institute, 2012). Out of a total 250 middleweight cities within the U.S., the top 20 alone are projected to contribute one-third of total economic growth over the next two years (McKinsey Global Institute, 2012). As an international trend, middleweight cities will soon account for the largest share of global economic output. By 2025, half of the world's global growth will be attributed to just 577 middleweight cities (McKinsey Global Institute, 2011). This study proposes that the lack of city-specific research is hindering more accurate understanding of conditions worldwide in the field of international development.
In order to test this prediction, the country of South Africa and its development landscape was chosen as a case study. South Africa presents an interesting case as a developing country with rapid growth and bright prospects for future investment and development, particularly in major metropolitan areas. South Africa also has fairly high levels of data reporting in relation to most other developing countries. While data on many individual cities is still weak, both Cape Town and Johannesburg are cities frequently referenced and treated as distinct entities in the literature. This presents a novel case as most developing nations have detailed data for only one major city, complicating comparative case studies.
This study will further assess the hypothesis that the validity of international development research can be enhanced through three new foci. First, city-specific perspectives must be included to triangulate findings on a regional or national level. Second, secondary- or tertiary-level cities, which are expecting to account for large shares of future economic growth, must also be included. Third, comparison of cities themselves, versus national development comparisons, can yield additional insights into how some development approaches have proven more successful than others.
This study is framed to overcome limitations in data availability. Most city-level data is strictly economic, limiting analysis of development level, which is amore comprehensive measure. Development level encompasses quality of life, measures of relative security, and contentment within a society. While this study examines the merits of city-level data for the understanding of development in particular, it is still limited by ongoing discussions on how to operationalize the concept of development. This study will adopt the Human Development Indicator's conceptualization of development. The level of human development can be measured by: (1) enjoyment of a decent standard of living, (2) level of education and knowledge, and (3) length of a healthy lifespan (UNDP 2010). It was beyond the scope of this study to measure the complete HDI index of variables, however. This study will therefore measure one indicator from each category, maintaining the validity of the tri-partite definition of development while also allowing for the greatest breadth of data to analyze.
These three indicators are: (1) crime rates, (2) school attendance, and (3) HIV/AIDS prevalence. A city's crime rate directly affects personal security and thus standard of living. School attendance is a key proxy for level of education in the developing world (Statistics South Africa (GHS), 2010). Lastly, HIV/AIDS was chosen as a proxy measure for healthy lifespan as it is one of the few development challenges that is more detrimental to urban populations. These three indicators were also chosen as they scale well across both urban and rural communities. This is due to the concept of service delivery, whereby it should be the quality of the service provided, whether urban or rural, rather than just the service's accessibility that should determine development level.
For instance, dropout rates for South Africa's provinces are more strongly influenced by unemployment and school quality than they are about being able to physically attend the school in question. Similarly, due to the country's relative successes in HIV awareness education and contraceptives distribution, transmission rates are now more dependent upon population densities and socioeconomic factors than they are access to health services. However, this finding may not apply to other nations. Due to differences in the data available, each indicator was analyzed in a variety of ways. Violent crime statistics, provided by the government, allowed for the conduction of regression analyses. Survey data for school dropout rates allowed for a mixed-methods analysis using qualitative data for correlation tests. Due to the private nature of data collection for HIV/AIDS rates, one particular city's policies are analyzed in order to ascertain whether they believe transmission rates affect spatial populations differently.
Crime is particularly pertinent problem for cities as populations are frequently tightly confined yet starkly split into communities based on economic strata. As crime and urbanization are strongly related, criminology as a discipline tends to acknowledge city variations in data much better than social science. As early as the 19th century, theoreticians Guerry and Quetelet observed that crime rates were uneven across locational spaces, with a higher concentration of crime in urban dwellings (Bruinsma 2007). More recently, researchers have paid renewed attention to their work, re-visiting the importance of city-specific measures as serious crimes, such as homicide, robbery, rape, and assault, are becoming disproportionately concentrated in cities (Ballentine 2006; Grahm 2000).
As consequence of both density and economic stratification, cities also offer some of the worst examples of relative deprivation. Relative deprivation is the phenomenon where an individual tends to evaluate their wellbeing relative to others in the same environment (Barash 2000). Due to South Africa's lingering spatial distribution of post-Apartheid cities, the urban poor predominately live on the urban outskirts. This creates urban hotspots for relative deprivation. The social stratification perspective, which asserts crime is related to economic conditions, can also be put forth as being especially relevant given South Africa's unemployment rate of 29.8% (Grahm 2000). Additionally there exists a strong positive association between a city's size and its reported level of crime. In fact, distinguishing between small and large cities has been "a much more important [descriptive] factor than the region where these cities were located." (Grahm 2000, 273) Data published by the South African government on crime rates is only produced regionally. The South African Police Department did offer crime data that was city-specific; however, there existed no reports from the government on population figures.
