Data analysis

Before analysing the data, all recorded interviews were transcribed. “A transcript is a translation from a narrative mode, oral discourse, into another narrative mode, written discourse” (Brinkmann & Kvale 2015 p. 204). Although during the transcriptions the tones of voice or intonations and other relevant interview aspects may be lost (ibid); all the video recordings were watched as many times as necessary to capture and write down all the information mentioned by the participants during the interviews, including the exact wording, pauses and confirmation of answers when the online connection presented problems. The transcripts were initially separated according to case study and then to target groups. Each participant, depending on the case study and group, was named with a pseudonym to be anonymized, as shown in Table 4 and Table 5.

Table 4: Farmer pseudonyms Source: Author

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Table 5: Other study participant pseudonyms Source: Author

The first case study was named Seed security responses and humanitarian action and the following groups were designed: NRC field staff from Uganda, female and male Ugandan refugee and host community farmers, Ugandan seed traders, Ugandan key informants and other key informants. The second case study was named Seed security responses and long-term development and the following groups were designed: DF field staff from Malawi, female and male Malawian farmers, Malawian key informants and other key informants.

The transcripts were made as the interviews were carried out from September to December 2020. The aim of transcribing simultaneously while developing the interviews was to organize the data for analysis to avoid overwhelming volumes of raw data at later stages (Berg & Lung, 2012 and Bryman, 2016). Furthermore, transcribing directly after the interviews made it possible to begin preliminary analysis (Maxwell, 2013). Transcripts were subsequently read as recommended by Maxwell (2013) based on Emerson et al., 1995, and analysed to highlight significant remarks (Bryman, 2016). Simultaneously, notes taken during the interviews were added to the transcripts and memos with possible codes, categories and relationships were created.

Field interviews conducted with support of research assistants were translated and transcribed by them. In the case of NRC, the interview transcripts were uploaded in real time to an online platform. No printed documents were generated for NRC, and I was the only one with access to read and download the data. In the case of DF, I received scanned pdf-transcripts and rewrote them to review the answers and categorize the information. Participant's names were not recorded in the transcripts done by the NGOs. The research assistants in both countries were contacted to clarify the answers given by the small-scale farmers when necessary while creating initial notes, memos, and preliminary codes.

33 After transcribing and adding of notes, conventional content analysis was used to analyse the data. Content analysis is defined as a "careful, detailed, systematic examination and interpretation of a particular body of material in an effort to identify patterns, themes, biases, and meanings" (Berg & Lune, 2012 p. 349). Content analysis involves the coding of categories derived from raw data, to reduce and code it to make the information more accessible and understandable to extract themes and patterns (ibid). Coding categories were developed deductively and inductively. The deductive approach, also known as directed content analysis, was used because it involves implementation of analytic codes derived from exiting theories and explanations relevant to the RQs (Berg & Lune, 2012). Coding categories and themes were created based on the seed and food security frameworks. The inductive approach, also known as conventional content analysis, was used for the creation of other coding categories derived directly from the raw data itself (Berg & Lune, 2012). When reading the transcripts, codes that did not yet belong to any theory emerged and were placed in groups relevant to answer the RQs. This approach originated from the grounded theoretical approach (ibid) and prioritizes the importance of allowing theoretical ideas to emerge from raw data (Bryman, 2016).

Moreover, the creation of codes was a way to answer the RQs (Berg & Lune, 2012).

The analysis was conducted manually using hand-coding. Initially, several codes were identified and represented with an individual colour. Each code had subcodes to guarantee that all relevant information to a certain code was included when the transcriptions were reviewed.

Afterwards, the related codes were grouped and classified into categories to create the themes.

Then, each transcript was revised to identify statements for code classification. As stated by Berg & Lune, (2012) main transcript elements can be counted when textual content analysis is developed. Each colour code was examined for repeating words and phrases, recurring patterns describing perceptions or ideas, trends, relationships, commonalities, deviations, or concepts.

Although some participants used different words to express their experiences, the meanings were similar. During the transcript review, I counted the number of participants who mentioned certain statements, concepts or ideas, as well as the frequency with which each participant mentioned certain statements and under what context. The use of numbers in itself does not turn a research study into mixed methods, but numbers give precision to descriptions of particular phenomenon (Maxwell, 2010).

After colour-coding, similarly coloured statements were transferred to a matrix where the codes were arranged and combined with the data obtained from the transcripts to provide in-depth

34 detailing for triangulation of each code. Subsequently, patterns and common trends were identified to answer the RQs. Lastly, a summary of each main finding was made by theme and by case, including also main characteristics of the findings. The final matrices contained the RQs, codes, subcodes, themes, detailed descriptions of the main findings for each theme and quotations that emphasized and captured the emerging themes.