Report 1

Status of Youth Unemployment, Skills and TrainingStatus of Youth Unemployment, Skills and TrainingStatus of Youth Unemployment, Skills and TrainingStatus of Youth Unemployment, Skills and Training
Needs in the John Taolo GaetseweNeeds in the John Taolo GaetseweNeeds in the John Taolo GaetseweNeeds in the John Taolo Gaetsewe DistrictDistrictDistrictDistrict
Municipality:Municipality:Municipality:Municipality: AnAnAnAn Audit and Policy TasksAudit and Policy TasksAudit and Policy TasksAudit and Policy Tasks
Compiled by
Yaw Johnson Arkaah
for
KgateloKgateloKgateloKgatelo----Pele InstitutePele InstitutePele InstitutePele Institute
Mafikeng, South AfricaMafikeng, South AfricaMafikeng, South AfricaMafikeng, South Africa
DeceDeceDeceDecember 2011mber 2011mber 2011mber 2011

i
Contents
1 Introduction 1
1.1 The John Taolo Gaetsewe Developmental Trust 1
1.2 What is the Skills Audit? 1
1.3 Purpose of the Audit 1
1.4 Scope of Audit 2
1.5 Implications of Findings 2
1.6 Percentage Youth Unemployment (18-35 Years Old) in Relation to IEC Database 2
1.6.1 Percentage Youth Unemployment: Comparison by Municipality 2
1.6.2 Percentage Youth Unemployment: Comparison by Ward and Gender 5
2 Characteristics of Participants 6
2.1 Participant Distribution by Municipality 6
2.2 Ga Maraga Municipality 11
2.3 Ga Segonyane Municipality 12
2.4 Joe Morolong Municipality 12
3 High School Grades Completed 14
3.1 Highest High School Grades Completed 14
3.2 Highest High School Grades Completed by Municipality, Gender and Age Group 15
3.3 Completion of Grade 12: Distribution by Ward 16
3.3.1 Ga Maraga Municipality 16
3.3.2 Ga Segonyane Municipality 18
3.3.3 Joe Morolong Municipality 18
3.4 High School Grades Ever Completed (Cumulative Distribution) 18
3.4.1 Distribution by Municipality 19
3.4.2 Distribution by Gender and Age Group 20
4 National Certifications Acquired 22
4.1 Introduction 22
4.2 Core National Vocational Certificates Acquired 22
4.2.1 Levels of Core National Vocational Certificates Acquired by 22
4.2.2 Core National Vocational Certificates Acquired by Municipality 24
4.2.3 Core National Vocational Certificates Acquired by Gender and Age Group 25
4.3 Elective National Vocational Certificates: Elective Courses Acquired 26
4.4 Elective National Vocational Certificates Courses Acquired by Municipality 27
4.5 Elective National Vocational Certificates Courses Acquired by Gender 28
4.6 Elective National Vocational Certificates Courses Acquired by Age Group 29

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5 College-Technikon Certifications Acquired 31
5.1 College-Technikon Diplomas Acquired 31
5.2 College-Technikon Diplomas Acquired by Municipality 31
5.3 College-Technikon Diplomas Acquired by Ward 32
5.4 Description of National Diplomas Acquired: N4, N5 and N6 34
6 Higher Academic Qualifications Acquired 36
6.1 Higher Qualifications 36
6.2 Higher Qualifications Acquired by Municipality 36
7 Further Training Areas 39
7.1 Training Interests 39
7.2 Preferred Training Areas by Municipality 39
7.3 Preferred Training Areas by Ward 40
8 Employment History 44
8.1 Job History 44
8.2 Job History by Municipality and Ward 45
8.3 Description of Jobs Ever Done 47
8.4 Past Sectors Ever Worked 48
8.4.1 First Employment Sector Listing 48
8.4.2 Second Employment Sector Listing 48
8.4.3 Third Employment Sector Listing 49
8.5 Preferred Sector to Work 50
9 Audit Findings and Policy Tasks 51
9.1 Introduction 51
9.2 Key Findings of the Audit 51
9.2.1 Educational Levels of Youth 51
9.2.2 Skills and Training Levels of Youth 51
9.2.3 Employment History/Experience of Youth 52
9.2.4 Youth and Training Preference 52
9.2.5 Youth and Employment Preference 53
9.3 Potential Consequences of Audit Findings 53
9.3.1 Deepened Unemployment 53
9.3.2 Future Employability 53
9.3.3 Lack of Income 53
9.3.4 Entrenched Poverty 54
9.3.5 Inequality 54
9.3.6 Social Ills 54
9.3.7 Community Economic Development 54

iii
9.4 General Recommendations 55
9.4.1 Wide Publication and Dissemination of Findings to Relevant Role Players 55
9.4.2 District Skills Information Management System 55
9.4.3 Matric Mathematics and Science Improvement Programme 56
9.4.4 Role of National Youth Development Agency 56
9.4.5 Forged Partnerships to Provide Training and Skills Development 56
9.4.6 Better Coordination of Training and Skills Development Initiatives by the
Mining Sector 57
9.4.7 Working in Collaboration with Government Departments and Department
of Labour 57
9.5 Conclusion 57

1
1 INTRODUCTION
1.1 The John Taolo Gaetsewe Developmental Trust
The John Taolo Gaetsewe Developmental Trust was established in April 2002 (reg. IT.2728/
2002) by Tiso Group Limited as a donor, mainly to carry out public benefit activities in a non-
profit manner. The JTGDT is a beneficiary of Sishen Iron Ore Company (SIOC) Community
Development Trust. The trust is also supported by Ntsimbintle (PTY) LTD, and other mines.
The primary objective for the establishment of the trust was to carry out public benefit activities
in a non-profit manner with a philanthropic intend. Over the years since the establishment of JTG
Developmental Trust it has engaged in a number of community development projects in line with
the five public benefit activities reflected in its trust deed; i.e. Education and Skills Development,
Health Care, Humanitarian and Welfare, Land and Housing and Enterprise Development.
1.2 What is the Skills Audit?
A skills audit is a process for identifying the skills levels of a group of individuals and assessing the
skills required now and in the future so that the skill shortfall can be determined and addressed.
The main objective for conducting a skills audit is to identify the skills and knowledge that will be
required, as well as the skills and knowledge that the group of individuals currently has. Skills
audits are also usually conducted to determine training needs so that improvement can be made
regarding the group’s skills and knowledge. The outcome of the skills audit process is a skills gap
analysis. The pieces of information gathered are meant to enable the group to improve by
providing the appropriate training and development to individuals to help address the identified
skill gaps.
1.3 Purpose of the Audit
The major purpose of the study is to ascertain the educational and skills level that unemployed
youth aged 18-35 years in the Taolo Gaetsewe Municipality have, training needs, and their
preferred sector they would like to work. The study intends to provide information on the
current state of youth unemployment in the municipality. Specifics include:
• Determining the existing skills level for unemployed youth
• Determining required skills and training for unemployed youth;
• Identifying the skills and training gaps that exist among unemployed youth;
• Identifying the sectors that most interests unemployed youth and subsequent
recommendation for training and skills development in those sectors; and
• Deriving policy tasks from the findings of the study.

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1.4 Scope of Audit
The audit covers three local municipalities in the Taolo Gaetsewe Municipality in the Northern
Province of South Africa. The local municipalities included in the study were Ga Maraga
Municipality, Ga Segonyana Municipality, and Joe Morolong Municipality. It focused on the
educational attainments and skills available in terms of numbers and profiles and the necessary
skills needed by youths in the Taolo Gaetsewe Municipality. The skills available were
disaggregated into four areas – Mining, Tourism and Hospitality, Management, and others.
1.5 Percentage Youth Unemployment (18-35 Years Old) in Relation to IEC Database
Based on the records of Independent Electoral Commission (IEC) covering the 32 wards from
three local municipalities in the Taolo Gaetsewe Municipality included in the study, 46,385 youths
aged 18-35 were registered.
• Of these 46,385 registered youths from the 32 wards from the John Taolo Gaetsewe
Municipality included in the study, 55.4% (25,681) were females while the remaining 44.6%
(20,704) were males.
Female,
25,681,
55.4%
Male,
20,704,
44.6%
Chart 1: Registered 18-35 Youths in Taolo Municipality by Gender (Source: IEC)
1.5.1 Percentage Youth Unemployment: Comparison by Municipality
Chart 1 and Chart 2 graphically display the percentages of young people from the John Taolo
Gaetsewe Municipality aged 18-35 who are unemployed relative to the IEC records.
• Overall, by interviewing 22,381 unemployed young people from the John Taolo Gaetsewe
Municipality aged 18-35 from a total of 46,385 young people aged 18-35 suggests that
nearly 43.3% documented young people in the John Taolo Gaetsewe Municipality aged 18-
35 are currently unemployed.

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• As also depicted by Chart 2, females (nearly 53.4%) constitute the largest proportion of
its unemployed youth in the John Taolo Municipality aged 18-35, relative to the IEC
record.
• As further depicted by Chart 3, Joe Morolong Municipality had the highest proportion of
its registered youth aged 18-35 who are unemployed with nearly 53.7% relative to the
IEC record, while Ga Maraga Municipality had the lowest proportion of its registered
youth aged 18-35 who are unemployed with nearly 33.2%.
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
PercentUnemployed
Percent Unemployed 53.41% 41.85%
Females Males
Chart 2: Percentage of Youth Aged 18-35 Unemployed by Gender
0%
10%
20%
30%
40%
50%
60%
PercentUnemployed
Percent Unemployed 33.16% 47.52% 53.68%
Ga Magara
Municipality
Ga Segonyane
Municipality
Joe Morolong
Municipality
Chart 3: Percentage of Youth Aged 18-35 Unemployed by Municipality

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Table 1: Comparison IEC Youth Population Information v/s Study Findings
Gender
TOTALFemale Male
IEC
Source Study
Fraction
Unemployed
IEC
Source Study
Fraction
Unemployed
IEC
Source Study
Fraction
Unemployed
Municipality Ward
810 249 30.74 914 155 16.96 1724 404 20.43Ga Magara
Municipality
Ward 1
Ward 2 703 333 47.37 518 144 27.80 1221 477 39.07
Ward 3 657 250 38.05 626 96 15.34 1283 346 26.97
Ward 4 744 333 44.76 626 104 16.61 1370 437 31.90
Ward 5 469 337 71.86 884 304 34.39 1353 641 47.38
TOTAL 3383 1502 44.40 3568 803 22.51 6951 2305 33.16
Ga Segonyane
Municipality
Ward
982 443 45.11 720 252 35.00 1702 695 40.83Ward 2
Ward 3 941 586 62.27 758 342 45.12 1699 928 54.62
Ward 4 626 486 77.64 421 238 56.53 1047 724 69.15
Ward 5 767 412 53.72 581 284 48.88 1348 696 51.63
Ward 6 700 403 57.57 557 261 46.86 1257 664 52.82
Ward 7 804 405 50.37 625 269 43.04 1429 674 47.17
Ward 8 851 436 51.23 691 252 36.47 1542 688 44.62
Ward 9 825 274 33.21 753 191 25.37 1578 465 29.47
Ward 10 964 354 36.72 695 227 32.66 1659 581 35.02
Ward 11 716 426 59.50 530 284 53.58 1246 710 56.98
Ward 12 1101 746 67.76 814 471 57.86 1915 1217 63.55
Ward 13 723 244 33.75 605 149 24.63 1328 393 29.59
TOTAL 10000 5215 52.15 7750 3220 41.55 17750 8435 47.52
Joe Morolong
Municipality
Ward
817 444 54.35 647 278 42.97 1464 722 49.32Ward 1
Ward 2 973 418 42.96 740 346 46.76 1713 764 44.60
Ward 3 834 301 36.09 661 181 27.38 1495 482 32.24
Ward 4 577 112 19.41 595 45 7.56 1172 157 13.40
Ward 5 871 545 62.57 790 311 39.37 1661 856 51.54
Ward 6 1000 446 44.60 787 333 42.31 1787 779 43.59
Ward 7 731 444 60.74 591 364 61.59 1322 808 61.12
Ward 8 794 375 47.23 567 252 44.44 1361 627 46.07
Ward 9 906 696 76.82 630 538 85.40 1536 1234 80.34
Ward 10 806 690 85.61 473 404 85.41 1279 1094 85.54
Ward 11 646 498 77.09 496 354 71.37 1142 852 74.61
Ward 12 941 726 77.15 486 442 90.95 1427 1168 81.85
Ward 13 805 568 70.56 616 344 55.84 1421 912 64.18
Ward 14 764 459 60.08 625 306 48.96 1389 765 55.08
Ward 15 833 277 33.25 682 144 21.11 1515 421 27.79
TOTAL 12298 6999 56.91 9386 4642 49.46 21684 11641 53.68