These data will be utilized to provide a window into regional differences, giving us city-specific crime rates against which to measure. To assess the claim that crime is most intense in highly dense areas due to relative deprivation factors, only crimes that potentially could be justified by economic and/or social grievances were analyzed. Such crimes included murder and attempted murder, assault with intent to inflict bodily harm, robbery, arson, burglary, theft and malicious damage to property. Crime statistics are broken down by both province as well as city when available from the South African Department of Police. To adequately compare crime rates, population data on these respective regions and cities was also required. Population rates are broken down by province when available by the South African Statistical Bureau but published data on current population figures for cities was not found. Population data also varied greatly by source and is a potential confounding variable in the analysis. The provinces in South Africa were then measured to determine whether a larger population would increase a region's overall chances of experiencing crime. A province's crime rate was not found to be indicative of its population size (Figure 1).
This finding supports this study's claim regarding the nature of crime in cities, mainly that provincial-level data is not conducive to determine city-level crime rates, as provinces often contain many cities as well as rural areas. The case of Gauteng provides a strong example of this phenomenon's importance. Gauteng's total crime rate is not very useful if one considers that five out of ten of the country's most populous cities fall within this one province. A high crime rate of any one of these cities would disproportionately skew Gauteng's data in relation to other provinces, such as Limpopo, which has a large rural population yet contains no major cities. City data was then tested in order to see if it differed from the provincial findings. Keeping with earlier findings that a larger city has higher levels of crime, South Africa's three most populous cities, Johannesburg, Cape Town, and Durban, were first analyzed (Grahm 2000). Three middleweight cities, Port Elizabeth, Pietermeritzburg, and Tembisa, were also included in the sample. Higher population was not correlated with higher crime rates. (See Figure 2).
These findings are not consistent with the original claim. Rather, these data indicate the smaller a city is, the more likely it is to experience crime. While not supportive of this study's claims, these findings provide avenues for future research. The over-arching meaning of these findings proves that city data is essential to understanding crime rates. The great disparity between these two levels of measurement represents how important city data is for criminology studies, as provincial data in no way indicates city- level conditions. Additionally, the overall lack of data for cities, in particular middleweight cities, is detrimental to any valid research on development. Even data for population size at this level was lacking. When it was available, the difference in population figures between sources confounded accurate analysis. If the second source of population data were accurate, our results suggest that previous findings by scholars are no longer relevant for today's crime patterns in specific cities. If the data were inaccurate, then our findings would likely have diverged significantly, potential leading to further avenues of research.
Education and School Attendance
Education is another vital aspect of development, as a child's level of education has long-lasting implications on general quality of life. Advances in education, and in particular female education, have been one of the largest successes for development of the past century. Since 1970, no country has seen declines in literacy rates or years of schooling. Moreover, once one generation is educated, it is highly unlikely their children will not receive the same, if not higher, level of education (UNDP "The Advance of People" 2010). Yet problems with education are still widespread. In Africa alone more than 30% of students will drop out of before completing primary school, making the Millennium Development Goal of universal primary education impossible to achieve (United Nations 2010). In addition, education rates and accessibility are highly skewed in favor of urban areas. In every developing country, urban areas equate to more and better schools, located within shorter reaches of the target population. School attendance rates are also higher in urban areas. Out of 25 African countries studied, every one has higher school enrollment in urban areas and generally more even girl-to-boy ratios (Sahn and Stiefel 2003). Cities also offer better opportunities for those who are educated, with a child's rate of schooling positively correlated with future occupation level and wages (Barnum and Sabot 1977).
Additionally, there is a positive correlation between one's education level and the propensity to migrate to urban areas (Ibid.). Individuals with higher education levels are more likely to migrate to cities, while those already living in a city are more likely to attend school for a longer amount of time. Essentially urban areas attract, and then retain a country's educated population. Urbanization is seen as being the "key positive influence on changes in education and income, confirming an established finding on the vital role of cities in transmitting ideas" (UNDP "The Advance of People" 2010, 57). Yet urban inequality in Africa grows at alarming rates. Urbanization rates in developing countries often outpace cities' increases in employment and production, leading to higher unemployment rates. Policy makers frequently overlook other unexpected results of urbanization, including urban malnutrition and food insecurity (Thurow and Kilman 2009).
