SECOND CARNEGIE INQUIRY INTO POVERTY

AND DEVELOPMENT IN SOUTHERN AFRICA

, ;1 , I Spatial variations in the levels of living in the cape JretroJXllitan area by N Riley, C Schtmrul, P JOnanovsky and R Gentle Carnegie Con£erence Paper No. 13

Cape Town 13 - 19 April 1984

, ISBN 0 7992 0823 X CONTENTS l'age

INTRODUCTION

LEVEL OF LIVING INDICATORS : A COMPOSITE INDEX 3

I NCOME DIfFERENCES AND THE lNDEX OF INCOHE INEQUALITY

OTHEH CONS] DERATIONS 9

"EPENDENCY RATES AND ACTIVITY RATIOS 9

OCCUPATION 12

EDliCATION 13

HOUSING 13

HEALTH 15

CRIME 16

CONCLUSION 17 LIST OF TABLES

1. Composite index for rich (low scores) and poor (high scores) suburbs

2. Mean Head of Household'and Personal Income

3. I ndex of Income J 11('4ua 1.1 ty for Bel ec ted suburbs

4. CombIned ind{,x of lncom" Inequality, dependency ratios and ActivIty rBtes for Relected suburbs

5~ PPf('f.'lll<:Jge 01 WId tt' and hluf> coJ Jar workers in selected subtlrbs

6. Housing Densities and room occupancy rates

7. Violent crime rRtes and the composite index by selected suburbs

LIST OF FIGURES

1. Composite Indicator of levels of living

2. Income inequality

APPENDICES

1. Table showing composite index scores

2. Figures of IndivIdual indicators

3. Tables of indivIdual indicators

4. Figures of Mean Head of Household and Personal Income

5. Formula for the index of income inequality

6. Table showing index of income inequality

7. Table shoWing frequency distribution of head of household income by number of persons per household (01 Region)

8. Table showing education levels for selected high and low income suhurbs

9. Spatial distribution of tenure

10. Spatial distri but ion of housing densi ties

11. Spatial distribution of occupancy rates

12. Table showing frequency distribution of number of habitable rooms per dwelling by number of persons per household (01 Region and Kullsriver) ,------

• " ..... oyF.~ "A~~ • ~nANGA

GREATER (01 REGION ANO KUILSRIVER) r SELECTED SUBURBS E TOWN METROPOliTAN TRANSPORT AREA

(01 REGION AND ' 1980 CENSUS - LOCAL ARtAS \1 • "To d.o better we must have game "'ay of ·distinguIshing

better from worse." Rivlin

INTRODUCTION

1. If it i.s 8("crptf'd th"t the injunction "It is not given to m"n to I,now

I.he truth but 1.0 Beek the truth", Is true, then It is lalso) ;,c,""pt •. d

that knowledge of re"lity is relative. lie have at our disposal

concepts and tools (in the heuristic sense) which we use in order to

describe reality. These concepts and tools, however, are not value

free, and the situation often occurs when the concepts used in social

analysis differ subtly in meaning when apparently addressing the same

phenomena or even, in extreme cases, differ diametrically (e.g. the

concept "democracy").

2. The problems of sodal analysIs are further compounded ",hen, wIthin

the same paradigm, consensus cannot be reached on the validi ty or

acceptability of certain concepts.· One "'ay out of such an impasse is

to consider concepts operationally as they are used in particular

studies. An acceptance of limitations imposed by working definition~

at least allows the researcher the room to develop hls ideas or

analysis coherently, that is, the discourse is internally logical.

3. While the Carnegie Inquiry has as its focus the understanding of the

extent and causes of poverty in Southern Africa, it must be accepted

that the concept poverty does not eaSily lend itself to description,

let alone definition. The problem has two dimensions, on the one

hand, conceptual/theoretical difficulties and, on the other, the

limi tations of available data; the conceptual/theoretical

difficulties relate to the problem of measurement, both 2 I

quantitatively and qualitatively. ]s poverty to he considered in

absolute terms or relative terms? Researchers are generally agreed

that it is highly improbable that poverty will ever be defined

absOlutely in a satisfactory manner, and for the purposes of the

paper thp issu~ of absolute poverty is not considered at all.

He]at tve poverty though itCh greater appeal af-i Ii mf~aSUrf:" since it Is a

much hroader COIlCP!'t and since it inherently has a dynamic

dimension. A definition, which captures the fluidity of relative

poverty admirably, reads "People are 'poor' because they are deprived

of the opportunities, comforts, and self-respect regarded as normal

in the community to which they belong. It is therefore the

continually moving average standards of that community that are the

starting points for an assessment of its poverty, and the poor are

those who fall suffIciently far below these aVE'rage standards."l.

Yet, however appealing such a definition may be, it stUI does not

address itself adequately to the notions of "self-respect" ,

"happiness", "misery" etc.

,. The issue of data availability is a further limitation on the

understanding and description of poverty. This paper draws heavily

on da ta ext racted f rom the 1980' Census and While census data itself

imposes restrictions on social research, the problem becomes

exaggerated when not all the information is available and, at the

same time, is available only in the form of a 5% sample. Given the

]jmi tatIons of the available data, as ",ell as the grey areas of

subjectivity in the concept of relative poverty, this paper will

address itself to an appraisal of levels of living in the Cape

Metropolitan Area. 3

5. It must be quite clear from the outset that thts pap~r is exploratory

and descriptive in nature. It is by no means intended as a

definitIve statement of territorial well-being. The notion of levels

of living therefore Is offered as ~ proxy indIcator for relatIve

d'·rrfv~tfon.

LEVELS or LIVING INDICATORS A COMJ'OSlTE J NIJEX

6. For the purposes of this paper, a level of living is defined

operationally as that which is constituted by the overall composition

of income, housing, education and employment aggregately exhibHed

within a given geographical area, together wIth those aspects of

demographic structure, general physical environment and consumption

of goods and servIces which may determine the extent to whIch the

needs relating to the foregoing constituents of level of lIving can

be, or are, met. Although this def.i.nition addresses 'itself to the

factual circumstances of well-being, it has built-in limitations;

the political dimension (democratic partIcipation, etc), leisure,

social security and social ~tatus are not considere~ for the purpose

of the study.