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1.5.2 Percentage Youth Unemployment: Comparison by Ward and Gender
Table 1 presents the various percentages of unemployed youth in the John Taolo Gaetsewe
Municipality in relation to IEC records.
Ward Comparison
• In Ga Maraga Municipality, Ward 5 (nearly 47.4%) currently has the highest proportion of
its registered youth aged 18-35 who are unemployed while Ward 1 (nearly 20.4%) has the
lowest proportion of its registered youth aged 18-35 who are unemployed.
• In Ga Segonyane Municipality, Ward 4 (nearly 69.2%) currently has the highest proportion
of its registered youth aged 18-35 who are unemployed while Ward 9 (nearly 29.5%) has
the lowest proportion of its registered youth aged 18-35 who are unemployed.
• In Joe Morolong Municipality, Ward 10 (nearly 85.5%) currently has the highest
proportion of its registered youth aged 18-35 who are unemployed while Ward 4 (nearly
13.4%) has the lowest proportion of its registered youth aged 18-35 who are
unemployed.
Gender Comparison
• In Ga Maraga Municipality, females (nearly 44.4%) constitute the largest proportion of
registered youth aged 18-35 who are unemployed.
• In Ga Segonyane Municipality, females (nearly 52.2%) constitute the largest proportion of
• In Joe Morolong Municipality, females (nearly 56.9%) constitute the largest proportion of
1.6 Unemployment in the John Taolo Municipality: Comparing with 2010 National
Figures
Unemployment levels of youth in the John Taolo Gaetsewe Municipality aged 18-35 were
compared with 2010 unemployment statistics for young people aged 15-34 and supplied by
Statistics South Africa (2010).
• The estimated proportion of youth aged 18-35 who are unemployed in the John Taolo
Municipality stood at 48.3% compared with the estimated 2010 national unemployment
rate of 38.0%.
With the exception of Ga Maraga Municipality (33.2%), unemployment rates of youth
aged 18-35 were higher in Ga Segonyane Municipality (47.5%) and Joe Morolong
Municipality (53.7%) than the national figure.

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• The estimated proportion of female youth aged 18-35 who are unemployed in the John
Taolo Municipality stood at 53.4% compared with the estimated 2010 national
unemployment rate of 46.6%.
• The estimated proportion of male youth aged 18-35 who are unemployed in the John
Taolo Municipality stood at 41.9% compared with the 2010 national unemployment rate
of 39.3%.
38.0%
48.3%
33.2%
47.5%
53.7%
0%
10%
20%
30%
40%
50%
60%
National
(2010)*
John Taolo
Municipality
Ga Maraga
Municipality
Ga
Segonyane
Joe Morolong
Municipality
UnemploymentRate
Chart 4: Unemployment Rates (* Estimated based on data on age interval, 15-34)
46.6%
53.4%
44.4%
52.2%
56.9%
39.3%
41.9%
22.5%
41.5%
49.5%
0%
10%
20%
30%
40%
50%
60%
National
(2010)*
JohnTaolo
GaMaraga
Ga
Segonyane
Joe
Morolong
National
(2010)*
JohnTaolo
GaMaraga
Ga
Segonyane
Joe
Morolong
Female Male
UnemploymentRate(%)
Chart 5: Unemployment Rates by Gender (* Estimated based on data on age interval, 15-34)

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2 KEY FINDINGS OF THE AUDIT
The primary intent of this study is to contribute to the formulation of better skills development
policies for youth in the John Taolo Gaetsewe Municipality. Summary of key findings of the study
are presented below:
2.1 Educational Levels of Youth
At the high school level, the study revealed that of the 22,381 participating young people from
the John Taolo Gaetsewe aged 18-35:
• Only 29.7% (6.442) indicated had achieved Grade 12 high school certification.
• Of the ten (10) core National Vocational Certificate courses listed in the study, Literacy,
Language and Communication I (394 or 1.8%) recorded the highest fraction of
participants who had achieved it.
• Of the four (4) elective National Vocational Certificate courses listed in the study,
Auxiliary Health Care (70 or 0.3%) recorded the highest fraction of participants who had
achieved it.
• Most of them indicated they had acquired 1-year university/college certification (131 or
24.3%), even though 262 (48.6%) indicated they acquired other higher qualifications.
2.2 Skills and Training Levels of Youth
• An overwhelmingly 97.4% (21,776) of the 22,381 participating young people from the John
Taolo Gaetsewe Municipality indicated they were interested in some form of skills
development training.
• Of the 21,776 who showed interest to be trained, most of the participants indicated their
interest in Mining (12,528 or 58.1%) followed by those with interest in Tourism and
hospitality (4,810 or 22.3%).
• Joe Morolong Municipality (6,313 or 50.4%) has the largest number of participants who
indicated they were interested to be trained in Mining.
• Males (7,004 or 55.9%) constitute the largest number of participants who indicated they
were interested to be trained in Mining.
2.3 Employment History/Experience of Youth
• Of the 22,381 participating young people from the John Taolo Municipality aged 18-35, an
astonishing 78.0% (17,071) indicated they had never worked before.

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• The majority of the participants who indicated they had worked before were from Ga
Segonyane Municipality (2,015 or 41.8%).
Most of the participants who indicated they had never worked before were from Joe
Morolong Municipality (9,906 or 58.0%).
• Most of the participants who indicated they had worked before were females (2,533 or
52.5%).
Most of the participants who indicated they had never worked before were also females
(10,881 or 63.7%).
• Of the 4,823 participants who indicated they had once worked, most of them indicated
they were part-time employees in the formal sector (1,969 or 40.8%).
• Of the 4,823 participants who indicated they had once worked, aside those who indicated
they worked in other sectors, most of them indicated they had worked in the mining
sector (743 or 19.1%).
• Of the 4,823 participants who indicated they had once worked, aside those who indicated
they worked, most of them indicated they had worked for 366 days or more (more than
1 year; 2,140 or 55.0%).
2.4 Youth and Training Preference
• Of the 21,562 who provided information on their training preferences, most of them
indicated they wished to be trained in mining (12,528 or 58.1%) followed by those who
indicated they wanted to be trained in tourism and hospitality (4,810 or 22.3%).
• Of the 12,528 participating youth who indicated they preferred to be trained in mining,
most of them were from Joe Morolong Municipality (6,313 or 50.4%).
2.5 Youth and Employment Preference
• Of the 21,908 who provided responses on their preferred sector to work, most of them
indicated they wished to work in the mining industry (11,815 or 53.9%) followed by those
who indicated they wanted to work in the tourism and hospitality industry (5,584 or
25.5%).
• Of the 11,815 participating youth who indicated they preferred working in the mining
sector, most of them were from Joe Morolong Municipality (6,146 or 52.0%).

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3 CHARACTERISTICS OF PARTICIPANTS
This section of the report discusses the profile of the participating youth. It particularly focuses
on the participants’ distributions according to municipality, ward, gender, and age group.
• In all, 22,381 unemployed youths from the John Taolo District Municipality participated in
the study.
• The John Taolo District Municipality is made up of three local municipalities, namely, Joe
Morolong Municipality (Kgalagadi), Ga Segonyana Municipality (Kuruman), and Ga Magara
(Kathu).
3.1 Participant Distribution by Municipality
The breakdown of participants according to the three municipalities, Joe Morolong Municipality,
Ga Segonyana Municipality, and Ga Magara are presented graphically in Chart 6.
• As indicated in Chart 4, the bulk of the participants were from the Joe Morolong
Municipality (12,011 or 51.5%) followed by participants from Ga Segonyana Municipality
(8,837 or 37.9%).
• Chart 7 is a graphical distribution of participants by gender. Of the 22,381 participating
youths, most of them were females (13,716 or 61.3%) while the remaining 8,665 (38.7%)
were males.
• As also depicted in Chart 8, of the 22,381 participants, the majority (10,285 or 46.0%) fall
within the 20-25 age group followed those within the age group 26-35 (9,804 or 43.8%),
while the remaining 2,292 (10.2%) of the participants fall within the 18-19 age group.
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
No.ofParticipants
No. Participants 2,305 8,435 11,641
Ga Magara
Municipality
Ga Segonyane
Municipality
Joe Morolong
Municipality
Chart 6: Breakdown of Participants by Municipality

10
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
No.ofParticipants
No. of Participants 13,716 8,665
Female Male
Chart 7: Distribution by Gender
0
2,000
4,000
6,000
8,000
10,000
12,000
No.ofParticipants
No. of Participants 2,292 10,285 9,804
18-19 years 20-25 years 26-35 years
Chart 8: Distribution by Age Group
Table 2 presents the distribution of participants by age group aggregated by municipality and
gender:
• Of the 2,292 participants aged 18-19 years, most of then were from Joe Morolong
Municipality (1,101 or 48.0%).
• Of the 10,285 participants aged 20-25 years, the majority of them were from Joe
• Of the 9,804 participants aged 26-35 years, the bulk of them were from Joe Morolong
Municipality (5,106 or 52.1%).
• Of the 2,292 participants aged 18-19 years, most of them were females (1,329 or 58.0%).

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• Of the 10,285 participating youths aged 20-25 years, the majority were females (6,075 or
59.1%).
• Of the 9,804 participants aged 26-35 years, most of them were females (6,312 or 64.4%).
Table 2: Distribution by Age Group and Gender
Age
TOTAL18-19 years 20-25 years 26-35 years
Freq Pcnt Freq Pcnt Freq Pcnt Freq Pcnt
Municipality
294 12.8 1075 10.5 936 9.5 2305 10.3Ga Magara Municipality
Ga Segonyane Municipality 897 39.1 3776 36.7 3762 38.4 8435 37.7
Joe Morolong Municipality 1101 48.0 5434 52.8 5106 52.1 11641 52.0
Gender
1329 58.0 6075 59.1 6312 64.4 13716 61.3Female
Male 963 42.0 4210 40.9 3492 35.6 8665 38.7
TOTAL 2292 10.2 10285 46.0 9804 43.8 22381 100.0
Distribution by Ethnic Origin
As depicted in Chart 9, the majority of the 22,386 participating youths were overwhelmingly of
African origin (21,352 or 95.4%) followed distantly by participants of Coloured origin (1,021 or
4.6%).
Africans,
21,352,
95%
Coloureds,
1,021,
4.6%
Chart 9: Distribution by Ethnic Origin

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• Of the 21,352 participants of African origin, the majority of them were from Joe
Morolong Municipality (11,564 or 54.2%) followed by Ga Segonyane Municipality (8,116
or 38.0%).
Of the 1,021 participants of Coloured origin, the majority of them were from Ga Magara
Municipality (626 or 61.3%) followed by Ga Segonyane Municipality (319 or 31.2%).
Table 3: Distribution by Ethnicity by Municipality, Gender, and Age Group
Ethnic origin
Africans Coloureds
Freq Pcnt Freq Pcnt
Municipality
1672 7.8 626 61.3Ga Magara Municipality
Ga Segonyane Municipality 8116 38.0 319 31.2
Joe Morolong Municipality 11564 54.2 76 7.4
Gender
13004 60.9 705 69.0Female
Male 8348 39.1 316 31.0
Age
2137 10.0 153 15.018-19 years
20-25 years 9796 45.9 487 47.7
26-35 years 9419 44.1 381 37.3
TOTAL 21352 100.0 1021 100.0
• Of the 21,352 participating youths of African origin, 60.9% (13,004) were females while
the remaining 39.1% (8,348) were males.
Of the 1,021 participating youths of Coloured origin, 69.0% (705) were females while the
remaining 31.0% (316) were males.
• Of the 21,352 participants of African origin, most of them fall within the 20-25 (9,796 or
45.9%) year age group followed by 44.1% (381) fall within the 26-35 year age group.
Of the 1,021 participating youths of Coloured descent, most of them (487 or 47.7%) fall
within the 20-25 year age group followed by 37.3% (381) falling within the 26-35 year age
group.
Distribution by Home Language
As revealed in Chart 10, participants were overwhelmingly Setswana-speaking with 20,783
(92.9%) and distantly followed by Afrikaans-speaking participants (1,311 or 5.9%), and Xhosa-
speaking participants (94 or 0.4%).