These negative consequences are detrimental to urban education rates. In South Africa, city municipalities are often too weak and underfunded to provide the service delivery necessary for increased population numbers. Individuals migrating from rural areas looking for better opportunities are frequently unable to afford the increased housing costs associated with moving to a city. They frequently relocate to informal settlements along city peripheries, comprised of "ex-White" neighborhoods existing since the Apartheid era. These informal settlements attract the largest percentage of the urbanizing population, yet due to their informal nature, are often under-regulated by the large city districts they fall under. In terms of education, these areas are characterized by poor school infrastructure, high secondary school dropout rates, and high unemployment rates. Interestingly, the average level of education in these informal urban areas is closer to rural communities than their city-center counterparts. Despite drastic differences between rural and urban, and even urban-to-urban levels, education policies do not differentiate between South Africa's "dualistic schooling systems."
Adequate research on a city-specific basis is key to creating meaningful policy recommendations with long-run implications, yet collection of this data is severely underfunded in South Africa. (Spaull 2012) Since city-specific data was again incomplete, provincial data based on the behavior of schoolchildren was used for analysis. Measures of education levels by province were adapted from two surveys, the General Household Survey (GHS), and the Survey of Activities of Young People, both commissioned by the South African government. The Survey of Activities of Young People looked at how children 7-17 years old divided their time between combinations of work, household chores, and studying. Out of all provinces, Eastern Cape had the highest number of students who reported having no time to dedicate towards study. The province also had the highest percentage of students who dropped out of school (See Figure 3).
However, when assessing the relationship for all of the provinces, the two variables are not strongly correlated. Of the students involved in economic activity, 95% were involved in the production of goods and services for their own household. For those who worked in industries, 58.1% were involved in trade. Additionally, if children reported working for more than 14 hours a week, they were overwhelmingly employed in trade (Statistics South Africa 2010). The report did not indicate what types of jobs were associated with the trade industry. This limitation was disappointing, as it would have been interesting to determine whether these jobs were mainly urban-based. The most interesting data from this report was what was left out of it. For example, the report indicated individuals without formal education were most prevalent in the Limpopo (13.4%), Mpumalanga (11.3%) and Northern Cape (10.9%) provinces (Statistics South Africa (GHS), 2010).
This is important considering none of these provinces include one of the 10 major cities in the country. Only one other province does not include such a city – Eastern Cape – and that province has the highest national dropout rate. This revelation suggests that an individual will tend to have lower levels of education if they do not live near a city. Yet such observations are impossible to predict for these areas, as city data is not available for testing. It is most interesting that the report, written by the South African government, does not acknowledge this. Another similar oversight occurred in the Activities of Young People Survey. Out of those who did not attend school, "a lack of money" was the most frequent explanation. The second most frequent constraint was that the individual had to work, either at home or in a business. Individuals in Gauteng (29.9%) and Western Cape (26.3%) most frequently cited working as a reason they dropped out of school.
Once again, the report fails to acknowledge that these two provinces contain by far the largest urban populations for the country. Working in a business in order to support one's family may give us a window into why students in urban locations drop out of school. The ability to have an out-of-home job, especially in trade, is substantially higher for urban than rural areas. Alternatively, if unemployment is increasing in cities and families cannot find jobs to support themselves, then those reporting a "lack of money" as the reason for dropping out of school will also be centralized around urban areas. A potential example of this could be Gauteng, where 37.7% of students said they were not attending schools because they could not pay for school fees (Ibid.). Making projections about an urban area's relationship of education and unemployment, based on provincial data, is not conclusive. In this instance, understanding provincial data fails to explain anything about its cities, besides the fact that it includes aggregate city-level data. Using provincial-level data to inform development policies at the city-level would appear to be a disastrous choice for developing nations.
South Africa's HIV/AIDS prevalence ranks among the highest in the world. However, thanks to South Africa's proactive response to the epidemic, most recently with its HIV/AIDS Strategic Plan of 2007-2011, the rate of increase has significantly slowed and the infection rate has peaked at 11.42% (Tomlinson 2008). Yet there is markedly more to be done, especially considering there is "no single HIV/AIDS epidemic in South Africa" (UNAIDS, 2007), but instead that the disease's spread is dependent on situational factors varying from region to region. For South Africa as a whole there are a few general trends. First, there is a clear positive correlation between HIV/AIDS and poverty, as well as with poor access to social services including adequate nutrition, care, and support programs. Second, prevalence is highest for African females in their early 20s, living in informal settlements in high prevalence provinces (Tomlinson 2008).