7. The derived composite Index for inter-suburb comparison is likely

to have greater usefulness than the individual indicators, which can

be unwieldy measures of what is essentially a unitary concept.

Notwi thstanding Townsend's stat emen t, "We should ff rs t understand

individual indicators before comhining them into complex indices"2,

it is tel t tha t the foregoing assertion is necessary as a point of

departure. In this regard there is a greater correspondence with

Smi th, "As long as the defects of existing data are recognised and f.tllprovf~ment:6 are conFltRl1t1y sought a useful atart can bp flJ(-Id~ 011

describing Borne Important dimensions of human existence conspicuously

missing from (ll(' conventional view of the ",,,rld,,.3

FurtlH'rIl10re, 11 is .1rkTH)\ •.df .. dg<:>d that in the confilTuction of thf'

composite index tlte 1i,,"fI,od of ",etghtl.ng is arhitrary and Rubjpct to

r{~searchf'rs, ;11 though not BS a deterrent; they feature, inter alta,

~ Dre",nowski and Scott I.n their "The Level of Living Index" ana

Reilly5 in her "Social Indicators."

8. Given the data constraints in the construction of the level of living

index for the Cape J.letropol1tan Area, seven proxy indicators \,if" ..

used as base Ol.1:terjal, viz. These were chosen in such a "'ay that

weJghting of the var.iables occurred implicitly. Generally the

weighting "'as related to recognised standards, for example, income

limits were imposed by the Bureau of Market Research 19/10

supplemented living levels, occupancy rates per room by the British

natlonal housing spec:fLicat.i.ons, shared accommodation by the measure

of one family per dwelling unit, car ownership by one car per

househol d, workers' educational level s by previous minimum levels

under the Apprenticeship Act, single mothers with more than three

children and finally, unemployment by actual levels per suburb.*

9. These variables were selected to represent, amongst them, the

character and composition of the major components of the Census. In

this case the diagnostic variables "'ere selected in such a way that

each was highly associated with at least One of the other six

* Suburbs have been matched approximately to Census Local Areas. In

some cases there is a total correspondence and in others not. 0= HIGH 100 = lOW

m33.80 - 63.34 .• 16.36 - 33.80 1IllIlII7.27 - 16.36 § 4.27 - 7.27 [[0 0.62 - 4.27 00.00 - 0.62 INDEX PRODUCED BY REATER CAPE TOWN CAL FORM LOCAL AREA BASE seAL

1980 DIREctOR OMPOS IT E IN DI CA TOR 1:836000 CENSUS TECHN'~~~v7~;~GEMEN F LEVELS OF LIVING

Figure 1 components (wlth a correlation of .:!:0,6< or more). TllIlS, if Wt,

consider a pair of variahles the correlatlon implfes that, in tlot·

matlH'matl.cRl RenHe at le"6t, and probably also in the conceptual

senRe, there 1 s nn "l "II'"nt of substitutability between the varl. ahles.

]0. Till' spati;l] (s11hllrh) 1 r(:quPllcJes jn pt'Tcentage scores for (';,t'l:

varjable was transformed onto a linear Reale to generate a new f;et of

scores for each varlable On a range 0 to 100, where ° represents th"

suburb with the lowest (j .e. most desirable) incidence and 100

represents the hIghest (.I.e. the worst). After transformaUon, all

the seven 6cores were summed for each suburb, on the assumption that

they contribute equally to living levels (given the weighting

constraints). The composite indicator was arrived at by divIding the

sum by the n\~ber of varIables. The living level index is not itself

on a scale of 0 to 100 hecause no suburb scores 100 on all variables,

but composite indices arrived at in this way do show that any suburb

with a score of ° must have the equivalent of the lowest (best) value

on all contributing v;,riables, and one with 100 must have the worst

performance of them all. (See Figure 1 for spatial representation).

TABLE I COMPOSITE INDEX FOR RICH (LOW SCORES) AND POOR (HIGH SCORES) SUBURBS

HIGH LOW

SUBURB SCORE SUBURB SCORE

Kalksteenfontein 63,3. Plattekloof 0,00 Lavender Hill 61,13 Neadowridge 0,7 I Valhalla Park 59,17 Kingfisher Estate O,lj~ Newtown 56,93 Bishopscourt 1,05 53,3. Llandudno 1,19 53,20 Dunrobin 1,32 Parkwood 53,16 Thalman 1,50 52,9. Eversdale 1,52 Matroosfontein 52,50 Edenpark 1,60 RurAl 52,38 Akasia Pa rk 1,65

See Appendix I for a nlore cOlIlprehensive table 11. The above table shows the relatIve positions of selected suhurbs

(some of the best and some of the worst). The composi te indicator is

responsible for smoothing the sharp differences hetw""n indf.v.idual

indicators, due largely to the fact that two varf.rlbJes, namely,

sing)e mothers with mOTe than thrpp c1d1dren and un(!mp]oYlJlent rates,

g~lIe~<111y regi.slered ]ower' frt:'quellctcs tll;]n t.h(~ other variables. Iii

the first case the effect is most prohably due to the way th~

variable was defined; in retrospe<;t it would appear that a better

definition should read as follows: single mothers wlth two or more

chUdren. However, the constraints of time and extent (more than 300

Local Areas in the Metropolitan Area) meant that the original

definition had to be retained. Secondly, while unemployment rates

fluctuate markedly from area to area, they average out at

approximately 10%. WhUe this did not markedly affect the scores of

the more affluent areas which regIstered low scores, it certainly

lowered the scores of the more deprived areas; no score higher than

63,34 was registered.