13
0
3000
6000
9000
12000
15000
18000
21000
No.ofParticipants
No. of Participants 1311 22 20783 94 14 73 84
Afrikaans English Setswana isiXhosa isiZulu Sesotho
Other/Not
supplied
Chart 10: Distribution by Home Language
Table 4: Distribution by Ethnic Origin and Municipality
Home language
Afrikaans Setswana
Freq Pcnt Freq Pcnt
Municipality
913 69.6 1279 6.2Ga Magara Municipality
Ga Segonyane Municipality 360 27.5 7961 38.3
Joe Morolong Municipality 38 2.9 11543 55.5
Gender
918 70.0 12648 60.9Female
Male 393 30.0 8135 39.1
Age
218 16.6 2046 9.818-19 years
20-25 years 621 47.4 9532 45.9
26-35 years 472 36.0 9205 44.3
Ethnic origin
429 32.7 20646 99.3Africans
Coloureds 876 66.8 136 0.7
TOTAL 1311 100.0 20783 100.0
Table 4 further presents the distributions of participants of African and Coloured descents by
home language aggregated by municipality, gender, age group, and ethnic origin.
• Most of the 1,311 Afrikaans-speaking participants were from Ga Magara Municipality (913
or 69.6%) while the majority of the 20,783 Setswana-speaking participants were from Joe

14
• The majority of the Afrikaans-speaking participants were females (918 or 70.0%) while the
majority of the Setswana-speaking participants were also females (12,648 or 60.9%).
• Most of the Afrikaans-speaking (621 or 47.4%) and Setswana-speaking (9,532 or 45.9%)
participants fall within the age group 20-25 years followed by the 26-35 year age group
(Afrikaans-speaking: 472, 36.0%; Setswana-speaking: 9,205, 44.3%).
• Most of the participants of Coloured origin were aged 20-25 (487 or 47.7) followed those
participants aged 26-35 years (381 or 37.3%).
3.2 Ga Moraga Municipality
Of the 2,305 participants from Ga Magara, 2,186 (excluding 6 White participants) supplied
information on their gender, age, and ethnic origin. As shown in Table 5:
Table 5: Distribution of Participants from Ga Moraga Municipality by Gender, Age and Ethnicity
Gender Age Ethnic origin
TOTALFemale Male 18-19 years 20-25 years 26-35 years Africans Coloureds
Freq Pcnt Freq Pcnt Freq Pcnt Freq Pcnt Freq Pcnt Freq Pcnt Freq Pcnt Freq Pcnt
Ward
230 16.1 146 19.2 40 14.4 195 19.1 141 15.9 306 19.6 70 11.3 376 17.2Ward 1
Ward 2 328 23.0 141 18.6 90 32.4 216 21.2 163 18.4 302 19.3 167 26.9 469 21.5
Ward 3 218 15.3 88 11.6 56 20.1 123 12.0 127 14.3 176 11.2 130 20.9 306 14.0
Ward 4 322 22.6 98 12.9 47 16.9 213 20.9 160 18.0 182 11.6 238 38.3 420 19.2
Ward 5 329 23.1 286 37.7 45 16.2 274 26.8 296 33.4 599 38.3 16 2.6 615 28.1
TOTAL 1427 65.3 759 34.7 278 12.7 1021 46.7 887 40.6 1565 71.6 621 28.4 2186 100.0
• The majority of the participants from Ga Magara Municipality were from Ward 5 (615 or
28.1%) followed by Ward 2 (469 or 21.5%) and Ward 4 (420 or 19.2%).
• Most of the participants from Ga Magara Municipality who participated in this study were
females (1,462 or 65.3%).
• The majority of the Ga Moraga participants fall within the age group 20-25 years (1,021 or
46.7%).
• The bulk of the participants were of African/Black origin (1,565 or71.6%) with participants
of Coloured origin making up of second biggest group (621 or 28.4%).
Breakdown of participants according to gender, age group and ethnic origin for the various wards
is also contained in Table 5.

15
3.3 Ga Segonyane Municipality
Of the total of 8,435 participants from Ga Segonyane Municipality, 8,321 provided information
about their gender, age, and ethnic orientation. As shown in Table 6:
• The three biggest share of participants from Ga Segonyane Municipality were from Ward
12 (1,197 or 14.4%), Ward 3 (901 or 10.8%), and Ward 4 (710 or 8.5%).
• Most of the participants from Ga Segonyane Municipality were females (5,165 or 62.1%).
Table 6: Distribution of Participants from Ga Segonyane Municipality by Gender, Age and Ethnicity
Ward
440 8.5 246 7.8 87 9.8 291 7.8 308 8.3 680 8.5 6 1.9 686 8.2Ward 2
Ward 3 573 11.1 328 10.4 90 10.1 360 9.7 451 12.2 897 11.2 4 1.3 901 10.8
Ward 4 481 9.3 229 7.3 78 8.8 320 8.6 312 8.4 699 8.7 11 3.5 710 8.5
Ward 5 410 7.9 281 8.9 55 6.2 331 8.9 305 8.2 686 8.6 5 1.6 691 8.3
Ward 6 399 7.7 258 8.2 66 7.4 309 8.3 282 7.6 651 8.1 6 1.9 657 7.9
Ward 7 401 7.8 267 8.5 54 6.1 299 8.0 315 8.5 666 8.3 2 0.6 668 8.0
Ward 8 435 8.4 248 7.9 49 5.5 278 7.5 356 9.6 682 8.5 1 0.3 683 8.2
Ward 9 273 5.3 189 6.0 38 4.3 208 5.6 216 5.8 459 5.7 3 1.0 462 5.6
Ward 10 350 6.8 222 7.0 62 7.0 251 6.7 259 7.0 567 7.1 5 1.6 572 6.9
Ward 11 425 8.2 283 9.0 70 7.9 331 8.9 307 8.3 702 8.8 6 1.9 708 8.5
Ward 12 738 14.3 459 14.5 153 17.2 561 15.1 483 13.0 1188 14.8 9 2.9 1197 14.4
Ward 13 240 4.6 146 4.6 88 9.9 183 4.9 115 3.1 129 1.6 257 81.6 386 4.6
TOTAL 5165 62.1 3156 37.9 890 10.7 3722 44.7 3709 44.6 8006 96.2 315 3.8 8321 100.0
3.4 Joe Morolong Municipality
Of the total of 11,641 participants from Joe Morolong Municipality, 11,580 supplied information
about their gender, age, and ethnic orientation. As shown in Table 7:
• Most of the participants were from Ward 9 (1,229 or 10.6%) followed by Ward 12 (1,165
or 10.1%) and Ward 13 (905 or 7.8%).
• The majority of the participants from Joe Morolong Municipality were females (6,968 or
60.2%).
• Most of the participants fall within the age group 20-25 years (5,409 or 46.7%) followed
closely by age group 26-35 years (5,077 or 43.8%).

16
• An overwhelmingly 99.3% (11,504) of the participants from Joe Morolong Municipality
were of African origin.
Table 7: Distribution of Participants from Joe Morolong Municipality by Gender, Age and Ethnicity
Ward
415 6.0 345 7.5 75 6.9 372 6.9 313 6.2 754 6.6 6 7.9 760 6.6Ward 2
Ward 1 444 6.4 278 6.0 61 5.6 312 5.8 349 6.9 717 6.2 5 6.6 722 6.2
Ward 3 301 4.3 180 3.9 47 4.3 225 4.2 209 4.1 481 4.2 . . 481 4.2
Ward 4 112 1.6 45 1.0 19 1.7 86 1.6 52 1.0 150 1.3 7 9.2 157 1.4
Ward 5 544 7.8 307 6.7 77 7.0 417 7.7 357 7.0 850 7.4 1 1.3 851 7.3
Ward 6 445 6.4 333 7.2 68 6.2 341 6.3 369 7.3 774 6.7 4 5.3 778 6.7
Ward 7 443 6.4 364 7.9 76 6.9 382 7.1 349 6.9 806 7.0 1 1.3 807 7.0
Ward 8 371 5.3 250 5.4 52 4.8 289 5.3 280 5.5 616 5.4 5 6.6 621 5.4
Ward 9 693 9.9 536 11.6 105 9.6 534 9.9 590 11.6 1218 10.6 11 14.5 1229 10.6
Ward 10 689 9.9 404 8.8 104 9.5 537 9.9 452 8.9 1088 9.5 5 6.6 1093 9.4
Ward 11 492 7.1 351 7.6 95 8.7 389 7.2 359 7.1 834 7.2 9 11.8 843 7.3
Ward 12 724 10.4 441 9.6 105 9.6 549 10.1 511 10.1 1157 10.1 8 10.5 1165 10.1
Ward 13 566 8.1 339 7.4 95 8.7 414 7.7 396 7.8 902 7.8 3 3.9 905 7.8
Ward 14 453 6.5 298 6.5 71 6.5 363 6.7 317 6.2 746 6.5 5 6.6 751 6.5
Ward 15 276 4.0 141 3.1 44 4.0 199 3.7 174 3.4 411 3.6 6 7.9 417 3.6
TOTAL 6968 60.2 4612 39.8 1094 9.4 5409 46.7 5077 43.8 11504 99.3 76 0.7 11580 100.0

17
4 HIGH SCHOOL GRADES COMPLETED
Education constitutes a crucial and fundamental dimension of human development and has a vital
bearing on achievement of other human developmental goals. More importantly, in this current
age of information and knowledge, education is essential to expanding life opportunities and for
enlarging human choices to live dignified lives. Consequently, education is truly regarded as the
most assured way toward the human empowerment. In several empirical studies, findings clearly
indicate the vital role that education plays in accelerating social development and human
upliftment. Furthermore, education contributes to generating sustainable livelihoods and
employment opportunities.
This unit of the report assesses the early academic background of participants according to
municipality and ward, and further aggregated according to gender, age group, and ethnic origin.
Grades completed by participants were also re-grouped according to whether they have
completed Grade 12 or not.
4.1 Highest High School Grade Completed
Of the 22,381 participants, 21,717 provided information about their highest high school
attainment. As revealed in Chart 11:
• Of the 21,717 participants who provided information on the highest high school grade
completed, only about 29.7% (6,446) indicated they completed Grade 12.

