Group 4 ( Activity 2)

 Activity 2 

Qualitative data Analysis

Coding identified metaphors in more than half of the transcripts. Respondents used non-literal descriptions when discussing topics that may involve emotion, such as distance (e.g. ‘another planet’), connection (e.g. ‘blood ties’) and surprise or impact.

Coding Respondents appeared to use several terms when indicating whether individuals were members of their household or not. Interviewees used terms as ‘being family’, ‘having blood ties’. Several found sharing a roof, sharing income, or expenditures, sharing food or household chores justification to include people in the category ‘household’. In several cases, household membership was related to feeling responsible.

After the coding was done, the rules of inclusion and exclusion used by the interviewees were classified into categories of Membership Categorization Devices, given in the first column of Table 1.

Table 1 Membership Categorization Devices (MCD) to include or exclude someone as household member

MCD

Terms used by interviewees

Remarks

Being family

having blood ties married descendants of grandfather

 

Sharing

a roof, food, income expenditures, decision making, care taking, household chores.

Being present is a criterion to include, being absent not necessarily a criterion to exclude

Emotional criteria

feeling responsible

Often related to one of the other criteria

Cultural criteria

she feels like family” in our culture…

In particular used by interviewees who mentioned awareness of the existence of different definitions of household

 

Coding When talking about their household, interviewees referred to the sharing of several aspects–sharing a roof, food, income, expenditures, time, household organization– and to the signifcance of households, including feelings of connectedness and emotional aspects. Terms used were, for instance, “the people who live together”, “who share food”, “who live under the same roof”; and: “it is an emotion”, “it is protecting”, “it is important”, “it is the ‘holy thing’”. Or: “the meaning of life”. Also mentioned: “It is the place where I feel important and valuable”.

MCA produced a list of criteria (Membership Categorization Devices) that justify classification of individuals with respect to their membership in the category ‘household’. It gave the authors a new understanding of respondents’ public construction of their understanding of relationships. Significantly, interviewees’ notions of ‘household’ were mutually inconsistent and many interviewees used more than one device (e.g. blood and familiarity) when determining membership in their household.

 

Figure 2


In the analysis phase, cover terms were defined and the folk terms were related with semantic relationships to these cover terms. In some cases, the cover terms were divided into sub-terms, for instance ‘sharing’ is subdivided into sharing a roof, sharing expenditures, etc. Figure 2 presents the result of both the coding phase and the analysis phase for the domain ‘Household’. In Fig. 3, the content types (cover terms) and expressions (folk terms) of the domain ‘Communication’ are shown.

 Figure 3


 

 

Content analysis, as conducted here, was counting the number of times the terms determined to be relevant appeared in the text. Although not presented here, analysis may be continued through the use of theoretically motivated descriptive and correlational statistics which would be then reported according to the norms governing reporting of quantitative analysis. We were able to report this analysis method transparently because its operation relied on deductive application of a clearly declared coding scheme. In our example, the content analysis gave information on household composition, what households shared, ICT-tools used, and frequency and duration of communication with those tools. The results of content analysis, domain analysis and MCA may usefully be presented in the form of a table or graph and in this article we showed examples of both. The graphs were produced within a qualitative data analysis program


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