12. There were three "maverick" suburbs as far as the composite index

scores were concerned, namely, Guguletu, Langa and Nyanga •. Contrary

to expectation, all three registered lower scores than expected in

relation to other areas, in fact they did not appear in the ten worst

off suburbs in the metropolitan area at all. Upon examination of

their scores on individual indicators it appeared that their scores

were a function of influx control and the Singular position of

Africans in the . It is generally accepted that the

African areas were underenumerated. On 'shared accommodation',

'single mothers with more than three children' and 'unemployment' all

registered low scores while o!, the other indiv.1.dual indicators they

were amongst the highest scoring suburbs. (See Appendix 2 for a

graphic distribution and Table 3 for a statistical representation of

extremes in living levels between the richest and the poorest suburbs.) INCOME DIFFERENCES AND TilE INDEX OF INCOME INEQUALITY

13. In a free market society such as ultimately the abJliLy

to pay Is the single most lu~ortant criterion of well-b~jng

c(~rtainly liS far as Ilw COIHiulllpti..on of eoods and b(+rvict:B .iE.

c()nc(·nwd. Thus the dil;paraties in incolllf- tynt;ral1y PYt.;Vt: d(~cj.s.ivl...

in distinguishing One arl:8 from auother. Ideally an analysIs of

income patterns which would inform an understanding of poverty should

have as its basis the family and/or the household income, that is, as

the central unit consuming goods and services. However this was not

possible as only head of household income and personal income figures

were available frow the 1980 Census. What is readily apparent

though, is the facl that 49,23% of all income earners earn less than

R3 000,00 per annum in the metropolitan area - an Income picture that

bodes no good for the living levels of the majority of persons living

in this area. l~e spatial variations in head of household income and

personal income are shown graphically in Appendix 4. These are

complemented by the following table showing median income for both

categories in affluent and poor areas.

TABLE 2 : MEAN HEAD OF HOUSEHOLD AND PERSONAL INCOME FOR SELECTED SUBURBS

HIGH INCOME AREAS LOW INCOME AREAS

Mean Mean Mean Mean Suburb Head of Personal Suburb Head of Personal Household Income Household Income Income Income

Welgemoed 20495,45 11651,53 Newtown 1003,33 1208,57 PIa tt ekl oof 18625,00 11004,54 Himosa Park 1150,00 1115,38 Bishopscourt 25238,63 13812,24 Ka1ksteenfontein 1481,57 1433,67 Penzance Est 13812,50 11071,42 Kraaifontein Rural 1400,00 1300,00 Kenridge 16056,33 12053,81 Valhalla Park 1554,34 1363,49 Constantia 18614,96 10361,64 Steenberg 1704,54 1440,00 Newlands. 15835,90 10552,27 Ilangberg 2000,00 1592,46 Chantecler 15937,50 9900,00 Lavender Hill 1990,65 1709, ':Il Fresnaye 15776,80 9053,19 Kew Town 1988,88 1773,52 Llandudno 15125,00 13353,57 Schotse Kloof 2365,00 1983,51 04893.05 - 16336.60

[[] 2215.00 - 4893.05 ~ 409.05 - 2215.00 g -1095.20 - 409.05 III -3121 .35 - - 1 095.20 E;;I-5337.80 - -3121.35 INDEX PRODUCED CAPE TOWN BY AREA BASE CAL FORM seAL ... . N.W.RIlEY ~~~ ~ MS 1.836000 "#;. w 1980 DIRECTOR INC 0 ME '-l ~ TECHNICAL H~N~GEMEN INEOUALITY <- ~ CE NS US SERVICES

Figure 2 8

]~. In order to approach tll{' issue of poverty or deprivation fJolI! nnoth('r

angle, an index of income divergence/inequality used by Smlll,t'

adapted to 11 lilstrat" Once again the sharp dlvergences In the

metropolHall Rrea. The derived index serves to illustrate the (kgree

to which ~rt'a!:; d1vcq:e frolTJ "f~qualfly" :f.f th~ norm Is C:(Jn~frlprf'd t(1

he the .1oCOHl(' Ct-It"t-f,ory, t:fvf'n thE' dfst.rlbutfon of income, .int() which

every earner should fall If they were deemed to be ··equal··. In thIs

partIcular study, head of household income was used (see Appendix 5

for an explanation of the formula). The table below shows the

divergence in scores of selected suburbs while Figure 2 shows the

total spatIal distribution graphically.

TABLE 3 1 NDEX OF 1 NC()~IE 1 NEQUALl TY FOR SELECTED SUBURB S

HIGH INCOME AREAS LOW INCOME AREAS

SUBURB 1 NDEX OF SUBURB INDEX OF I NEQUALlTY INEQUALl TY

Welgemoed + 11999,7 Newtown - 5181,5 Plattekloof + 11695,1 Mimosa Park - 4937,8 Bishopscourt + 10041,4 Kalksteenfontein - 4816,2 Penzance Estate + 9624,4 Kraaifontein Rural - 4787,8 Kenridge + 9603,5 Valhalla Park - 4747,4 Constantia + 9387,5 Steenberg - 4!JlS,O Newlands + 8184,9 Hangberg - 4409,6 Chantecler + 8143,3 Lavender Hill - 4370,3 Fresnaye + 7376,1 Kew Town - 4255,0 Llandudno + 7309,9 Schotse Kloof - 4249,0

See Appendix 6 for a more comprehensive table

15. The Ruburbs depicted in the above table were deliberately selected on

a non-random basis. Since the areal scores derived correspond

over-all to the same patterns exhibited by the composite index, it

was felt that selected suburbs (subjective bias) would suit the

purpose of the exercise. The greatest departures from equality of

distr.l huUon (L c. high indices) correspond wi th high income areas, 9

as m.lght be expected. The question 01 how far observed scores in

this region were inequi table or unjust is beyond th~ scope of tI,..

present discussion, 'however such questions cannot he asked or

answered unless Inequality can be measured. CertRinly, whatever

thresholds are accepted, the poverty they dpf1.ne could be eliminatpd

by raIsing thl' whole population ahov(·

relationships 'between people. !nequa11.ly, on the other h~nd, can

only be eliminated by changing relatIonships hetwl'en people, between

regions, between classes, and between etholc groups. EquaHty would

eliminate poverty, in this sense, whether the average standards

achieved were higher or lower than the present averages.