Third, in places such as KwaZulu-Natal's informal urban slums, prevalence is higher than in formal urban areas (Ramjee et al 2012). Furthermore, special attention to cities facing the epidemic is critical to implementing successful prevention and treatment programs. First, while urban areas may not always have the highest prevalence rates, they almost always carry a higher probability of contracting the disease. Factors exacerbating HIV/AIDS transmission, including multiple concurrent partners, men-to-men transmission, co-infection with other STIs, and high levels of migration, are all more prevalent in cities (Tomlinson 2008; UNAIDS 2011). Second, informal settlements frequently bordering city lines have prevalence rates almost twice as high as formal urban complexes. Third, in informal urban areas, women frequently have a lack of economic freedom, education, health services, sanitation, and ability to negotiate safe sex practices (Ibid). Fourth, since cities also support significantly higher educational opportunities, access to health professionals and resources, and increased sanitation facilities, there also exists a divergence between availability and access to services.
Accurately viewing the HIV epidemic requires identifying infection rates by in individual cities. By dividing these respective cities based on sub-level demographic indicators, health workers may better target infection rates while providing treatment to those who need it. South Africa understands the importance of establishing city-specific HIV/AIDS strategy programs that involve the work of local governments and municipalities. In Cape Town and Johannesburg, thorough plans targeting resource allocations and service delivery have been proposed and some even partially implemented. For example, the strategy plan for Johannesburg acknowledges prevalence rates in the city are higher than they are in the Gauteng province as a whole and are "significantly higher" than in the rest of South Africa (See Figure 4; Tomlinson 2008). Yet there is a difference between identifying a problem and creating strategies to target it. For policy to spur genuine results, adequate research examining how urban populations uniquely experience the epidemic needs increasing attention.
In regards to developing a more urban-centric approach, the first steps have already been taken. Many professionals involved in HIV/AIDS prevention understand change needs to be spurred by the affected local communities. However, the overall lack of attention paid to these local municipalities in the first place reduced their chances of effectively implementing prevention strategies. HIV/AIDS prevention usually requires large changes in city infrastructure. Increased sanitation and water facilities must be provided, waste removal delivery must become more coordinated, treatment facilities must be built in areas to serve as large a portion of the population as possible, and households must be able to pay for their increased health services.
Not only does this mean giving out more contraceptives and medicine, this means creating more jobs, building more houses and formal community areas, and delivering health services more efficiently. These development plans place huge demands on local governments, who simply do not have the capacity nor funding to make such changes. A large part of the blame for weak municipalities is attributed to the way in which they have been structurally ignored for so long, in favor of regional and national entities. For example, the South African government's National Strategy Plan proclaimed that all local governments enact mainstream, integrated HIV/ AIDS development plans within the next five years (Centre For Development and Enterprise). Yet the South African government failed to consider that the budgets of these municipalities were not large enough to even recommend, let alone implement, such programs. Some municipalities have been more successful than others in service delivery. For example, the Johannesburg municipality stands out as a key example of power and influence in ground-level interventions. Yet Johannesburg also has the benefit of zero growth rates, higher reporting levels, and a larger governmental capacity than most cities (Corrigan 1998). In order to achieve such success in other cities, such as Durban, a city that still struggles with a prevalence rate of almost 40% (Ramjee et al. 2012), policymakers must change the way they view local-level capacity. With more accountable reporting rates, increased coordination between national and local governments, and viable, long-term strategies for local governments, cities can lower infection rates while extending treatment to a larger portion of the affected population.
The field of development still faces many challenges in the realms of quality of life, education, and healthcare, as detailed in the South African case study. This discussion section is devoted to assessing what progress has been made thus far on integrating city-specific data into the field of international development. In policy research, Both domestic as well as international think tanks have made headway in understanding how increasingly important cities are for economic growth. Yet aside from the reports, it is unclear how much attention and influence has really been generated. South Africa's most prestigious developmental think tank, Centre for Development and Enterprise (CDE), established the need for increased city introspection in 1999 (CDE "Cities, Towns and Local Government").
CDE stressed the importance of strengthening South Africa's major cities as many still "do not have many of the necessary powers required to compete effectively with other cities in the world economy" (Bernstein 1996). Yet even in these reports, only the largest three cities are analyzed and never in comparison to one another. When think tanks do conduct research at the city-specific level, they fail to account for other factors of growth besides economics. Three US-based think tanks, the McKinsey Global Institute, Martin Prosperity Institute, and AT Kearney represent institutes that espouse an urban-specific focus. Most of their work focuses on the United States, and so when international countries are analyzed only their most powerful city is researched for economic potential. Despite statements like "the world today is more about cities than countries," few developing cities were included, and no middleweight cities anywhere, in their mainstream analysis (AT Kearney 2012). Potential was only classified along economic and political means.
