3.1 Introduction 59
4.6.3 Content analysis of the verbal text 105
I conducted content analysis of the verbal text using a quantitative technique. As such I first developed a data analysis instrument with pre-determined categories for coding and analysing the data (Ary et al., 2002; Leavy, 2007; Wilkinson &
Birmingham, 2003). Refer to Appendix D in the Appendices section for the content analysis tool of the verbal text. The instrument had three categories, each with a set of criteria for coding the verbal text. The three categories were: representation of women mentioned, frequency of mentioning women and sections where women were included in the text. These categories were aimed at addressing the research question under study namely “how women are portrayed in the textbooks”. This is in keeping with the characteristic of content analysis as argued by Leavy (2007) and Wilkinson and Birmingham (2003) namely that the categories developed depended on the phenomenon under study and the research question.
Once the tool was finalised, I also pilot tested it with the same textbooks mentioned in section 4.6.1. After the pilot testing, I prepared myself for coding by first of all reading through the data in all the three textbooks. McMillan and Schumacher (2001, p. 464) argue that, “intensive analysis usually begins with the researcher reading all of the data to gain a sense of the whole …” This was also done in order to familiarise myself with the data considering that content analysis deals with data that is pre- existing i.e. data which was produced by someone else other than the researcher (Leavy, 2007). After the preparatory reading, I began coding and analysing the data
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in steps, category by category, as content analysis by nature is systematic and follows a clear and straightforward process (Cohen et al., 2011; Leavy, 2007;
Wilkinson & Birmingham, 2003).
I read again each textbook chapter by chapter generating data for the first category in my instrument which dealt with the representation of women mentioned in the text.
As I read through each chapter, I noted the names of women and men mentioned in the text. I included men in this analysis because I wanted to establish representation of women in relation to their male counterparts. Names which were repeated were highlighted and recorded only once upon the first appearance. I highlighted names of men in the text in red and those of women in blue and also listed the names in my notebook. There was no criterion for the choice of colours; it depended on the highlighters that were available. I compiled the data in tabular form with three columns and the number of rows depending on the number of chapters of each textbook. The three columns of the table were labelled by chapter, and women and men mentioned. Therefore as I read through every chapter, I recorded in the table the names of women and men I discovered in the text while also highlighting those names in the textbook with the two different colours mentioned above. I also recorded page numbers where the names were found in the text. Refer to Appendix E for an example of one of the three tables used to record the data (from Textbook A). After reading each chapter, I checked the names listed in each column against those highlighted in the text to verify that I had captured the data correctly. I then counted the names in each column and recorded the total for each chapter. I also counted the highlighted names of women and men in the text and cross-checked with the totals obtained in my list. The page numbers indicated in my notes, as well as the highlighting of the names in the text, helped with this cross-checking exercise as it facilitated the location of the names in the chapters. The cross-checking exercise was done repeatedly in order to establish credibility of the findings which, among other procedures, is achieved through prolonged engagement (Babbie &
Mouton, 2001). After I compiled data for all chapters and recorded totals for each chapter, I then added up all the figures for the chapters in each column to indicate the total number of women and men mentioned in the text in the entire textbook.
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The second category dealt with the frequency of the mention of women in the text.
To compile data for this category, I again read through the text chapter by chapter highlighting names of women and men whenever they were mentioned in the text. I used the same colours used for the first category. I also recorded all the instances when names of women and men were repeatedly mentioned in the text. This is unlike the procedure in the first category where a name was highlighted and recorded only once upon first appearance. The aim was to establish the frequency of referring to women and men mentioned in the text. I organised the notes in tabular form which had three columns, indicating chapter, women and men. Refer to Appendix F for an example of one of the three tables (from Textbook B) used to record the data on frequency of referring to women and men. A name that was mentioned several times was highlighted every time it appeared and also listed for all the instances including the pages where it was mentioned. At the end of each chapter, the number of times names of women and men were mentioned were counted and recorded. I also cross-checked the totals of each category by counting the highlighted names in the chapter to ensure that every repeated mention of a woman or man was recorded and counted. Finally, I added up the total number of repeated mention of women in all the chapters to tally with the grand total of times of mentioning women in the text. I also summed up the total number of times to which men were referred. The last step was to calculate the averages of the number of times when women and men were mentioned in the text and to interpret the meaning in terms of portrayal of women.
The third category dealt with sections in the sampled textbooks where women are included in the text. For this analysis I firstly focussed on the table of contents. I read through the table of contents and recorded the topics that specifically mentioned women and those that dealt with men. I then counted the total number of topics that I had recorded for each group and I verified the totals by counting again straight from the tables of contents. Subsequently I interpreted the results based on the total number of topics featuring each gender group. Secondly I examined the topics and subtopics in the text by reading all the topics and subtopics and listing those that featured men as well as those that featured women. Finally I counted the topics and subtopics that reflected women and recorded the total and did the same for topics and subtopics that featured men. A conclusion was then drawn based on the results.
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After analysing the topics and subtopics in the tables of contents and the text, I proceeded to examine how the narrative text included women. I read through the text again chapter by chapter highlighting those sections which made reference to women whether by name or not. Immediately after highlighting a section, I copied it down in my notes indicating the chapter and page number where the citation was lifted from. I highlighted the sections where women were discussed in yellow. After reading each chapter, I cross-checked the citations copied down with the sections highlighted in the text so as to ensure that all sections were highlighted and noted.
Refer to Appendices G, H and I for lists of the citations from each of the three textbooks. Having compiled data for all the chapters in a textbook, I analysed the sections by counting them to arrive at a total. I also analysed the sections in terms of number of sentences and paragraphs that discussed women. Finally, I interpreted the meaning of the results in terms of the portrayal of women. In the next section I explain how the data generated from the content analysis as contained in Appendices G, H and I was analysed by means of open coding.