OTHER CONSIDERATIONS

16. An index of income inequality, of course, has its own limitations;

fundamentally, it says nothing about total wealth, for example,

property, investments, saving,; and inheritance. It also cannot

incorporate fringe benefits, .ubsld!es etc. However, as a measure of

remuneration for services or work performed, it does allow an

indication of the "gaps" that exist in society. As a tool for

analysis, when coupled with other indicators such as dependency

ratios, activity rates and occupations for instance, reasonable

inferences can be made about general conditions in the metropolitan

area.

Dependency rates and activity ratios

17. A dependency ratio consists of the number of non economically active

to every 100 economically active persons in a given population, while

an acti~ity rate refers to the proportion which employed and 10

ulIl'mploypd perROIlS form of the total population. The following tahle

111llRtrRt"s qutte ,"arply the vastness of the "gaps" which exist in

the u,etropo1ftan area.

TABLE 4 COMHI NED ] Ni)I':>: OF J NCOME J NEQUALJ TY , DEPENDENCY RAT! OS AND ACTIVITY RATES FON SELECTED SUHURHS

I1I.CIl J NeONE AREAS

SUBURB DEPENDENCY RATIO INDEX OF ACTIVITY RATES INEQUALITY

Fresnaye 49,6 + 7376,1 48,2 Newlands 45,6 + 8184,9 49,39 Constantia 55,0 + 93B7,5 45,00 Bishopscourt 22,8 +10041,4 4~,30 L1and'udno 21,1 + 7309,9 54,17 Penza nee Estate 33,3 + 9624,4 58,33 Chl!ntec1er 75,0 + B143,3 37,50 Dunrobin 76 t 4 + 7344,1 41,13 We1gemoed 55,3 +11999,7 40,0 Kenrl.dge 67,3 + 9603,5 37,27 Plattekloof 46,2 +11695,1 47,B3

LOW JNCOME AREAS

Scottsdene 61,0 - 4070,0 43,07 Valhalla Park 104,7 - 4747,4 27,50 Kalksteenfontein 68,0 - 4B16,2 33,60 Mimosa pI! rk 176,9 - 4937,B 25,00 Kraaifontein Rural 166,7 - 47B7,8 33,33 Ne.'town 41,5 - 51Bl,5 58,62 Kewtown 60,0 - 4255,0 37,42 Lavender Hill 76,9 - 4370,3 31,75 Hangberg 78,8 - 4409,6 3B,27 Steenberg Bl,8 - 4415,0 31,67 Ocean View 85,7 - 3786,5 31,21 Bonteheuwel 63,7 - 4088,3 38,12 Epping Forest 83,5 - 4831,5 39,03 Nooitgedacht 75,0 - 4019,2 34,48 Sa repta I 11,5 - 3268,3 29,06

18. The large degree to which the affluent areas deviate from the norm is

remarkable. This difference is further exaggerated by the effect of

the corresponding activity rates and dependency ratios. Thus, for

instance, WelgE'moed, Plattekloof and Bishops Court all have the

activity rates of 40 or more (relatively,high) and dependency ritlos

of acceptable proportions when compared to the more deprived areas 11

such RS, for example, Kraatfontein's rural hinterland, Valhalla Par,

and Sarepta. The poorer areas, convprsely, also have lower Rctivity

rates. ThIs means in real terms that the former areas, While not

only having .. xrel'dlngly higher levels of Income (h"ads of households)

8]60 Ilave fewer deppnrieJlt per~ons ~ndt at the ~alne tj.me, nl()re people

..",rklng. Ilence when income from other "arners 'is added (assuming they

have roughly the same relative Inter-suburb dJstrJbutJon, disposable

income must diverge even more.*

19. Applying the Bureau of Market Research's Minimum LivIng Levels for

households ranging in size from 1 to 8 persons per household, it is

illuminating to see that for coloured households (the largest ethnic

component by far in the region) some &8,8% of households fall below

mt ntmum income levels. The matrix from which this statement is

derIved however does not incorporate the number of workers per

household. Undoubtedly their (workers) presence would supplement

household income and certainly modIfy the gross percentage. An

indication of its modifying Influence is offered by the figure of

3,6& workers per household in the coloured group for the region as a

whole. Notwithstanding their modifying Influence, the general

position still appears to be one of considerable deprivation (see

Appendix 7 for a frequency distribution of head of household income

by number of persons per household - 01 Region).

* An examination of the spatial patterns of Appendix & showing personal income, will confirm this assumption 12

OCCllpat ion

20. An lnt('gral component of deprivation, in so far as it 1s A prime

determinant ·of income, is occupation. This assertj on is made in

support of Rp I HS wilo ilia I nl a j ns t ha t, "wh11 e We may think of income as

hejn~ rf'ceived "'OTf' or Jess s:tmuJtan('o1Js]y with the purfiuJt of ali

occupation, it is l rue that most of the income received from an

occupational pursuit accrues subsequent to the entry Into and

Identification with that occupation. There is a sense, then, in

which occupaUon may he considered logically or temporally prior to 7 income, as well as fllnctionally relRted thereto· • Thus a spatial

Indication of skIlled, semi-skilled and unskilled persons by actual

occupational catego!".ies would go A long way in furnishing the

understanding of .1 Ivi ng levels in the metropolitan area.

Unfortunately, this was not possible given the census constraints On

available information. Instead, whAt is offered is a slightly cruder

distinction between white collar workers and blue collar workers.