18
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
6,000
6,500
No.ofParticipants
No. of Participants 120 154 248 381 481 700 1,205 1,406 2,258 3,826 4,500 6,446
Grade
1
Grade
2
Grade
3
Grade
4
Grade
5
Grade
6
Grade
7
Grade
8
Grade
9
Grade
10
Grade
11
Grade
12
Chart 11: Distribution by Highest High School Grade Completed
4.2 Highest High School Completed by Municipality, Gender and Age Group
As further reported in Table 8 and Table 9, of the 6,442 participants who indicated they had
completed Grade 12:
Table 8: Distribution of Highest High School Grade Completed by Gender and Age
Gender Age
TOTALFemale Male 18-19 years 20-25 years 26-35 years
Freq Pcnt Freq Pcnt Freq Pcnt Freq Pcnt Freq Pcnt Freq Pcnt
Highest school class
58 48.3 62 51.7 5 4.2 36 30.0 79 65.8 120 100.0Grade 1
Grade 2 71 46.1 83 53.9 8 5.2 43 27.9 103 66.9 154 100.0
Grade 3 137 55.2 111 44.8 16 6.5 76 30.6 156 62.9 248 100.0
Grade 4 214 56.2 167 43.8 23 6.0 114 29.9 244 64.0 381 100.0
Grade 5 273 56.8 208 43.2 37 7.7 167 34.7 277 57.6 481 100.0
Grade 6 412 58.9 288 41.1 81 11.6 247 35.3 372 53.1 700 100.0
Grade 7 677 56.2 528 43.8 159 13.2 513 42.6 533 44.2 1205 100.0
Grade 8 814 57.9 591 42.1 205 14.6 602 42.8 598 42.6 1405 100.0
Grade 9 1324 58.6 934 41.4 272 12.0 1047 46.4 939 41.6 2258 100.0
Grade 10 2188 57.2 1636 42.8 352 9.2 1896 49.6 1576 41.2 3824 100.0
Grade 11 2947 65.5 1552 34.5 336 7.5 2127 47.3 2036 45.3 4499 100.0
Grade 12 4188 65.0 2254 35.0 757 11.8 3229 50.1 2456 38.1 6442 100.0

19
Table 9: Distribution of Highest High School Grade Completed by Municipality
Municipality
TOTAL
Ga Magara
Municipality
Ga Segonyane
Municipality
Joe Morolong
Municipality
Highest school class
10 8.3 46 38.3 64 53.3 120 100.0Grade 1
Grade 2 15 9.7 34 22.1 105 68.2 154 100.0
Grade 3 16 6.5 64 25.8 168 67.7 248 100.0
Grade 4 36 9.4 89 23.4 256 67.2 381 100.0
Grade 5 58 12.1 126 26.2 297 61.7 481 100.0
Grade 6 71 10.1 202 28.9 427 61.0 700 100.0
Grade 7 134 11.1 366 30.4 705 58.5 1205 100.0
Grade 8 150 10.7 495 35.2 760 54.1 1405 100.0
Grade 9 193 8.5 746 33.0 1319 58.4 2258 100.0
Grade 10 446 11.7 1508 39.4 1870 48.9 3824 100.0
Grade 11 461 10.2 1741 38.7 2297 51.1 4499 100.0
Grade 12 650 10.1 2853 44.3 2939 45.6 6442 100.0
• Most of those who completed Grade 12 were from Joe Morolong Municipality (2,939 or
45.6%) followed by Ga Segonyane Municipality (2,853 or 44.3%).
• Most of those who completed Grade 12 were females (4,188 or 65.0%) while the
remaining 35.0% (2,254) were males.
• Most of those who completed Grade 12 fall within the age group 20-25 years (3,229 or
50.1%).
Table 10 displays the municipal distribution of participants who indicated they completed high
school Grade 12 by gender and age group.
Table 10: Municipal Distribution of High School Grade 12 Completed by Gender and Age
Grade 12 acquired?
Yes, Grade 12 acquired
Gender Age
Municipality
455 70.0 195 30.0 79 12.2 358 55.1 213 32.8 650 100.0Ga Magara Municipality
Ga Segonyane Municipality 1870 65.5 983 34.5 348 12.2 1387 48.6 1118 39.2 2853 100.0
Joe Morolong Municipality 1863 63.4 1076 36.6 330 11.2 1484 50.5 1125 38.3 2939 100.0
TOTAL 4188 65.0 2254 35.0 757 11.8 3229 50.1 2456 38.1 6442 100.0

20
4.3 Completion of Grade 12: Distribution by Ward
Grade 12 completion by participants was further assessed on local municipal basis according to
ward. Table 11 summarizes the breakdown of participants according to ward.
4.3.1 Ga Maraga Municipality
Of the 650 participants from Ga Moraga Municipality who indicated they completed Grade 12,
the majority of them were from Ward 1 (202 or 31.1%).
• Of the 455 female participants who indicated they completed Grade 12, most of them
were from Ward 1 (144 or 31.6%). Of the 195 male participants who indicated they
completed Grade 12, most of them were from Ward 5 (79 or 40.5%).
• Most of 18-19 year olds from Ga Maraga Municipality who indicated they completed
Grade 12 were from Ward 1 (21 or 26.6%). Most of 20-25 year olds from Ga Maraga
Municipality who indicated they completed Grade 12 were also from Ward 1 (110 or
30.7%). Most of 26-35 year olds from Ga Maraga Municipality who indicated they
completed Grade 12 were also from Ward 5 (73 or 34.3%).
Table 11: Grade 12 Status by Ward Aggregated by Gender and Age
Grade 12 acquired? Yes, Grade 12 acquired
Gender Age
Municipality Ward
144 31.6 58 29.7 21 26.6 110 30.7 71 33.3 202 31.1Ga Magara
Municipality
Ward 1
Ward 2 49 10.8 12 6.2 10 12.7 43 12.0 8 3.8 61 9.4
Ward 3 64 14.1 19 9.7 18 22.8 36 10.1 29 13.6 83 12.8
Ward 4 83 18.2 27 13.8 14 17.7 64 17.9 32 15.0 110 16.9
Ward 5 115 25.3 79 40.5 16 20.3 105 29.3 73 34.3 194 29.8
TOTAL 455 100.0 195 100.0 79 100.0 358 100.0 213 100.0 650 100.0

21
Grade 12 acquired? Yes, Grade 12 acquired
Gender Age
Ga Segonyane
Municipality
Ward
92 4.9 35 3.6 18 5.2 62 4.5 47 4.2 127 4.5Ward 2
Ward 3 273 14.6 144 14.6 45 12.9 174 12.5 198 17.7 417 14.6
Ward 4 239 12.8 111 11.3 41 11.8 167 12.0 142 12.7 350 12.3
Ward 5 155 8.3 118 12.0 23 6.6 152 11.0 98 8.8 273 9.6
Ward 6 142 7.6 86 8.7 30 8.6 118 8.5 80 7.2 228 8.0
Ward 7 80 4.3 31 3.2 16 4.6 48 3.5 47 4.2 111 3.9
Ward 8 134 7.2 51 5.2 16 4.6 73 5.3 96 8.6 185 6.5
Ward 9 86 4.6 50 5.1 13 3.7 68 4.9 55 4.9 136 4.8
Ward 10 104 5.6 42 4.3 19 5.5 74 5.3 53 4.7 146 5.1
Ward 11 164 8.8 109 11.1 25 7.2 135 9.7 113 10.1 273 9.6
Ward 12 295 15.8 159 16.2 69 19.8 227 16.4 158 14.1 454 15.9
Ward 13 106 5.7 47 4.8 33 9.5 89 6.4 31 2.8 153 5.4
TOTAL 1870 100.0 983 100.0 348 100.0 1387 100.0 1118 100.0 2853 100.0
Joe Morolong
Municipality
Ward
138 7.4 68 6.3 18 5.5 94 6.3 94 8.4 206 7.0Ward 1
Ward 2 113 6.1 70 6.5 22 6.7 100 6.7 61 5.4 183 6.2
Ward 3 77 4.1 22 2.0 11 3.3 51 3.4 37 3.3 99 3.4
Ward 4 19 1.0 5 0.5 3 0.9 14 0.9 7 0.6 24 0.8
Ward 5 154 8.3 91 8.5 27 8.2 140 9.4 78 6.9 245 8.3
Ward 6 80 4.3 39 3.6 12 3.6 60 4.0 47 4.2 119 4.0
Ward 7 138 7.4 102 9.5 24 7.3 123 8.3 93 8.3 240 8.2
Ward 8 133 7.1 72 6.7 23 7.0 104 7.0 78 6.9 205 7.0
Ward 9 175 9.4 114 10.6 36 10.9 129 8.7 124 11.0 289 9.8
Ward 10 148 7.9 88 8.2 20 6.1 117 7.9 99 8.8 236 8.0
Ward 11 160 8.6 99 9.2 34 10.3 123 8.3 102 9.1 259 8.8
Ward 12 187 10.0 113 10.5 38 11.5 160 10.8 102 9.1 300 10.2
Ward 13 143 7.7 78 7.2 25 7.6 106 7.1 90 8.0 221 7.5
Ward 14 130 7.0 78 7.2 24 7.3 105 7.1 79 7.0 208 7.1
Ward 15 68 3.7 37 3.4 13 3.9 58 3.9 34 3.0 105 3.6
TOTAL 1863 100.0 1076 100.0 330 100.0 1484 100.0 1125 100.0 2939 100.0
4.3.2 Ga Segonyane Municipality
Of the 2,853 participants from Ga Segonyane Municipality who indicated they completed Grade
12, most of them were from Ward 12 (454 or 15.9%). Also from the results in Table 10:
• Most of the female participants from Ga Segonyane Municipality who indicated they
completed Grade 12 were from Ward 12 (295 or 15.8%).

22
Most of the male participants from Ga Segonyane Municipality who indicated they
completed Grade 12 were also from Ward 12 (159 or 16.2%).
• Most of 18-19 year olds from Ga Segonyane Municipality who indicated they completed
Grade 12 were from Ward 3 (42 or 12.9%).
Most of 20-25 year olds from Ga Segonyane Municipality who indicated they completed
Grade 12 were also from Ward 3 (174 or 12.5%).
Most of 26-35 year olds from Ga Segonyane Municipality who indicated they completed
4.3.3 Joe Morolong Municipality
Of the 2,939 participants from Joe Morolong Municipality who indicated they completed Grade
12, most of them were from Ward 12 (300 or 10.2%). Also from the results in Table 10:
• Most of the female participants from Joe Morolong Municipality who indicated they
completed Grade 12 were from Ward 12 (187 or 10.0%).
Most of the male participants from Joe Morolong Municipality who indicated they
completed Grade 12 were also from Ward 9 (114 or 10.6%) and Ward 12 (113 or
10.5%).
• Most of 18-19 year olds from Joe Morolong Municipality who indicated they completed
Grade 12 were from Ward 12 (38 or 11.5%).
Most of 20-25 year olds from Joe Morolong Municipality who indicated they completed
Most of 26-35 year olds from Joe Morolong Municipality who indicated they completed
4.4 High School Grades Ever Completed (Cumulative Distribution)
The evaluation of high school grades completed was further expanded to account for all possible
high school grades completed by participants. Chart 12 presents the cumulative distribution of all
possible high school grades completed. Of the 21,717 provided who provided information on all
possible high school grades completed:
• All 21,717 indicated they completed Grade1 compared to the 6,442 who indicated they
completed Grade 12.
• Only about 29.7% of all participants who indicated they completed high school Grade 1
also indicated they completed high school Grade 12.

23
0
4,000
8,000
12,000
16,000
20,000
24,000
Cum.No.ofParticipants
Cum. No. of Partic. 21,717 21,597 21,443 21,195 20,814 20,333 19,633 18,428 17,023 14,765 10,941 6,442
Grade
1
Grade
2
Grade
3
Grade
4
Grade
5
Grade
6
Grade
7
Grade
8
Grade
9
Grade
10
Grade
11
Grade
12
Chart 12: Distribution of All Possible High School Grades Completed
41.1
25.9
13.3
7.6
6.1
3.4
2.3
1.8
1.2
0.7
0.6
0 10 20 30 40 50
Grade 11 - Grade 12
Grade 10 - Grade 11
Grade 9 - Grade 10
Grade 8 - Grade 9
Grade 7 - Grade 8
Grade 6 - Grade 7
Grade 5 - Grade 6
Grade 4 - Grade 5
Grade 3 - Grade 4
Grade 2 - Grade 3
Grade 1 - Grade 2
Drop-Out Rate (%)
Chart 13: Drop-Out Rates at the High School Level
Chart 13 displays the drop rates of youths from the Taolo Gaetsewe Municipality who
participated in the study. From Chart 11:
• It is disturbing to establish that the rate at which participants dropped as they progress
from a grade to the next higher grade was exponential.