Additionally, none of AT Kearney's data was published, so the only information on cities that can be gained is from what AT Kearney supplies the reader graphically. While an index such as this one may be beneficial to many in the business world, these think tanks repeatedly fail to generate substantial knowledge for up-and-coming cities. When one is able to pick out information for a scant few developing cities, this information is decentralized, economic in focus, and without accessible raw data. In the non-profit arena, non-governmental organizations such as Global Water and Oxfam overwhelmingly base projects on the country level. Under the "South Africa" country page, all of Oxfam's work is titled "Climate Change in South Africa", "Helping women farmers in South Africa" and "HIV/ AIDS in South Africa;" everything is measured in aggregate, general terms (Oxfam International).
A closer examination of these projects only clarifies that projects occurred "in South Africa's North West Province" or that Oxfam provided support for "families in four villages" (Oxfam International). Global Water is much the same. Their South African profile page only explains that shallow-well reconstruction occurred in South Africa's "northern portion" (Global Water 2009). Let it be known that this is not a failure for the organizations; NGOs such as Global Water and Oxfam do provide real, necessary support for those whom they help. What is missing is a lack of coordination, for once these specific projects are finished, NGOs provide no real data or measurements that could potentially aid future projects from other agencies (Polman 2010).
These are the organizations that have the best insider's access; they already work at the municipality level, actively interact with the population, and have viable funds and reporting methods that make data collection feasible. Yet these ground-level projects become grouped in together as one in support of overall country focus, thus blurring their importance and specific implications for specific cities and rural areas alike. Alternatively, small city-centralized NGOs only focus on developmental issues involving their respective cities. The Development Action Group's (DAG) aim is to create sustainable human settlements in urban areas, enhancing safety while spanning investment. Their local projects have achieved very high levels of success, as each specific project focuses implicitly on the community in question. Increasingly the Development Action Group has begun partnering with UN-Habitat on international reports. This is done so that their research may be projected large-scale. However, since these co-publications are international in focus, DAG is forced to apply their research to explain South Africa as an aggregate whole.
Their most recent joint publication, Land Value Capture Scoping Study, speaks only about South Africa's municipalities as a whole, meshing their ground-level research to describe South Africa in a sum of four paragraphs (UN-Habitat 2010). In the case of international organizations, many aid groups do not adequately address the unique challenges facing development in urban areas. Even in broad strategy targets for these organizations, such as the USAID Policy Frame for 2011-2015, mo mention is given to the specialized role that cities can play in achieving proposed goals, even while the organization should "nurture sustainable local institutions, systems, and capacities." ("USAID Policy Framework" 2011-2015).
The crucial take-away is clear: development research needs to be viewed from an urban, city-specific focus. The development field has identified urban hotspots as the main catalysts of growth. However, accurate, verifiable research for use in development projects is sorely lacking. While the literature broadly acknowledge the validity of urban development research, very few explicit plans and reports are being produced studying how critical indicators diverge between population distributions. To change this nation-based view of development will require a paradigm shift for the discipline of international development. This study recommends increasing the availability of accurate, verifiable data for urban entities as a first step towards solving the disparity in development research.
Such primary-level indicators include general population statistics such as population size, density and percent growth. City-descriptive statistics, including the availability of sustainable housing, costs of living, GDP per capita, and unemployment levels, should also follow. Tertiary-level data measures of city services; local municipalities must report education rates, health and health service availability, waste, energy, water, and transportation facilities, and opportunities for city growth. Finally, quality of life measurements must be accounted for in city-specific development research.
This includes indicators such as civic engagement, social equity, women's organizations, and technology and innovation rates. In turn, this city data must be used in comparison with other cities, not provinces, to understand growth patterns. Additionally municipalities need to be given their greater power to increase capacity in order to affect real change from the grassroots level. While the scope of this paper centers around South Africa as a case study, findings infer such a disparity of accurate, publically available data on urban municipalities is lacking in many nations, developing and developed alike. In our global age, it will be cities, not countries, which determine productivity and growth. Acting on this understanding is fundamental if we wish to prosper as a global society.
Janetta Deppa is a student of International Relations specializing in International Development. School of International Studies (SIS), American University.
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