Crude as this distinctJ.on may be, it certainly supports the above

mentioned hypothesis that income and occupation are "functionally

related". WIIE'n one considers the table below then it is quite clear

that the high income areas have a larger proportion of white collar

workers than blue collar workers and, conversely, the poorer areas

have a higher proporti.on of blue collar workers than white collar

workers. 13

TABLE -5 PERCENTAGE Of WHITE AND BLUE COLLAR WORKERS IN SELECTED SUIlURBS

LOW INCOME AREAS

Valhalla Park Mimosa Park Kraaifon- Epping Sarepta tein RurAl Forest

WHITE COLLAR 13,6% 0% 0% 13,4% 20,6%

BLUE COLLAR 86,4% 100% 100% 8b,6% 79,47.

TOTAL 100,0% 100,0% 100,0%' 100,0% 100,02:

HIGH INCOME AREAS

Constantia Bishopscourt Penza nee Welgemoed Platte- Es ta te kloof

WHITE COLLAR 54,9% 62,9% 57,1% 71,2% 54,6%

BLOE COLLAR 45,1% 37,1% 42,9% 28,8% 45,4%

TOTAL 100,0% 100,0% 100,0% 100,02: 100,0%

Education

21. On the question of education Reiss continues "We have, therefore, the

following sequence: a man qualifies for occupational life by

obtaining an education; as a consequence of pursuing his occupation

be obtains income. Occupation, therefore, is the intervening

activity linking income to education". 8 Appendix 8 demonstrates

this relati.onship by showing the educational levels for selected high

income and low income suburbs.

Housing

22. The form of tenure under which people are housed is an important

indicator of material well-being. Generally in the metropolitan area

the people who "have", possess their own homes and those who "have 14

not" ] ive in public rented accommodation (economic and 6ub-economl c

units) while those inbetween, rent privately. The qual i ty of

people's physical exlstence tends to be the mirror-image of the samp

grada tions. Appendix 9 shows the same spatial patterns as the

composite lndex of lpvels of lJvlng and the Index of fn~orr.e

Apl,(·"dJx 1(1 showIng housing densftf~!: also hears rhis

out. Furthermore, the tahle below which depicts occupancy rates for

selected suburbs 8S well as their corresponding hOUSing densities

once. again reinforces the view that tenure and well-being are closely

related. See Appendix 11 for spatial variations in persons per

habitable room.

TARLE 6 HOUSING DENSITIES AND ROOM OCCUPANCY RATES

LOW INCOME AREAS

Suburb Average persons Housing units per room per hectare

Factreton 2,19 9,26 Hanover Park 2,12 19,14 Lavender Iii 1 I 2,08 43,93 Manenberg 2,19 23,81 parkwood 2,20 17 ,97 Nyanga 2,62 6,77 Kalksteenfontein 2,57 20,95 Bonteheuwel 2,03 15,56

HIGH INCOME AREAS

Suburb Average persons Housing units per room per hectare

Fresnaye 0,47 9,26 ~Ii lnerton 0,56 0,36 Mead owridge 0,63 6,30 Bishopscourt 0,44 1,96 Llandudno 0,42 1,19 0,44 0,14 0,66 2,53 Pinelands 0,57 6,00 Welgemoed 0,55 2,64 0,60 2,76 15

23. What is important, with the above table in mind, is to realise that

overcrowding is a multi-dimensional problem, resulting from the

interaction of physical arrangement of space, noise, temperalure and

social (degree of cohesion, personality interactions etc.) factors.

It i6 characterised by adverse manifestst ions of stress. Numerous

examples from research li.terature lndicate that \o,lhen privacy

disappears, the maintenance of harmonious social relationships is

threatened. There is no opportunity to wi t hd raw from rela tionships

that have become sufficiently intense to cause confilict. It is

therefore alarming to discover that 58,9% of all Coloured households

in the region are overcrowded. (This figure was derived from a

mat rix of persons per household by the numher of rooms per house with

a desired ratio of 1,5 persons per room. See Appendix 12).

Health

24. A number of studies have indicated that high density living is

associated with many deprivations and stresses, and that both

infectious and non-infectious diseases tend to cluster together under

such conditions. In a study done in Baltimore, USA among high

density housing areas with high occupancy rates it was stated that

"Various diseases and maladies, including pysychoneurosis were

found" 9 In Cape Town itself this is manifested by the prevalence

of tuberculosis which "affects mainly the underprivileged and, •••••

will remain a problem as long as sections of the Cape Town population

remain exposed to the effects of malnutrition, overcrowding

etc." Furthermore, "overcrowding especially in cold weather" which

"is unavoidable for large sections of the community"lO is also seen

to have a high correlation with cerebrospinal fever. 16

25. Given the low scores on the index of Income. inequality, lilt· !.11'.!.

dependency ratios, overcrowding etc it is nol su~prl.6illg thaI lIIosl of

the local authority health clinics (preventive medicine) are si[uatpd

in the pubJ i c rented "ccon1lnoda tl.on a reas must sure] y be one of the

strongest slate",(,nls "hollt reJativ(> deprivatIon.

Crime

26. Certain types of crimes, particularly crimes of violence, are

generally considered to correlate highly with areas exhibiting marked

depr iva tion. II is therefore interesting to note that the areas

identified by the composite index as being highly deprived also tend

to have the highest vIolent crime ratios in the . The

table below ilJuslrates the spatial affinity of violent crimes and

deprivation in se]('cted suburbs. These suburbs were identified as

the most criminogenic in a study conducted in the months of January, 11 June and December 1979.

TABLE 7 VIOLENT CRHlE RATES AND THE COMPOSITE INDEX BY SELECTED SUBURBS

Suburb Crimes per 100 000 Compnsite Index for 3 month period

Guguletu 397 46,90 Retreat 280 45,95 Bonteheuwel 721 53,34 Manenberg 715 52,94 353 31,24 371 47,97 Langa 039 44,67 Athlone 160 39,39 Hanover Park 387 50,37 Nyanga 513 43,47 Philippi 175 32,00 17

CONCLUSION

27. This study has demonstrated spatially the large "gaps· that exist in

levels of living in the metropolitan ar~a. Undoubtedly there are

large areas, some of which are contigllOUti \,oJhile uthers are almost

islands, that are suffering condl t Ions of extreme deprivation. FroID

a developDl~ntal point of view these structural obstacles need to be

addressed if there is to be stability and growth in the region.