24
• Drop-out rate went from 0.6% in Grade 2 to as high as 41.1% in Grade 12, a difference
of about 40.5%.
4.4.1 Distribution by Municipality
The evaluation of all possible high school grades completed by participants was further done on
the basis of local municipalities. As reported in Table 12:
• Of the 2,240 participants from Ga Maraga Municipality who indicated they completed
Grade 1, only 650 of them indicated they also completed Grade 12, representing just
about 29.0% of all participants from Ga Maraga Municipality.
• Of the 8,270 participants from Ga Segonyane Municipality who indicated they completed
Grade 1, 2,853 of them indicated they also completed Grade 12, representing about
34.5% of all participants from Ga Segonyane Municipality.
• Of the 11,207 participants from Joe Morolong Municipality who indicated they completed
Grade 1, only 2,939 of them indicated they also completed Grade 12, representing just
about 26.2% of all participants from Joe Morolong Municipality.
Table 12: Distribution of All High School Grades Completed by Municipality
Grade
Municipality
TOTAL
Ga Magara
Municipality
Ga Segonyane
Municipality
Joe Morolong
Municipality
Grade 1
0 0.0 0 0.0 0 0.0 0 0.0
Grade 2 10 8.3 46 38.3 64 53.3 120 100.0
Grade 3 25 9.1 80 29.2 169 61.7 274 100.0
Grade 4 41 7.9 144 27.6 337 64.6 522 100.0
Grade 5 77 8.5 233 25.8 593 65.7 903 100.0
Grade 6 135 9.8 359 25.9 890 64.3 1384 100.0
Grade 7 206 9.9 561 26.9 1317 63.2 2084 100.0
Grade 8 340 10.3 927 28.2 2022 61.5 3289 100.0
Grade 9 490 10.4 1422 30.3 2782 59.3 4694 100.0
Grade 10 683 9.8 2168 31.2 4101 59.0 6952 100.0
Grade 11 1129 10.5 3676 34.1 5971 55.4 10776 100.0
Grade 12 1590 10.4 5417 35.5 8268 54.1 15275 100.0
4.4.2 Distribution by Gender and Age Group
The evaluation of all possible high school grades completed by participants was further done
according to gender and age group. From the results in Table 13:

25
Table 13: Distribution of All High School Grades Completed by Gender and Age Group
Grade
Gender Age
Grade 1 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0
Grade 2 58 48.3 62 51.7 5 4.2 36 30.0 79 65.8 120 100.0
Grade 3 129 47.1 145 52.9 13 4.7 79 28.8 182 66.4 274 100.0
Grade 4 266 51.0 256 49.0 29 5.6 155 29.7 338 64.8 522 100.0
Grade 5 480 53.2 423 46.8 52 5.8 269 29.8 582 64.5 903 100.0
Grade 6 753 54.4 631 45.6 89 6.4 436 31.5 859 62.1 1384 100.0
Grade 7 1165 55.9 919 44.1 170 8.2 683 32.8 1231 59.1 2084 100.0
Grade 8 1842 56.0 1447 44.0 329 10.0 1196 36.4 1764 53.6 3289 100.0
Grade 9 2656 56.6 2038 43.4 534 11.4 1798 38.3 2362 50.3 4694 100.0
Grade 10 3980 57.2 2972 42.8 806 11.6 2845 40.9 3301 47.5 6952 100.0
Grade 11 6168 57.2 4608 42.8 1158 10.7 4741 44.0 4877 45.3 10776 100.0
Grade 12 9115 59.7 6160 40.3 1494 9.8 6868 45.0 6913 45.3 15275 100.0
• Of the 13,303 female participants who indicated they completed Grade 1, only 4,188 of
them indicated they also completed Grade 12, representing just about 31.5% of all female
participants.
• Of the 8,414 male participants who indicated they completed Grade 1, 2,254 of them
indicated they also completed Grade 12, representing just about 26.8% of all male
participants.

26
5 COLLEGE-TECHNIKON CERTIFICATIONS ACQUIRED
5.1 College-Technikon Diplomas Acquired
Participants were also asked to indicate whether or not they have acquired college diplomas. As
depicted in Chart 14:
• Of the 22,831 participants, 435 indicated they have acquired certifications (N4, N5 and
N6) at the college/technikon level. Most certifications acquired by participants had been in
Business Skills (165 or 0.7%) and certifications in Engineering (76 or 0.3%), even though
127 (0.6%) also indicated they had acquired certification in other college diplomas.
0
20
40
60
80
100
120
140
160
180
No.ofParticipants
No. of Participants 165 47 76 10 10 127
Business
Skills
IT Engineering
Creative and
Social
Service
Call Centre Other
Chart 14: Distribution of College Diploma Certifications Acquired
5.2 College-Technikon Diplomas Acquired by Municipality
College diploma certifications were further aggregated according to Municipality. Table 14
presents the distributions of participants with information on whether they had acquired college
diploma certifications.
• Of the 165 participants who indicated they had college diploma in Business Skills, the
most were from Joe Morolong Municipality (56 or 33.9%).
• Of the 47 participants who indicated they had college diploma in IT, most of them were
from Ga Segonyane Municipality (24 or 51.1%). No participant from Ga Maraga had
college diploma in IT.
• Of the 76 participants with college diploma in Engineering, the majority of them were
from Ga Segonyane Municipality (48 or 63.2%).

27
Table 14: Distribution of College Diploma Certifications Acquired by Municipality
Municipality
TOTAL
Ga Magara
Municipality
Ga Segonyane
Municipality
Joe Morolong
Municipality
Business Skills 11 6.7 98 59.4 56 33.9 165 100.0
IT . . 24 51.1 23 48.9 47 100.0
Engineering 2 2.6 48 63.2 26 34.2 76 100.0
Creative and Social Service . . 5 50.0 5 50.0 10 100.0
Call Centre . . 3 30.0 7 70.0 10 100.0
Other 31 24.4 55 43.3 41 32.3 127 100.0
• Of the only 10 participants who indicated they had college diploma in Creative and Social
Services, half was from Ga Segonyane Municipality while the remaining half was from Joe
Morolong Municipality. No participant from Ga Maraga Municipality had a college diploma
in Creative and Social Services.
• Of the 10 participants who indicated they had college diploma in Call Centre
management, most of them were from Joe Morolong Municipality (7 or 70.0%). No
participant from Ga Maraga had college diploma in Call Centre Management.
• Of the 127 participants with college diploma in other fields, the majority of them were
from Ga Segonyane Municipality (55 or 43.3%).
5.3 College-Technikon Diplomas Acquired by Ward
College diplomas acquired by participants were further assessed on ward basis. Table 15 presents
the distributions of participants with information on whether they had acquired college diplomas.
Most noticeable among the results are summarized below:
• No participants from Ward 2 in Ga Maraga Municipality and Ward 4 in Joe Morolong
Municipality had college diplomas in Business Skills.
• No participants from any of the 5 wards in Ga Maraga Municipality, Ward 7 and Ward 9
in Ga Segonyane Municipality, Ward 3, Ward 4, and Ward 7 in Joe Morolong Municipality
had college diplomas in IT.
• No participant from Ward 1, Ward 2, Ward 3, and Ward 4 in Ga Maraga Municipality,
Ward 13 in Ga Segonyane Municipality, Ward 4, Ward 7, Ward 9, Ward 13, and Ward
15 had college diploma in Engineering.

28
Table 15: Distribution of College Diploma Certifications Acquired by Municipality and Ward
Business
Skills IT Engineering
Creative and
Social Service Call Centre Other
Municipality Ward
4 36.4 . . . . . . . . 21 67.7Ga Magara
Municipality
Ward 1
Ward 2 . . . . . . . . . . . .
Ward 3 1 9.1 . . . . . . . . 7 22.6
Ward 4 3 27.3 . . . . . . . . 1 3.2
Ward 5 3 27.3 . . 2 100.0 . . . . 2 6.5
TOTAL 11 100.0 . . 2 100.0 . . . . 31 100.0
Ga Segonyane
Municipality
Ward
5 5.1 2 8.3 2 4.2 . . . . 1 1.8Ward 2
Ward 3 8 8.2 1 4.2 2 4.2 . . 1 33.3 14 25.5
Ward 4 16 16.3 2 8.3 11 22.9 . . . . 2 3.6
Ward 5 8 8.2 5 20.8 5 10.4 . . . . 6 10.9
Ward 6 9 9.2 1 4.2 2 4.2 1 20.0 . . 5 9.1
Ward 7 6 6.1 . . 6 12.5 . . . . 1 1.8
Ward 8 10 10.2 7 29.2 5 10.4 1 20.0 . . 6 10.9
Ward 9 3 3.1 . . 3 6.3 . . . . 4 7.3
Ward 10 3 3.1 2 8.3 1 2.1 2 40.0 1 33.3 2 3.6
Ward 11 7 7.1 1 4.2 3 6.3 1 20.0 1 33.3 2 3.6
Ward 12 15 15.3 1 4.2 8 16.7 . . . . 6 10.9
Ward 13 8 8.2 2 8.3 . . . . . . 6 10.9
TOTAL 98 100.0 24 100.0 48 100.0 5 100.0 3 100.0 55 100.0
Joe Morolong
Municipality
Ward
9 16.1 1 4.3 1 3.8 . . . . 5 12.2Ward 1
Ward 2 6 10.7 1 4.3 2 7.7 . . 1 14.3 5 12.2
Ward 3 1 1.8 . . 2 7.7 . . . . 3 7.3
Ward 4 . . . . . . . . . . . .
Ward 5 5 8.9 7 30.4 4 15.4 4 80.0 4 57.1 4 9.8
Ward 6 1 1.8 1 4.3 2 7.7 . . . . 2 4.9
Ward 7 12 21.4 . . . . . . . . 1 2.4
Ward 8 5 8.9 1 4.3 4 15.4 . . . . 5 12.2
Ward 9 1 1.8 1 4.3 . . . . . . 4 9.8
Ward 10 2 3.6 3 13.0 3 11.5 . . . . 3 7.3
Ward 11 1 1.8 3 13.0 4 15.4 1 20.0 1 14.3 2 4.9
Ward 12 3 5.4 1 4.3 1 3.8 . . 1 14.3 . .
Ward 13 4 7.1 1 4.3 . . . . . . . .
Ward 14 4 7.1 2 8.7 3 11.5 . . . . 6 14.6
Ward 15 2 3.6 1 4.3 . . . . . . 1 2.4
TOTAL 56 100.0 23 100.0 26 100.0 5 100.0 7 100.0 41 100.0

29
• No participants from any of the 5 wards in Ga Maraga Municipality, Ward 2, Ward 3,
Ward 4, Ward 5, Ward 7, Ward 9, Ward 12, and Ward 13 in Ga Segonyane Municipality,
Ward 1, Ward 2, Ward 3, Ward 4, Ward 6, Ward 7, Ward 8, Ward 9, Ward 10, Ward
12, Ward 13, Ward 14, and Ward 15 in Joe Morolong Municipality had college diplomas
in Creative and Social Services.
• Only Ward 3, Ward 10, and Ward 11 in Ga Segonyane Municipality, Ward 2, Ward 5,
Ward 11, and Ward 12 had, at least, one participant with college diploma in Call Centre
management. No participants from any of the 5 wards in Ga Maraga Municipality had
college diploma in Call Centre management.
5.4 Description of National Diplomas Acquired: N4, N5 and N6
National certifications acquired by participants were further assessed. Table 16 presents the
distributions of participants. Most noticeable among the results are summarized below:
• Of the 165 certifications acquired by participants in Business Skills, most of them were
N4 (86 or 52.1%) certificates.
• Of the 37 certifications acquired by participants in Information Technology (IT), most of
them were N4 (30 or 63.8%) certificates. No participant from Ga Magara Municipality had
acquired certification in IT.
• Of the 76 certifications acquired by participants in Engineering, most of them were N4
(49 or 64.5%) certificates.
• Of the 10 certifications acquired by participants in Creative and Social Service, half of
them were N4 certificates while the remaining half was N6 certificates. No participant
from Ga Magara Municipality had acquired certification in Creative and Social Service.
• Of the 10 certifications acquired by participants in Call Centre management, most of
them were N4 (5 or 50.0%) certificates. No participant from Ga Magara Municipality had
acquired certification in Call Centre management.
• Of the 127 certifications acquired by participants in other fields, most of them were N4
(65 or 51.5%) certificates while 31.5% (40) were N6 certificates.

