Plate 9.5: Gas Welders Working along Madzindadzi Road
3.5 Population and Sampling Procedure
This section explains sampling techniques and the technique used to collect data on informal manufacturing. Details are specifically given on how and why informal manufacturing, specific study sites, key informers and respondents were chosen.
3.5.1 Selecting Informal Manufacturing
Informality within Zimbabwe and other places is cross sector visible (Miraftab, 2009; Dube and Chirisa, 2012; Majumdar and Borbora, 2012; Shah, 2012; Varley, 2013). Informality is found at tertiary, secondary and primary levels of production. In comparison to other levels of production, the secondary production level generates huge volumes of activity and employs a substantial amount of people (Hart, 1973; Despres, 1988; Sparks and Barnett, 2010;
Mazongonda and Muromo, 2011; Majumdar and Borbora, 2012). As such, this study purposively selected informal manufacturing, in the secondary level of production, because it accounts for a larger proportion of activities in accordance with level and value of trade.
3.5.2 Selecting Study Sites
Thorough information on the geographical location, pattern of activities and growth strides of three home industries studied is represented in Section 1.5, Note on Study Areas. Reasons on why the studied sites were selected follow Figure 3.4 which shows the geographic location of selected study sites in Harare.
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Figure 3.4: Location of Study Areas (Google Map, 2016 on Google Earth Extract)
In studying informal employment in Brazil’s three cities, it has been reasoned that the cities in question were purposively chosen based “upon their regional location, the different socio and cultural origins of their working-class populations, and the point that each city revealed a somewhat different pattern of urban-industrial and population increase” (Despres, 1988, p. 6).
Inspired by this ground-breaking work on comparative research of informality, the current
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study used three home industries in Harare (Despres, 1988). The reasoning behind the selection of the sites in question followed the conclusions in existing literature about their large sizes, and differences in industrial pattern of activities and geographic location (Mazongonda and Muromo, 2011; Muponda, 2012; Uzhenyu, 2015).
Among other home industries in Harare, Gazaland, Siyaso and the Complex attract huge volumes of activity (Jerie, 2013; Masarirambi, 2013; Uzhenyu, 2015). As such, studying the three sites, arguably gave an indicative picture of issues surrounding informal industries in Harare. Furthermore, purposively choosing three different sites partly enabled the comparative examination of practical realities across sites as there are differences according to industrial activities between and within study sites. For example, Gazaland, has been described as “a conglomeration of small businesses involved in a plethora of activities such as sheet metal fabrication, light engineering, motor vehicle maintenance and repairs, spray painting and panel beating among others in the retail business like the supply of vehicle spare parts and general merchandising” (Muponda, 2012, p. 2).
3.5.3 Selecting Interviewees during the Survey: Informal Operators
The description of Gazaland in the preceding chapter is a reflection that a complicated mixture of activities takes place in a home industry. In that regard, the survey of informal trade operators largely relied on references to identify operators in informal manufacturing. References to other operators made it easy to utilise the spatial setting and assumed positive association between manufacturers in establishing the trade flow network connecting informal operators. Use of probabilistic sampling methods like simple random sampling could not yield intended results since numerous activities, including non-manufacturing activities, happen in home industries.
Because this research is focussed on manufacturing activities, specific emphasis was paid on
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avoiding accidentally choosing non-manufacturing operators.
To this effect, this study relied on a census blocks because the intent was to survey all manufacturers in each sampling window. The enumerators interviewed one and the next in a row. Enumerators came back for those not present. It is crucial to observe that the survey was exhaustive in nature, that is, all manufacturers in three sampling windows were surveyed as prescribed by the sampling design of spatial point patterns (Baddeley, 2010). This concept of census blocks (that is, analysing all units of analysis) was made use of in the city of Buffalo, New York (see Section 2.9.3) to identify and map deprived areas where access to grocery foods was restricted due to impoverishment (Lee and Lim, 2009).
3.5.4 Selecting Key Respondents during Ethnography: Informal Operators
Site key respondents were established through references to one person from at least five operators in a home industry. Number of years an operator has worked in a certain home industry and spontaneous leadership were used as the criteria to establish site key respondents.
For example, the reception given by Mupostori (a key informant working in Gazaland whose role is discussed in Sections 3.6.1 and 5.3) when the researcher first visited Gazaland in November 2014, and spontaneous leadership skills he demonstrated at the duration of the field work made him a key informant. Through his links and network, Mupostori referred the research scientist to many other influential manufacturers working in Gazaland.
3.5.5 Selecting Key Respondents: End Users and Practicing Planners
Inspired by Sections 395 to 400 of the 2014 Mid-Term Fiscal Review, the informal trade sector database “will be distributed to micro-finance institutions, banks and ZIMRA” (GoZ, 2014a, p. 97). As such, to establish and structure the data needs of different end users, purposive
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sampling was employed to ascertain main respondents. Key respondents were taken from the ZIMRA, banks, micro-finance institutions, Harare City Council, and MSME. Upon approaching these organisations, it was much easier to ascertain the key respondents because references were made to individuals who are mandated to handle urban informality issues.
After designing the database according to identified user needs, planning practitioners were purposefully selected to provide feedback on the implication of the database on planning law.
Among the six selected practitioners were one High Court of Zimbabwe judge (who handled planning law cases since 2004 when she was a judge at the Administrative Court), selected town planning assessors with the Administrative Court, and former Deputy Director of the Department of Physical Planning (DPP) in Zimbabwe. These planning experts were selected since they are daily exposed to planning related issues. As such, they have experience and expertise in handling and interpreting planning law.