28. There is a need for work and the acquisition of skills for productive

economic performance. It is essential that access to infrastructural

facilities be provided. Research has shown that the constraints imposed by jobs, school, health facilities and recreation facilities

affect productivity, conjugal relationships and amount of leisure

time etc. The growing specialization of our economy has. increased

the significance of education as a prerequisite of employment and as

a determinant of occupational status.

29. Opportunities for social participation, interaction, community cohesion and communication are needed. The provision of adequate and

sufficient housing is of vital importance. Based on the 1980 Census

an estimated minimum backlog of 46 000 houses was determined. Along

with the provision of housing there should be security of tenure.

30. Finalli, it can be said with reasonable certainty, that if a

conscious effort is not made to raise the levels of living of the

people within the study area that conditions will worsen. It is

time to acknowledge that the depriva tIon of one is inextricably bound

up with the affluence of another. APPENDICES 18

APPENDIX I : COMPOSITE INlJEX

HIGH SCORES LOW SCORES

SUBURB SCORE SUBURB SCORE

Factreton 50,94 Akasia Park 1,65 Schotse Kloof 50,61 Bantry Bay 3,36 Sa It Rl ver 46,71 Fr~snaye 2,b2 Hanover Park 50,57 3,92 Il,' ze ndal 50,43 Frere Estate 4,59 lIeideveld 41,24 Ilat ton £s tal e 3,57 Lavender Hill 61,13 Kingfisher Estate 0,84 Manenberg 52,94 0,71 Parkwood 53,16 Newlands 2,25 Retreat 45,95 4,05 Hangberg 53,20 Bi shops Cou rt 1,05 Guguletu 46,90 Llandudno 1,19 Langa 44,67 lIout Bay 3,29 Nyanga 43,47 Richmond Estate 3,23 Ocean View 46, 4~ Bellville Central 3,90 Scottsdene 49,86 Chrismar 2,86 Kalksteenfontein 63,34 Dunrobin 1,32 Valhalla Park 59,17 Thalman 1,50 Eisies River 48,82 lielgelDoed 2,30 Uitsig 47,02 Eversdale 1,52 Matroosfontein 52,50 Kenridge 2,42 Bishop Lavis 47,97 Belmont Park 3,98 Mimosa Park 44,05 Peerless Park North 3,23 Newtown 56,93 Clam lIall 1,79 Kraaifontein Rural 52,38 Panorama 1,79 Bonteheuwel 59,07 Plat:tekloof 0,00 Eden Park 1,60 Durbanville 2,04 '.

I!I 65.86 - 100.00 • 33.33 - 65.86

• 16.37 - 33.33 § 8.51 - 16.37 Illl 0.00 - 8.51 00.00 - 0.00 INDEX PRODUCED BY REATER CAPE TOWN CALFORH LOCAL AREA BASE seAL N.W.RILEY MS 1980 DIRECTOR HOUSEHOLD HEADS 1 1836000 CEN sus ECHH'~:~v7~~~GEt1EH EARNING < R3000 Appendix 2A 18162.02 - 100.00 III 33.52 - 62·02 m18.65 - 33.52 § 7.34 - 18.65 OIl 0.00 - 7~34 00.00 - 0.00 INDEX REATER CAPE TOWN LOCAL AREA BASE seAL ~ ;; .., 0 N.W.RILEY o ~ MS 1980 DIRECTOR HOUSEHOLDS WITH 11836000 ~. ~~ ~ CENS US TECHHI;~~v~~~:CEH£M NO CARS .. -

Appendix 28 '.

£1'48.43 - 100.00

• 19.26 - 48.43 ffiI 3. 66 - I 9. 26 § 0.00 - 3.66 IJ] O. 00 - O. 00 00.00 - 0.00 INDEX PRODUCED BY REATER CAPE TOWN CAL FORM lOCAL AREA BASE seAL N.W.RILEY 1980 DIRECTOR OCCUPANCY RATES 1 1836000 MS CENSUS rEcHNI~:~v~~~~GEMfN GREATER THAN 1.5 Appendix 2C (31 22.78 - 100.00 • 5.95 - 22.78 l1li o. 00 - 5. 95 § 0.00 : 0.00 lID o. 00 - o. 00 o 0.00 - 0.00 INDEX CAPE TOWN AREA BASE seAL MS 1980 .'0EC,.0 1. 8J6000 CENSUS ECHMI~~~y7c::GEt'EN HARED ACCOMMODATION

Appendix 2D g 13.77 - 71.40 .0.00 - 13.77 IIIIIIII 0.00 - 0.00 ~ 0.00 - 0.00 ITO 0.00 - 0.00 00.00 - 0.00 INDEX PRODUCED J.G.BRAND BY ITY ENGINEER REATER CAPE· TOWN CAL FORM LOCAL AREA BASE seAL N.W.RILEY MS 1980 DIRECTOR I NG L. E MOT HER S WIT H" 836000 CENS US TECHNI;;~V~~~:GENEN ORE THAN 3 CHILDREN Appendix 2E ~ 16.68 - 100.00

.2.58 - 16.68

• 0.00 - 2.58 § 0.00 - 0.00 []]] 0.00 - 0.00

00.00 - 0.00

INDEX CAPE TOWN AREA BASE seAL N.W.RILEY MS 11836000 1980 DIRECTOR UNEMPLOYED CENS US ECHM 1~~~¥ ~~GEHE"

Appendix 2F R"zrm

E! 22·S3 - 100.00 • 7.7i - 22.53 ffiI 2.02 - 7. 71 ~ 0.00 - 2.02 IIIl 0.00 - 0.00 00.00 - 0.00 INDEX REATER CAPE TOWN LOCAL AREA BASE seAL ... ~ N.II.RILEY ...o 0• MS 1980 OIRECTOR EDUCATION OF " 8J60tO ~..... w 'i i CENS US ECHN I ~~~v ~~~GEt1EH WORf