30
Table 16: Distribution of National Certifications (N4, N5 and N6) Acquired by Municipality
Municipality
TOTAL
Ga Magara
Municipality
Ga Segonyane
Municipality
Joe Morolong
Municipality
Business Skills
4 4.7 48 55.8 34 39.5 86 52.1N4
N5 3 9.7 22 71.0 6 19.4 31 18.8
N6 4 8.3 28 58.3 16 33.3 48 29.1
IT
. . 16 53.3 14 46.7 30 63.8N4
N5 . . 3 100.0 . . 3 6.4
N6 . . 5 35.7 9 64.3 14 29.8
Engineering
2 4.1 31 63.3 16 32.7 49 64.5N4
N5 . . 7 53.8 6 46.2 13 17.1
N6 . . 10 71.4 4 28.6 14 18.4
Creative and Social
Service
. . 3 60.0 2 40.0 5 50.0N4
N6 . . 2 40.0 3 60.0 5 50.0
Call Centre
. . 2 40.0 3 60.0 5 50.0N4
N5 . . . . 1 100.0 1 10.0
N6 . . 1 25.0 3 75.0 4 40.0
Other
17 26.2 29 44.6 19 29.2 65 51.2N4
N5 6 27.3 7 31.8 9 40.9 22 17.3
N6 8 20.0 19 47.5 13 32.5 40 31.5

31
6 HIGHER ACADEMIC QUALIFICATIONS ACQUIRED
Participants were requested to indicate whether or not they had acquired university
qualifications.
6.1 Higher Qualifications Acquired
Chart 15 graphically displays the distribution of higher qualifications acquired by participants. Of
the 539 participants who provided information on this:
• Most of them indicated they had acquired other university qualifications (262 or 48.6%)
aside the ones listed.
• From the regular university certificates/diplomas/degrees, most of the participants
indicated they had acquired 1-year university/college certificates (131 or 24.3%) followed
by those who had acquired 2-year university/college diplomas (98 or 18.2%) and first
degree (33 or 6.1%).
0
50
100
150
200
250
300
No.ofParticipants
No. of Participants 131 98 33 10 4 262
1-year
univ./col.
2-year
univ./col.
First degree
Honours
degree
Masters
degree
Other
qualifications
Chart 15: Higher Qualifications Acquired
6.2 Higher Qualifications Acquired by Municipality
Distribution of higher qualifications was further assessed according to municipality, gender and
ethnic origin (Table 17). Of the 539 participants who had acquired university certificates/diplomas
/degrees:
• Most of them were from Ga Segonyane Municipality (262 or 48.6%); most of them were
females (384 or 71.2%); and most of them were of African origin (486 or 90.2%).

32
Further breakdown according to actual university certificate/diploma/degree is presented in Table
18. As further reported in Table 19:
• In Ga Maraga Municipality, Ward 5 (55 or 36.7%) had the largest number of participants
who had acquired university certificates/diplomas/degrees.
• In Ga Segonyane Municipality, Ward 3 (62 or 23.7%) had the largest number of
participants who had acquired university certificates/diplomas/degrees.
• In Joe Morolong Municipality, Ward 10 (62 or 23.7%) had the largest number of
participants who had acquired university certificates/diplomas/degrees.
Table 17: Higher Qualifications Acquired by Municipality, Gender and Ethnic Origin
Higher qualification holding status
Holders of higher qualifications
Freq Pcnt
TOTAL 539 100.0
Municipality
150 27.8Ga Magara Municipality
Ga Segonyane Municipality 262 48.6
Joe Morolong Municipality 127 23.6
Gender
384 71.2Female
Male 155 28.8
Ethnic origin
486 90.2Africans
Coloureds 53 9.8
Table 18: Higher Qualifications Acquired by Municipality, Gender and Ethnic Origin
Municipality
TOTAL
Ga Magara
Municipality
Ga Segonyane
Municipality
Joe Morolong
Municipality
Higher education earned
12 9.2 63 48.1 56 42.7 131 100.01-year univ./col. certificate
2-year univ./col. diploma 46 46.9 34 34.7 18 18.4 98 100.0
First degree 5 15.2 15 45.5 13 39.4 33 100.0
Honours degree 1 10.0 6 60.0 3 30.0 10 100.0
Masters degree 1 20.0 3 60.0 1 20.0 5 100.0
Other qualifications 85 32.4 141 53.8 36 13.7 262 100.0
TOTAL 150 27.8 262 48.6 127 23.6 539 100.0

33
Table 19: Higher Qualifications Acquired by Municipality and Ward
Higher qualification holding status
TOTAL
Non-holders of
higher qualifications
Holders of higher
qualifications
Freq Pcnt Freq Pcnt Freq Pcnt
Municipality Ward
323 15.0 75 50.0 398 17.3Ga Magara
Municipality
Ward 1
Ward 2 477 22.2 . . 477 20.8
Ward 3 338 15.7 8 5.3 346 15.1
Ward 4 424 19.7 12 8.0 436 19.0
Ward 5 586 27.3 55 36.7 641 27.9
TOTAL 2148 100.0 150 100.0 2298 100.0
Ga Segonyane
Municipality
Ward
689 8.4 6 2.3 695 8.2Ward 2
Ward 3 866 10.6 62 23.7 928 11.0
Ward 4 676 8.3 48 18.3 724 8.6
Ward 5 690 8.4 6 2.3 696 8.3
Ward 6 658 8.1 6 2.3 664 7.9
Ward 7 672 8.2 2 0.8 674 8.0
Ward 8 660 8.1 28 10.7 688 8.2
Ward 9 456 5.6 9 3.4 465 5.5
Ward 10 581 7.1 . . 581 6.9
Ward 11 682 8.3 28 10.7 710 8.4
Ward 12 1186 14.5 31 11.8 1217 14.4
Ward 13 357 4.4 36 13.7 393 4.7
TOTAL 8173 100.0 262 100.0 8435 100.0
Joe Morolong
Municipality
Ward
714 6.2 8 6.3 722 6.2Ward 1
Ward 2 762 6.6 2 1.6 764 6.6
Ward 3 479 4.2 3 2.4 482 4.1
Ward 4 157 1.4 . . 157 1.3
Ward 5 844 7.3 12 9.4 856 7.4
Ward 6 776 6.7 3 2.4 779 6.7
Ward 7 800 6.9 8 6.3 808 6.9
Ward 8 624 5.4 3 2.4 627 5.4
Ward 9 1230 10.7 3 2.4 1233 10.6
Ward 10 1063 9.2 31 24.4 1094 9.4
Ward 11 838 7.3 14 11.0 852 7.3
Ward 12 1147 10.0 21 16.5 1168 10.0
Ward 13 908 7.9 4 3.1 912 7.8
Ward 14 754 6.5 11 8.7 765 6.6
Ward 15 417 3.6 4 3.1 421 3.6
TOTAL 11513 100.0 127 100.0 11640 100.0

34
7 EMPLOYMENT HISTORY
7.1 Job History
Participants in the study were also asked to provide information on their employment history,
with particular attention to the three recent past jobs, if there are.
• As shown in Chart 16, the bulk of those who responded indicated they have never
worked before (17,071 or 78.0%).
0
4,000
8,000
12,000
16,000
20,000
No.ofParticipants
No. of Participant 4,823 17,071
Ever worked Never worked
Chart 16: Employment History
Table 20 presents the distribution of participants’ job history according to municipality, gender,
and ethnic origin.
Table 20: Employment History by Municipality, Gender and Ethnicity
Recent pass employment status
TOTALEver worked Never worked
Freq Pcnt Freq Pcnt Freq Pcnt
TOTAL 4823 22.0 17071 78.0 21894 100.0
Municipality
1098 52.8 980 47.2 2078 100.0Ga Magara Municipality
Ga Segonyane Municipality 2016 24.6 6185 75.4 8201 100.0
Joe Morolong Municipality 1709 14.7 9906 85.3 11615 100.0
Gender
2533 18.9 10881 81.1 13414 100.0Female
Male 2290 27.0 6190 73.0 8480 100.0
Ethnic origin
4361 20.8 16615 79.2 20976 100.0Africans
Coloureds 457 50.2 453 49.8 910 100.0

35
• Joe Morolong Municipality (9,908 or 85.3%) had the largest proportion of participants
who indicated they had never worked before.
• A relatively larger proportion of female participants (81.1% or 10,881) than male learners
(73.0% or 6,190) indicated they had never worked before.
• A significantly larger proportion of participants of African origin (79.2% or 16,615) than
Coloured participants (49.8% or 453) indicated they had never worked before.
7.2 Job History by Municipality and Ward
Table 21 displays the distribution of participants’ employment history according to municipality
and Ward.
• Of the 980 participants from Ga Moraga Municipality who had never worked before,
Ward 1 (54.9% or 208) had the largest proportion of participants followed by Ward 4
(54.7%) and Ward 5 (51.3%).
Of the 6,185 participants from Ga Segonyane Municipality who indicated they had never
worked before, Ward 7 (85.3% or 575) had the largest proportion of participants
followed by Ward 9 (85.2% or 396), Ward 4 (84.1% or 609), and Ward 11 (80.3% or
570).
Of the 9,906 participants from Joe Morolong Municipality who had never worked before,
Ward 9 (99.0%) had the largest proportion of participants, followed by Ward 7 (97.8% or
790), Ward 2 (90.8% or 693) and Ward 11 (90.4% or 765).

36
Table 21: Employment History by Municipality and Ward
Recent pass employment status
Ever worked Never worked
Freq Pcnt Freq Pcnt
Municipality Ward
171 45.1 208 54.9Ga Magara Municipality Ward 1
Ward 2 262 58.2 188 41.8
Ward 3 195 75.9 62 24.1
Ward 4 178 45.3 215 54.7
Ward 5 292 48.7 307 51.3
TOTAL 1098 52.8 980 47.2
Ga Segonyane Municipality Ward
220 31.7 473 68.3Ward 2
Ward 3 214 28.4 539 71.6
Ward 4 115 15.9 609 84.1
Ward 5 221 31.9 472 68.1
Ward 6 166 25.1 495 74.9
Ward 7 99 14.7 575 85.3
Ward 8 209 30.4 479 69.6
Ward 9 69 14.8 396 85.2
Ward 10 130 22.4 450 77.6
Ward 11 140 19.7 570 80.3
Ward 12 280 23.1 932 76.9
Ward 13 153 44.0 195 56.0
TOTAL 2016 24.6 6185 75.4
Joe Morolong Municipality Ward
82 11.4 639 88.6Ward 1
Ward 2 70 9.2 693 90.8
Ward 3 71 14.7 411 85.3
Ward 4 56 35.7 101 64.3
Ward 5 114 13.5 728 86.5
Ward 6 231 29.7 548 70.3
Ward 7 18 2.2 790 97.8
Ward 8 103 16.4 524 83.6
Ward 9 12 1.0 1219 99.0
Ward 10 271 24.8 822 75.2
Ward 11 81 9.6 765 90.4
Ward 12 167 14.3 1001 85.7
Ward 13 117 12.8 795 87.2
Ward 14 198 25.9 567 74.1
Ward 15 118 28.0 303 72.0
TOTAL 1709 14.7 9906 85.3

