PROYECTO PARA LA SOLUCION DEL PROBLEMA CON REFERENCIA AL CODIGO DE TRABAJO

Secondary research involves a search for existing data on a research subject. It is usually consulted to enlighten the researcher on what has been done and what is still left to do or how to improve what has been done. Secondary data sources are found in archival publications, statistical systems, scholarly publications or unpublished data obtained either online or in physical form (Whitehead, 2005).

I used secondary data to get an idea of the geography of the place and to familiarize myself with studies already done on urban agriculture in Ghana, Africa, and in other places around world. After collecting the preliminary data, I returned to Germany to read more sec-ondary literature and analyze the preliminary information I had obtained. Secsec-ondary data sources were employed to contextualize the data. Secondary data was obtained from the ar-chives in Tamale courts in Accra and Tamale, unpublished and published data from libraries and online, Ghanaian land laws and also letters to land agencies on land conflict related mat-ters. The following section explains the sampling method used for this study.

3.5 Sampling

This research was carried out in urban and peri-urban vegetable fields in Tamale. The terms urban and peri-urban are ambiguous and defining them is not easy. When one thinks of urban images of a developed or built up area with good transport network and high population density comes to view. However, this is not necessarily the image in many urban areas across the African continent. According to Andranovich and Riposa (1993), an urban area is character-ised by a dense population, social networks, high concentration of living spaces and a variety of economic activities. The population size usually ranges from 2500 to 50,000 people. Ac-cording to Drechsel et al. (2006), Adam (2001) and Moustier (2001), urban areas are consid-ered administrative centers. Drescher and Iaquinta (2002: 5) went further to define urban ar-eas as a “statistical concept defined by a country’s government.” This definition leaves a lot of room for flexibility although it most likely takes into account features regarding population size, density, political and economic activity.

Peri-urban areas have been defined in Chagomoka et al. (2015a) as areas not more than 40km from the urban center. Adam (2001) proposes a similar range of 30-40 km from a city center and Moustier (2001) argues for a 50 km distance from the city center. Simon et al.

(2006) refer to peri-urban areas as a dynamic interface between the urban and rural area with no particular reference to its geographical location. In this study, I consider an area urban or peri-urban in the same vein as Laquinta (2012); that is, based on its classification by the gov-ernment and in this case the Ghanaian govgov-ernment. All vegetable sites in urban and peri-urban Tamale were identified through snowball sampling, with city officials and staffs at the

University for Development Study (UDS), I identified other sites. When I got to these other sites through more interviews and focus group discussions, I was informed about the existence of additional vegetable that I was unaware of. Altogether, I identified twenty open space dry season vegetable sites and two irrigation sites as shown in chapter 6. Key informants for in-depth interviews were selected purposively. Case studies were built from the data obtained from in-depth interviews, informal conversation, focus group discussions, and secondary liter-ature.

When new information came up, I adjusted the participant’s list by adding new inform-ants to my research list Key informinform-ants in the government sector were selected for interviews as a result of their interactions with farmers in accessing agricultural resources like land, water, and seed. Information about them was obtained through snowballing with farmers, non-gov-ernmental organizations and the Regional Agricultural Ministry. Information on non-govern-mental organizations associated with agriculture was obtained from UrbanFood^Plus partners in Tamale including UDS and my assistants. Through conferences at UDS, I also received addi-tional information through presentations and discussions with other colleagues working on urban agriculture in Tamale. I targeted mostly sub-chiefs and regents in my attempt to gather information about land use and management because of the unnecessary bureaucracy in meeting with district chiefs. Also, informal conversations with community elders revealed that sub-chiefs and the linguist of the local chiefs had more information on how land is transacted than the district chiefs themselves. This, according to them, was s due to a Dagbon custom that physical restrict the district chief to certain areas. This means physical land transactions are done mainly by secretaries, relatives and linguists of chiefs. Information on how spatial data was sampled can be seen in section 3.3.3.7.

By using a mixed method, I gained an extensive understanding of both methods and avoided the problems associated with using only one method. This technique also provided a possibility for triangulation which allowed me to identify aspects of phenomenon more accu-rately by approaching them from different angles. The next section explains how data collected was analysed during and after field work.

3.6 Analysis

Analysis was done from an emic perspective in which an inductive reasoning (see section 3.3.1) was used to identify relevant patterns, categories, and relationships through a process of discovery of participants` views as prescribed by Schutt (2012). Here, I was interested in analysing cases in the research project as wholes and not as since the whole is larger than the sum of its parts. The analysis started from the data collection stage and continued through-out the research process.

I took notes and made conceptual inferences as data was collected. Interview record-ings were mostly transcribed personally in order to immerse myself into the data. Due to a continues self-analysis of my work, information from interviews and informal discussions were later reexamined during focus group discussions and vice versa to compare data gotten and recheck meanings attached to descriptive data. The aim of this activity was to ensure that the data best described the social realities of the farmers as communicated by them.

This process or what Parlett and Hamilton (1976) and Sinkovics and Alfoldi (2012) refer to as progressive focusing was repeated throughout the research process. After the pro-cess was completed, important themes and concepts contained in the notes and descriptive data were identified and continuously refined as new information emerged. For example, through discussing preliminary data with colleagues on and off the field, the information I re-ceived gave me new ideas about what to look for next time I was on the field. Through this process, new ideas and information cropped up modifying old themes and concepts as ex-pected by Anderson (2003; Maxwell, 1996).

New themes and concepts were continuously refined to fit new information obtained till the researcher gets to the point of theoretical saturation. Theoretical saturation here does not only entail reaching a point where the researcher has ‘heard it all.’ According to Morse (2015: 587), theoretical “saturation is the building of rich data within the process of inquiry, by attending to scope and replication, hence, in turn, building the theoretical aspects of inquiry.”

Data was analyzed as per Figure 3.7 below.

Figure 3.7: How data was analysed

Source: Adapted from Miles and Huberman, 1994

To reach data saturation I explored all the aspects of the phenomenon under study and use open-ended questions to collect data from farmers, government officials, traditional authorities, and non-governmental organisations. Data from different informants validated same ideas as I studied my notes and transcripts in the field. Theories and concepts devel-oped were used as a tool to check for gaps in data collection and more data was collected and new themes were contextualised in the event of a gap at any junction. This continuous process of data processing, analysis, and verification (with participants) made this research work theoretically saturated with relevant and fully developed theories.