Appendix 2G 19

APPENDIX 3A

HOUSEHOLD HEADS EARNING LESS THAN R3 000 PER ANNUH

SUBURB SCORE SUBURB SCORE

Zonnebloem 8~,70 Akasia Park 3,84 Bridgetown 73,80 Bantry Bay 6,12 Hanover Park 78,75 fresnaye 8,69 lI"zenda] 73,58 Camps /lay 9,73 Kew Town 83,90 Hi Inert on 9,30 Klipfontein Mission 81,81 Kenilworth 3,~6 Lavender Hill 80,48 Hcadowridge 2,50 Manenberg 82,00 Ne..,lands 6,62 Parkwood 77 ,35 Rondebosch 9,~5 Silvertown 76,36 Constantia 9,43 Hangberg 90,62 Welgemoed 6,25 Guguletu 90,80 Durbanville 5,55 Langa 90,58 Kenridge 2,81 NyangB 86,72 Glen Lily 5,26 Steenberg 90,90 Panorama 1,79 Ocean View 74,39 Parow North 2,09 Kalksteenfontein 97,72 Plat tekl oof 1,60 Valhalla Park 100,00 Matroosfontein 72,22 Bishop Lavis 75,86 Nooitgedacht 77,14 Newtown 93,75 Bonteheuwel 92,85 Kleinvlei 75,43 Scottsdene 83,33 100,00

, ;1 , I 2U APPENDIX 3B

HOUSEHOLD HEADS WITH NO CARS

SUBURB SCORE SUBURB SCORE

FRcreton 74,71 Bridgetown 76,18 HAnover Park 80,71 Fresnaye 5,78 H('ideveld 71,77 Camps Bay 9,73 Kew Town 1ll,59 5,81 Lavender Hill 84,55 Table View 5,94 Manenberg 86,UO Kingfisher Est~te 5,88 PRrkwood 77 ,35 Newlands 8,60 Si lvertown 85,84 Bishopscourt 0,00 Hangberg 84,37 Kirstenbosch 0,00 Cuguletu 84,68 Constantia 6,91 Langa 85,87 Pinelands 9,64 Nyanga 78,75 Bellville Central 8,12 Steenberg 90,90 Plattekloof 0,00 Ocean View 82,91 Bonteheuwel 79,68 Ka1ksteenfontein 90,90 Valhalla Park 84,61 Elsies River 77 ,16 Uitsig 86,03 The Range 73,33 Matroosfontein 72,21 Mimosa Park 100,00 Newtown 87,50 Kraaifontein Rural 100,00 Scottsdene 85,55 21

APPENDIX 3C

OCCUPANCY RATES

HIGH LOW

SUBURB SCORE SUBURB SCORE

Facreton 75,86 Bantry Bay 0,00 Athlone 54,23 Frefinaye 0,00 Hanover Park 76,13 Green Point 2,58 He1develd 58,89 Camps Bay 5,30 Lavender Hill 76,41 1,60 Manenberg 74,28 4,23 Parkwood 74,52 Gardens 1,12 Retreat 66,65 Milnerton 1,16 Silvertown 50,90 Table View 0,98 Hangberg 75,00 Claremont 3,95 Guguletu 76,58 Kenilworth 2,B8 Langa 57,64 Meadowridge 2,50 Nyanga 80,53 RondeboRch 0,00 Ocean View 57,31 Rosebank 0,00 Mfuleni 50,00 Constantia 4,40 Kalksteenfontein 72,71 Bishopscourt 0,00 0,00 El~tes River 65,50 Llandudno Cravenby Estate 64,28 Hout Bay 0,00 Ui tsig 67,69 Simon's Town 1,29 Matroosfontein 68,50 1,14 Bi shop Lavi s 63,35 Edgemead 0,00 Bellville .South 60,B2 Pine lands 1,12 Newtown 68,75 Bellville Central 2,32 Kraaifontein Rural 100,00 Bell ville West 0,00 Ravensmead 67,90 Boston 0,00 Bonteheuwel 78,56 Chantecler 0,00 Sc ot tsdene 75,55 Welgemoed 0,00 Durbanville 1,37 BelvedE'.re 0,00 Panorama 0,00 Plattekloof 0,00 Welgelegen 0,00 22 APPENDIX 3D 1 SHARED ACCOMMODATlON

HIGH LOW'"

SUBURB SCORE SUBURB SCORE

Facreton 89,64 Akasia 0,00 KensIngton 75,48 Bantry Bay 0,00 Schoonekloof Ill,81 CI if ton 0,00 Salt River 33,33 0,00 WaIDler Estate 42,84 Fresnaye 0,00 Woodstock 50,74 Camps Bay 0,00 Athlone 50,82 0,00 Athlone West 94,71 0,00 Belgravia Estate 32,28 Bridgetown 35,70 Gleemoor 63,63 Hanover Park 30,39

Lavender Hill 34 t 14 Lincoln EstRte 60,00 Pen1yn Es tate 30,76 Primrose Park 49,98 Retreat 41,22 She ,,",ood Pa rk 46,86 Silvertown 65,43 Strandfontein 72,00 Wynberg 36,18 Ocean View 62,19 Bonteheuwel 44,52 Kalksteenfontein 81,81 Valhalla Park 51,90 Elsies River 30,51 MatroosfoTltein 94,44 Nooitgedacht 51,42 Newtown 93,75 Sarepta 54,04 Scottsdene 33,33