37
7.3 Description of Jobs Ever Done
Chart 17 is the distribution describing the nature of jobs done participants who had once
worked. Of the 4,823 participants who indicated they had worked before:
• Most of them indicated they were part-time employees in the formal sector (1,969 or
40.8%), followed by those who indicated they were part-time employees in the informal
sector (1,697 or 35.2%).
Further breakdown of the description of jobs ever done by participants according to municipality,
gender, and ethnic origin is presented in Table 22.
0
500
1,000
1,500
2,000
2,500
No.ofParticipants
No. of Participants 646 1,969 403 1,697 108
Employed full
time, formal
sector
Employed
part time,
formal sector
Employed full
time, informal
sector
Employed
part time,
informal
Self-
employed
Chart 17: Description of Recent Employment
Table 22: Description of Recent Employment by Municipality, Gender and Ethnicity
Recent past employment status
Employed full
time, formal
sector
Employed part
time, formal
sector
Employed full
time, informal
sector
Employed part
time, informal
sector
Self-
employed
Freq Pcnt Freq Pcnt Freq Pcnt Freq Pcnt Freq Pcnt
Municipality
177 16.1 396 36.1 154 14.0 366 33.3 5 0.5Ga Magara Municipality
Ga Segonyane Municipality 329 16.3 887 44.0 128 6.3 618 30.7 54 2.7
Joe Morolong Municipality 140 8.2 686 40.1 121 7.1 713 41.7 49 2.9
Gender
294 11.6 967 38.2 222 8.8 992 39.2 58 2.3Female
Male 352 15.4 1002 43.8 181 7.9 705 30.8 50 2.2
Ethnic origin
580 13.3 1791 41.1 352 8.1 1539 35.3 99 2.3Africans
Coloureds 64 14.0 178 38.9 48 10.5 158 34.6 9 2.0

38
7.4 Past Sectors Ever Worked
For the participants who indicated they had ever worked for, they were asked to indicate the
sectors in which they worked for as well as the duration of engagement. Of the 4,823
participants who indicated they had once worked before, 4,268 provided information on the
sectors they had once worked as well as the durations.
Table 23: First Employment Sector Listing and Duration Employed
Municipality
TOTAL
Ga Magara
Municipality
Ga Segonyane
Municipality
Joe Morolong
Municipality
Sector once worked - Sector 1
133 15.9 369 19.3 320 21.1 822 19.3Mining
Tourism and Hospitality 22 2.6 46 2.4 93 6.1 161 3.8
Management and Others 14 1.7 58 3.0 50 3.3 122 2.9
Other Sectors 670 79.9 1440 75.3 1053 69.5 3163 74.1
Days worked under Sector 1
82 9.8 186 9.7 143 9.4 411 9.61-90 days
91-180 days 85 10.1 221 11.6 191 12.6 497 11.6
181-365 days 239 28.5 508 26.6 332 21.9 1079 25.3
366+ days (1+ year) 433 51.6 998 52.2 850 56.1 2281 53.4
TOTAL 839 100.0 1913 100.0 1516 100.0 4268 100.0
• Aside those who indicated they worked in other sectors, most of the participants
indicated they had once worked in the mining sector (822 or 19.3%) followed by those
who indicated they once worked in the tourism and hospitality industry (161 or 3.8%).
Of the participants who indicated they had once worked, most of them indicated they
worked for 366 days or more (2,281 or 53.4%).
• Aside those who indicated they worked in other sectors, most of the participants from
Ga Maraga Municipality indicated they had once worked in the mining sector (133 or
15.9%) followed by those who indicated they once worked in the tourism and hospitality
industry (22 or 2.6%).
Of the participants from Ga Maraga Municipality who indicated they had once worked,
most of them indicated they worked for 366 days or more (433 or 51.6%).
Ga Segonyane Municipality indicated they had once worked in the mining sector (369 or
19.3%) followed by those who indicated they were into management (58 or 3.0%).
Of the participants from Ga Segonyane Municipality who indicated they had once worked,

39
Joe Morolong Municipality indicated they had once worked in the mining sector (320 or
21.1%) followed by those who indicated they once worked in the tourism and hospitality
industry (93 or 6.1%).
Of the participants from Joe Morolong Municipality who indicated they had once worked,
7.5 Preferred Sector to Work
Finally, participants were asked to indicate the sectors they prefer to work. Of the 22,381
participants, 21,908 provided responses.
• As depicted in Chart 18, most of the participants indicated they wished to work in the
mining industry (11,815 or 53.9%) followed by those who indicated they wanted to work
in the tourism and hospitality industry (5,584 or 25.5%).
0
2000
4000
6000
8000
10000
12000
14000
No.ofParticipants
No. of Participants 11815 5584 1942 2567
Mining
Tourism and
Hospitality
Management
and Others
Other Sectors
Chart 18: Preferred Sector to Work

40
Table 24: Preferred Sector to Work by Municipality, Gender and Age Group
Preferred sector to work
TOTALMining
Tourism and
Hospitality
Management and
Others Other Sectors
Municipality
Gender
5184 43.9 4983 89.2 1600 82.4 1662 64.7 13429 61.3Female
Male 6631 56.1 601 10.8 342 17.6 905 35.3 8479 38.7
Age
1218 10.3 512 9.2 217 11.2 287 11.2 2234 10.218-19 years
20-25 years 5555 47.0 2316 41.5 978 50.4 1191 46.4 10040 45.8
26-35 years 5042 42.7 2756 49.4 747 38.5 1089 42.4 9634 44.0
TOTAL 11815 100.0 5584 100.0 1942 100.0 2567 100.0 21908 100.0

41
8 FURTHER TRAINING AREAS
8.1 Training Interests
Participants were requested to indicate whether or not they were interested in further training.
Chart 19 depicts the distribution of responses provided by participants. Of those who
responded, a myriad of participants (21,776 or 97.4%) responded in the affirmative.
Yes, 21776,
97.4%
No, 579,
2.6%
Chart 19: Any interest in Training?
8.2 Preferred Training Areas by Municipality
Chart 20 pictorially displays the distribution of preferred training areas supplied by participants
by municipality. Of the 21,776 participants who indicated they were interested in having training
interests, 21,562 of them indicated their preferred training areas. As revealed in Table 25:
• Most of the participants indicated they had interest to be trained in Mining (12,528 or
58.1%) followed distantly by training in Tourism and Hospitality (4,810 or 22.3%).
• Joe Morolong Municipality (6,313 or 50.4%) has the largest number of participants who
indicated they were interested to be trained in Mining.
• Males (7,004 or 55.9%) constitute the largest number of participants who indicated they
were interested to be trained in Mining.
• Participants of African origin (12,106 or 96.6%) overwhelmingly constitute the largest
number of participants who indicated they were interested to be trained in Mining.

42
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
No.ofParticipants
No. of Participants 12,528 4,810 3,314 910
Mining
Tourism and
Hospitality
Management
and Others
Other Sectors
Chart 20: Preferred Training Interest Sectors
Table 25: Preferred Training Interest Sectors by Municipality, Gender, and Ethnic Origin
Training Sector
TOTALMining
Tourism and
Hospitality
Management and
Municipality
Gender
5524 44.1 4325 89.9 2751 83.0 632 69.5 13232 61.4Female
Male 7004 55.9 485 10.1 563 17.0 278 30.5 8330 38.6
Ethnic origin
12106 96.6 4542 94.4 3080 92.9 866 95.2 20594 95.5Africans
Coloureds 419 3.3 266 5.5 232 7.0 44 4.8 961 4.5
TOTAL 12528 100.0 4810 100.0 3314 100.0 910 100.0 21562 100.0
8.3 Preferred Training Areas by Ward
Table 26 displays the distribution of preferred training areas supplied by participants according to
municipality.
• Of the 1,084 participants from Ga Maraga Municipality who indicated they had interests
to be trained in Mining were from Ward 5 (410 or 37.8%).
• Of the 5,131 participants from Ga Segonyane Municipality who indicated they had
interests to be trained in Mining were from Ward 12 (812 or 15.8%).
• Of the 6,313 participants from Joe Morolong Municipality who indicated they had
interests to be trained in Mining were from Ward 12 (574 or 9.1%) and Ward 9 (573 or
9.1%).

43
Table 26: Preferred Training Interest Sectors by Municipality and Ward
Training Sector
Mining
Tourism and
Hospitality
Management and
Municipality Ward
219 20.2 40 7.1 120 28.8 11 9.9Ga Magara
Municipality
Ward 1
Ward 2 200 18.5 140 25.0 44 10.6 32 28.8
Ward 3 140 12.9 96 17.1 75 18.0 15 13.5
Ward 4 115 10.6 190 33.9 93 22.3 16 14.4
Ward 5 410 37.8 95 16.9 85 20.4 37 33.3
TOTAL 1084 100.0 561 100.0 417 100.0 111 100.0
Ga Segonyane
Municipality
Ward
410 8.0 199 12.6 69 5.6 8 3.0Ward 2
Ward 3 485 9.5 130 8.3 235 19.1 53 20.0
Ward 4 525 10.2 105 6.7 71 5.8 1 0.4
Ward 5 417 8.1 126 8.0 105 8.5 34 12.8
Ward 6 444 8.7 114 7.2 59 4.8 21 7.9
Ward 7 373 7.3 220 14.0 61 5.0 7 2.6
Ward 8 392 7.6 161 10.2 113 9.2 12 4.5
Ward 9 231 4.5 72 4.6 62 5.0 35 13.2
Ward 10 330 6.4 130 8.3 99 8.1 15 5.7
Ward 11 506 9.9 110 7.0 84 6.8 3 1.1
Ward 12 812 15.8 162 10.3 155 12.6 68 25.7
Ward 13 206 4.0 46 2.9 116 9.4 8 3.0
TOTAL 5131 100.0 1575 100.0 1229 100.0 265 100.0
Joe Morolong
Municipality
Ward
323 5.1 164 6.1 135 8.1 20 3.7Ward 1
Ward 2 475 7.5 152 5.7 110 6.6 13 2.4
Ward 3 255 4.0 123 4.6 78 4.7 14 2.6
Ward 4 60 1.0 51 1.9 23 1.4 12 2.2
Ward 5 523 8.3 175 6.5 133 8.0 9 1.7
Ward 6 446 7.1 154 5.8 130 7.8 39 7.3
Ward 7 503 8.0 208 7.8 94 5.6 3 0.6
Ward 8 368 5.8 107 4.0 116 7.0 26 4.9
Ward 9 573 9.1 275 10.3 179 10.7 122 22.8
Ward 10 527 8.3 236 8.8 158 9.5 106 19.9
Ward 11 483 7.7 255 9.5 67 4.0 42 7.9
Ward 12 574 9.1 312 11.7 115 6.9 90 16.9
Ward 13 510 8.1 242 9.1 134 8.0 19 3.6
Ward 14 389 6.2 164 6.1 172 10.3 19 3.6
Ward 15 304 4.8 56 2.1 24 1.4 . .
TOTAL 6313 100.0 2674 100.0 1668 100.0 534 100.0

44
Table 27: Preferred Training Interests Sector by Training Area
Freq Pcnt
Training Sector Area under Training Sector
847 6.8Mining Mining: Driller Assistant
Mining: Fitter 1643 13.1
Mining: Electrician 3231 25.8
Mining: Welder 1611 12.9
Plumber 1265 10.1
Mining: Earth-moving Equipment Operator 896 7.2
Mining: Support Worker 2462 19.7
Mining: Loader 290 2.3
Mining: Other 277 2.2
Management: Human Resources 1 0.0
Management: Marketing 1 0.0
Other Areas 4 0.0
TOTAL 12528 100.0
Tourism and Hospitality Area under Training Sector
688 14.3Tourism: Room Attendant
Tourism: Waiter 975 20.3
Tourism: Cook 2002 41.6
Tourism: Crafter 54 1.1
Tourism: Maintenance 407 8.5
Tourism: Guide 136 2.8
Tourism: Driver 438 9.1
Tourism: Other 110 2.3
TOTAL 4810 100.0
Management and Others Area under Training Sector
2 0.1Mining: Other
Management: Finance 289 8.7
Management: Human Resources 849 25.6
Management: Supply Chain 31 0.9
Management: Marketing 348 10.5
Management: Operations Manager 96 2.9
Management: Health and Safety 654 19.7
Management: Food and Related 79 2.4
Management: Security 558 16.8
Management: Receptionist/Clerical 408 12.3
TOTAL 3314 100.0

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Table 27 presents the distribution of the preferred training sector interests according to the
three core areas.
• Of the 12,586 participants who indicated they were interested to be trained in Mining:
Most of them were interested to be trained as electricians (3,231 or 25.8%), followed by
those interested to be trained as support workers (2,462 or 19.2%).
• Of the 4,810 participants who indicated they were interested to be trained in Tourism
and Hospitality, most of them were interested to be trained as cooks (2,002 or 41.6%),
followed by those interested to be trained as waiters (975 or 20.3%), room attendants
(688 or 14.3%), and drivers (438 or 9.1%).
• Of the 3,314 participants who indicated they were interested to be trained in
Management-related areas, most of them were interested to be trained in Human
Resource Management (849 or 25.6%), followed by those interested to be trained in
Health and Safety (654 or 19.7%), and in security (558 or 16.8%).

