This paper discusses Patterns and motivations of Code Switching among male and female speakers of different ranks and age groups in Nairobi. The main objective is to examine the influence of Variables such as Gender, Rank and Age group in Code Switching and Code selection. The researcher tape-recorded spontaneous speech from the respondents, then the tape recorded data was transcribed on paper and the extracts from the transcribed text were analyzed based on the tenets of Speech Accommodation Theory and Markedness Model. The study has revealed that speakers Switch Codes in an attempt to exhibit their level of confidence, domination and also when they desired a need for social integration and approval. The various groups; Male and Female, High and low Rank are consequently found to use these Codes in different ways. It was therefore realized that each of the Codes has a specific function and social symbolism to each individual group in different contexts.
Well-functioning business sectors are crucial driving forces for economic growth. In developing countries, entrepreneurship can function as a tool to fight poverty as well as to strengthen the role of women and promote gender equality. This study used the sample size of 132 women entrepreneurs from the three districts in Dar es Salaam city; Simple random sampling was used in sampling the women entrepreneurs in Dar es Salaam city in Tanzania. A Pearson's correlation was employed in this study. SPSSv16.0 software was used to generate thePearson's correlation coefficient. The findingshowever reflected as, there is a correlation between threats and weakness is at Pearson's correlation coefficient (r) equals .421**correlation is significant at the 0.01 level (2-tailed) and p < .000, opportunities and weakness Pearson's correlation coefficient (r) equals .388**, correlation is significant at the 0.01 level (2-tailed) and p < .000 , strengths and opportunities Pearson's correlation coefficient (r) equals .245**, correlation is significant at the 0.01 level (2-tailed), p < 0.05 on the other hand there was weak correlation between strengths and weakness, Pearson's correlation coefficient (r) equals .089, p < .309 which indicates that the coefficient is significantly where the (r) is lower than the P value. Strengths and threats Pearson's correlation coefficient (r) equals .038, indicating that there is a weak relationship in terms of correlation. p< .667 . We can conclude that there is a correlation between weakness and threats, opportunities and weakness, strengths and opportunities. There is a weak correlation between opportunities and threats, strengths and threats.Recommendations that the government and Non-governmental organizations should open training programmes for women entrepreneurs based on their needs. Finance be made available to enable them to access business development and other services.
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