Convergencia de filtros

South Africa has an estimated population of 53.4 million people as of 2015 (Worldometers, 2015). Rich in cultural and ethnic diversity the population has a wide range of languages, religious beliefs and traditions. According to Census 2011 (the latest to date), Africans (broad grouping including the Nguni, Sotho-Tswana, Tsonga and Venda populations) make up the majority of the population at 79.2%, coloured (a contentious label of people from mixed lineage) 8.9%, white people (Afrikaners, English-speakers and immigrants from the Europe) 8.9% and the Indian and Asian population (majority of South Africa’s Asian population are Indian but there is also a significant population of Chinese South Africans) at 2.5%. “Other” population group makes up 0.5% of the total (Census, 2011). At a glance the population data can be seen in table 1 below:

Table 1 South Africa's Population Census 2011 (Statistics SA, 2011)  

Of the total population mentioned above, 22,25 million people (42%) are regarded as youth (14-35 years old) (NYDA, 2013). Statistics South Africa (Stats SA) is the national statistics service of the country producing official censuses and surveys. The latest Quarterly Labour Force survey (Quarter 4, 2014) provides information on youth divided into two groups i.e. 15-24 and 25-34 year cohorts. As of Quarter 4, 2014 labour force characteristics by age groups across the country were documented as follows:

Table 2 Labour force characteristics by age group Q4 Labour Force Survey (Statistics SA, 2014: 6)  

Labour force characteristics by age group Population15-24 years Oct-Dec 2014

Unemployment rate (%) 48,8

Population 25-34 years Oct-Dec 2014

Unemployment rate (%) 29.6

Despite being a leading economy in Sub-Saharan Africa, South Africa has one of the highest youth unemployment rates in the region. In 2014 in the 15-24 year cohort unemployment was estimated at 48,8 with a slight decrease from 51,2% from January-March 2014. For the population of 25-34 years unemployment stood at 29.6% with a slight increase from 28,3% from October-December 2013 (Stats SA, 2014: 6). Understanding the magnitude and impact of the unemployment situation for young people becomes clearer in the 3 categories

unemployment is divided into: Unemployed young people are categorized as having no job, but still actively seeking employment. Discouraged groups have given up hope of seeking a job, because they feel that their efforts are of no consequence. Those inactive are not

involved in any activities that are linked to economic activities. Another important consideration is the number of young people neither in employment, nor in education or training (NEET). Many countries across the world are experiencing an upward trend of NEETs particularly since the start of the financial crisis in 2008.

Disparity across provinces

In South Africa equality and opportunity is spread disproportionately across the 9 provinces contributing to disadvantaged states of young people. South Africa experiences regional disparities, which can be characterized as a rural-urban divide and an urban underclass (Linford, 2011, para 2). To understand the stark contrast across regions and their implications

for access to opportunities, figures have been collected in table 3 below. These figures use the expanded definition of unemployment, which includes people who have stopped looking for work. Unfortunately statistics for youth by age and province were not included in the survey. However taking account the trends by province gives further insight into understanding the socio-economic contexts of young peoples’ experiences.

Table 3 Labour force characteristics by province Q4 Labour Force Survey (Statistics SA, 2014: 8)  

Labour force characteristics by province Population 15-64 years Oct-Dec 2014

Unemployment rate (%) Western Cape 22,9 Eastern Cape 29,1 Northern Cape 28,7 Free State 32,2 KwaZulu-Natal 20,8 North West 25,2 Gauteng 24,6 Mpumalanga 26,6 Limpopo 15,9

Severe economic disparities characterize South Africa and this is connected to geographical inequality. The differences that mark the provinces such as poverty, access to services and geographical isolation can lead to small homogenous networks, create instances of poor self- esteem and can fuel social, racial and gender prejudices. In South Africa inequalities have a high correlation to race. The Apartheid regime’s (1948-1994) concern with the wellbeing of the white population; reserving decent, well-paying jobs for whites and improving the economical situation for poor white people. The widening gap especially affected the black African population as the government ensured that the majority of black Africans were limited to lower-level jobs. In addition, educated black people could not find decent work opportunities. Shifts in the labour market in the 1970s for jobs that required little education particularly in the mining industry left many non-white people without work. These factors partly still account for the inequality within races in the history of South Africa and continue to be felt in the present day.

With the end of apartheid in 1994, the educated non-white population was given the opportunity to gain substantive employment. “However, the vast majority of the black population still suffers severely from lack of marketable skills. Such discrepancies will continue to be felt in the next generation, as levels of education vary tremendously among social classes” (Linford, 2011, para.10). Affirming this prediction, the recent Stats SA 20 year review of skills and youth unemployment shows that black Africans have fallen behind in enquiring skills in the period from 1994-2014. While the report shows that during the period there has been a shift from low skilled to semi-skilled and skilled-work, higher percentages were still in semi-skilled occupations (clerks, craft and related trades and

machine operators) and only a slight decrease was noted in low-skilled work (elementary jobs and domestic work) within the South African workforce. “An examination of the data also revealed little movement towards skilled employment among the black African

workforce…showing only a slight movement towards skilled occupations” (Stats SA, 2014, para. 3). When Stats SA applied the analysis to age groups “…data show that there has been a shift towards skilled work in all age groups within the four population groups, with the

exception of black Africans aged 25-34 years. In 1994, 17% of black African youths aged 25- 34 occupied skilled occupations. In 2014, this decreased to 15%” (Stats SA, 2014, para. 4). In light of such a review, the country will no doubt be placing greater emphasis on addressing effective skills development. It is therefore a crucial moment to broaden the parameters of youth development and critically evaluate how we do skills development. This will be addressed throughout this work.