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9 KEY AUDIT FINDINGS AND POLICY TASKS
9.1 Introduction
Youth unemployment has become a major development challenge globally. Undeniably, social and
emotional integration of youth is essential for sustaining the very fabric of every society. It is,
therefore, important that governments design and implement strategies for youth employment.
This is especially so for developing countries like South Africa. However, in most developing
nations, the youth enter the workforce at the end of the queue and naturally have relatively
lower skill levels and experience than older groups. This tends to place them at a structural
disadvantage in the labour market. There is therefore the need for development and
implementation of intervention strategies that will bring the unemployment situation in the John
Taolo Gaetsewe District Municipality to some reasonable level.
9.2 Potential Consequences of Audit Findings
South Africa is saddled with an enormous unemployment challenge. In general, for every young
person, having a decent job is an important step in completing the transition to adulthood, an
achievement towards independence and self-reliance. For young people living in poverty and in
disadvantaged communities, employment is often the main means for attaining a better life.
Socially, youth employment promotes integration, intergenerational dialogue and solidarity.
Making available income-generating job opportunities for young people can have direct positive
consequences for poverty alleviation. In a sense, youth employment benefits social development.
On the contrary, the lack of employment, especially among young people, often comes with it
immeasurable consequences.
9.2.1 Deepened Unemployment
Growing and persistent youth unemployment has a negative impact on social development.
Unemployment among the youth, in particular long-term youth unemployment, can generate
frustration and low self-esteem and low self-worth. Youth unemployment can also lead to the
marginalization and social exclusion of young people. The literature argues that unemployment
can expose youth to greater risks of lower future wages, repeated periods of unemployment,
longer unemployment spells as adults. Unemployment rates are typically higher for youth in rural
areas than their peers in urban areas.
9.2.2 Future Employability
For unemployed youth lacking basic education, failure to find a first job or keep it for long can
have negative long-term consequences on their future employability, a scenario some experts
describe as ‘scarring’. There are many constraints related with lack of employability. These
include preference by employers for experienced workers, lack of work experience, poor quality
in the education, and inadequate preparation of the youth in career development.

47
9.2.3 Lack of Income
From an economic perspective, youth unemployment means loss of output to the economy and
lack of income to the families of the unemployed. Lack of income on the part of the unemployed
youth and the inability to purchase basic necessities, such as clothing and hygiene supplies,
contributes to a reduced self-esteem in youth experiencing periods of unemployment.
9.2.4 Entrenched Poverty
Poverty is closely linked to the structural problems of unemployment and the lack of skills;
unemployment affects poor households most severely. Repeat periods of unemployment and
prolonged unemployment, especially among young people, often lead to generational poverty.
Entrenched poverty seriously affects full participation in civic life. Young people experiencing
generational poverty are at an increased risk of experiencing lower wages as adults, should they
become employed in the future. If not addressed in time, generational poverty could continue
unless the unemployed youth receive outside intervention.
9.2.5 Inequality
Lack of income resulting from youth unemployment can generate to an aggressive feeling toward
what is perceived as a social bias. Social inequalities, resulting from prolong unemployment has
the potential of threatening existing social cohesion. Racial inequality also undermines all efforts
to build a non-racial society. Monetarily, income inequality has been found to greatly contribute
to crime. In Europe, unemployment and income inequality have become markers of social
cohesion.
9.2.6 Social Ills
Long periods of youth unemployment often mean vulnerability of the youth to other social ills.
Drug abuse and crime are major consequences that are mentioned in many studies of youth
unemployed. More recently, studies have shown that unemployment causes more crime not only
as property-related ones but also violent crimes. Having virtually all the time on their hands, and
the opportunity to participate in socially deviant behaviours, unemployed youth are at risk of
being involved in criminal activity. In addition, unemployment is argued to have a much deeper
impact on the community by creating a severe social disorganization that is all the more difficult
to reverse, eventually leaving a community helpless towards the cycle of crime.
9.2.7 Community Economic Development
With a larger fraction of the young people within a community unemployed, the community
experiences a decrease in human capital. Increased unemployment among the youth in the
community means decreased consumer spending within the community. A community having a
larger proportion of unemployed youth means a decreased amount of taxes being paid.

48
Consequently, high level of unemployment among the youth in a community has the potential to
affect the future economic development of the community.
9.3 General Recommendations
Unemployment among youth is a delicate issue. Drastic measures are needed to bring the level of
youth unemployment to a reasonable level. In some countries, direct job creation and subsidies
to private sector employers have shown to work in the case of reducing youth unemployment. In
Australia and most European countries, training and employment programmes provided by
governments for disadvantaged youth who have not graduated through the mainstream education
system or vocational pathways have yielded some encouraging results.
While making this argument, it is also important that prevention and early intervention strategies
be adopted if youth unemployment is to be reduced in the Municipality. Based on the findings
from this study, the following general recommendations are suggested.
9.3.1 Wide Publication and Dissemination of Findings to Relevant Role Players
In social research, it is vital that the final survey report be prepared and disseminated to relevant
audiences. It may be useful for stakeholders from the government and the John Taolo
Municipality and other interested organizations, especially the mining sector to attend a
dissemination meeting where the survey results are presented and discussions held on the
findings. Use of stakeholders’ meetings as a complementary activity is important. This type of
forum encourages discussion and invites input from a wide array of experts, ultimately helping to
address a pending issue while contributing to a shared knowledge base about it. It is also possible
to give feedback from the survey results to members of the communities involved.
In the context of this study, such a forum for dissemination of findings can also serve as a tool to
engage those communities in finding solutions to the unemployment issues. By and large, it
should be beneficial that findings from this study be published and to make the findings available
to a wider audience. Options that can be explored include posting it on the municipal website
and municipal bulletins. Publishing of the survey findings could contribute to the growing evidence
base for effective management of unemployment and skills gap among young people in the John
Taolo Municipality.
9.3.2 District Skills Information Management System
At the time of conducting this study, there is basically no institutional mechanism that provides
credible information and analysis with regard to the skills demand for young people in the John
Taolo Gaetsewe Municipality. While it is recognized that there are a number of disparate
information databases available, there is virtually no standardized framework for determining
skills levels of youth aged 18-35 years in the municipality. To address the issue, this study has
included the setting up of municipal-wide a single information-generating system or database of
young people aged 18-35 years, their level of skills, competences, educational levels, training
needs, and presences for training.

49
9.3.3 Matric Mathematics and Science Improvement Programme
Mathematics and science are the keys to innovation and power in today’s world. Exposing high
school learners to mathematics and science and improving the preparation among high school
learners must be a high priority for the John Taolo Gaetsewe Municipality. In addition, the John
Taolo Gaetsewe Municipality should consider expanding the awareness, understanding, and the
importance of mathematics and science to the youth, especially high school learners in the
municipality in modern workplace, and to the future economic growth and prosperity of a nation.
To better tackle the issue of low-level knowledge of mathematics and science, the John Taolo
Municipality should consider setting up a mathematics and science improvement programme to
help address the situation.
9.3.4 Role of National Youth Development Agency
Youth development in the John Taolo Gaetsewe Municipality, especially regarding youth
unemployment, cannot be addressed by the Municipality alone. The John Taolo Municipality can
bring on board, the National Youth Development Agency (NYDA). The mandates of the NYDA
are geared towards skilling and empowering young people and alleviating the unemployment
challenge in societies. The John Taolo Gaetsewe Municipality can partner with the NYDA to
initiate youth development initiatives so that sustainable solutions to the unemployment and un-
skilling challenges faced by youth in the municipality can be addresses.
9.3.5 Forge Partnerships to Provide Training and Skills Development
Education and training is the key ingredients in the economic and personal development of any
community. The lack of it has the potential of generating upheavals, especially among the
unemployed youth in the community. By forging partnerships with the relevant entities,
appropriate skills development programmes can be developed, could enable the unemployed
youth in the Municipality to acquire the necessary skills and qualifications that will enable them
confident to apply for jobs needed by the local industry and enter the job market.
• Based on the findings from this study, it is unequivocal to state that there is an immediate
need for the forging of a partnership among the John Taolo Gaetsewe Municipality, local
industries, especially the mining and hospitality industries, and training providers, with the
task of providing the appropriate skills training that will equip the unemployment in the
District for job market.
• Also, the fact that there may be some industries that may be willing to provide
technical/artisan skills training, especially the scarce ones, it is recommended that the John
Taolo Gaetsewe District Municipality consider taking the initiative to engage such
companies and training providers to help in the training of scarce skills that have been
identified in this study for the unemployed youth.

50
9.3.6 Better Coordination of Training and Skills Development Initiatives by the
Mining Sector
The mining sector, particularly those one located within the John Taolo Gaetsewe Municipality
should regard findings from this study should be able to used as a tool that will better help the
coordination of training and skills development required by youth in the municipality. Based on
the findings, a more appropriate mechanism can be designed to provide such training to the
unemployed and unskilled youth in the John Taolo Gaetsewe Municipality. Undoubtedly, by
provided the needed training and skills training will go a long way to make youth in the John
Taolo Gaetsewe Municipality employable.
9.3.7 Working in Collaboration with Government Departments and Department
of Labour
Constitutionally, the Department of Labour is mandated to help address such issues as youth
unemployment by providing funds for skills development. The Taolo Gaetsewe Municipality can
bring on board the Department of Labour in its efforts to address youth unemployment in the
Municipality to provide training for the unemployed youth. One or more of the methods listed
above can be used to establish training centres were unemployed and unskilled youth can be
trained. The Department of Labour’s only funding requirement is that at least 70% placement on
successful completion of the training for at least three months. The following approach can be
used by the Municipality to successfully bring on board the Department of Labour.
• The Municipality can write to the Regional Manager of the Department of Labour
explaining the need for funding and mention the results of the skills audit conducted.
• The Municipality must engage relevant companies and organization who will be willing to
take in unemployed youths for placement.
• The willing organizations must then write letters confirming placement of the unemployed
youths that would be on training. Typically, organizations, having satisfied themselves with
the arrangements with the Department of Labour, accept the proposal from the
Department.
• Once the Municipality receives letters confirming the placement of the unemployed
youths, the municipality attaches them to the funding proposal which is then submitted to
the Department of Labour.
• Once accepted by the Department of Labour, the Municipality then acts as a Project
Manager during the implementation of training.
9.4 Conclusion
This skills audit was conducted with the aim of gathering information on the level of
unemployment of the youth in the Taolo Gaetsewe Municipality. Findings from the audit

51
indicated the skills needs of the youth in the Municipality require a concerted effort from all
relevant stakeholders. The Taolo Gaetsewe Municipality can take a lead to addressing these skills
needs by ensure that the demand for skills in the Municipality is met.

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