* No shared accommodation in most affluent areas 23

APPENDIX 3E SINGLE MOTHERS WITH MORE THAN 3 CHILDREN

HIGH LOW* SCORE SUBURB SCORE SUBURB

12,79 AkaRia 0,00 Schotse Kloof 0,00 Sc hoonekl oof 45.~5 Bantry Bay 42,34 Clifton 0,00 Athlone 0,00 Belgravia Estate 30,75 Th ree Anchor Bay 0,00 Bridgetown 23,79 Fresnaye 0,00 Gleemoor 45,45 Green Point 18;85 Camps Bay 0,00 Grassy park 0,00 Greenhaven 57,65 MouUIe Point 0,00 Hanover Park 31,00 Sea Point Hazendal/Bokmakierie 56,60 18,39 Kew Town 22,95 Lan"downe 39,04 Lavender Hill 60,95 13,30 Manenberg 45,70 Montagu's Gift 23,96 Parkwood 18,85 Retreat 23,35 Sherwood Park 15,60 Silvertown 18,14 Surrey Estate 31,90 Wynberg 12,90 38,45 IIangberg 46,85 Philippi 44,10 Guguletu 5,44 20,80 Steenberg 45,45 Bonteheuwel 31,25 45,45 ,I Kalksteenfontein . \ Valhalla Park 38,45 Elsies River 43,40 E}>ping Forest 50,00 Uitsig 41 ,64 Matroosfontein 27,75 Bishop Lavis 28,00 Bellville South 20,94 Mimosa Park 62,50 Sarepta 27,75 Newtown 31,25 Scottsdene 33,29

* Most affluent areas score 0 APPENDIX 3r

ALL UNENI'LOYED

HIGH LOW

SUBURB SCORE SUBURB SCORE

F<1ctreton 26,79 Akasia 0,00 N~jtl~lld 21,33 Bt'ooklyn 0,00 Schot"e Kloo! "1 ,2(J Three Anchor Bay 0,00 Salt RIver 00,37 Camps Bay 0,00 Sa It R:lver 35,37 Mouille Po:lnt 0,00 Woodstock 26,66 Sanddrift 0,00 Bridgetown 36,12 Schoonekloof 0,00 Grassy Park 34,79 Sea Point 0,00 Hazendal/Bokmaklerle 42,70 Tamboerskloof 0,00 Heideveld 22 ,54 0,00 Lavender Hi 11 47,04 0,00 Lotus River 25,74 Blouberg Strand 0,00 Manenberg 26,00 Montagu's Gift 23,79 Mount View 43,08 Parkwood 62,29 Retreat 28,70 Sllvertown 22,24 Surrey Estate 24,50 Wynberg 27,20 lIangberg 22,20 Gugllletu 28,45 Ka Ik Bay 54,79 Bontehellwel 25,54 Epping Forest 67,45 Bishop Lavis 22 ,70 Sa repta 32,33 Scottsdene 35,04 25

APPENDIX 3G EDUCATION OF WORKERS WITH LESS THAN STD &

HIGH LOW SCORE SUBURB SCORE SUBURB Park 0,00 Factreton 38,&2 Akasia 2,50 Hazendal 27,35 Bant ry Bay 3,44 Bridgetown 3&,35 Clifton 2,70 Ileideveld 3&,75 Camps Bay 1,72 Kew Town 39,28 Oranjeztcht 0,94 Kllpfontetn Mission 33,32 Sea Point 1,50 Lavender Hill 44,34 Gardens 1,33 Manenberg 43,82 Table View 3&,31 Claremont 1,39 Parkwood 0,00 Retreat 34,07 KirstenboBch 0,00 Welcome Estate 33,32 Meadowridge 2,45 Hangberg 34,&5 Newlands 1,47 Langa 45,23 Rondebosch 0,00 Nyanga 39,75 Rosebank 2,84 Steenberg 47,35 Bishopscourt 0,00 Ocean View 42,25 LI andudno 0,00 Bonteheuwel 42,79 Hout Bay Kalksteenfontein 54,76 Simon's Town 1,14 0,00 Valhalla Park 52,71 Marina da Gama 0,00 Elsies River 37,35 St .James 0,54 Ul.tsig 34,45 Fish Hoek 1,52 Matroosfontein 32,37 Bell ville Central 0,00 Bishop Lavis 38,20 Boston 0,00 Nooitgedacht &0,00 Chantecler 0,00 Sarepta 32,34 Dunrobin 1,79 Kraaifontein Rural &&,65 Durbanville Ravensmead 35,39 Eversdale 0,00 Panorama 1,79 Plattekloof 0,00 iii 12500.00 - 30000.00 611 9999.99 - 12499.90 lID 7500.00 - 9999.90 ~ 5000.00 - 7499.90 [OJ 2500.00 - 4999.90 00.00 - 2499.90 RANDS PER ANNUM PRODUCED REATER CAPE TOWN BY LOCAL AREA BASE CALFORM SCALE <~'I; iT MS 1980 NO',~('C~O~LfY HEAD OF HOUSEHOLD 1:836000 .,. w CENSUS lrcHIH~:~v7~~~r,r.Mr.N 1 N COME '} ~ ______. ___ -"--'--'-=-~:.:::._ ____~_.___L _ ___L

Appendix 4A I, i ~=-I '-" 1,,;

I:l i 2500.00 - 30000.00 1I!l9999.99 - 12499.90

I~ill 7500. 00 ~ 9999.90 ~ ~OOO.OO - 7499.90

III] 2500. 00 - 4999.90 00.00 - 2499.90 PROD:-U-C-CE:::-:D.----:---c:c:---:--.:::--=-=--=--=-=--C-,---A-P~E,--tA~~i~!-lA~IWM JE CALnRM AREA BASE SCALE . T MS N.II.RILEY ~"O:- ~z: 1980 O!REefOR PER SON AL INC 0 ~1E ,,636000 '''l ~ CEN SUS TECH~I;~~v7~~~CrMi:H .. - LO.::..:c:_::..=.t_-=:.:.::..:--'------. --~.--~- -- Appendix 4B 2&

APPENDIX 5

FORMULA FOR TIlE INDEX OF THE INEQUALITY OF INCOME

Houaehold Head Income

It is proposed lo me~sure the degree of income inequality in the 01 Economic RegIon and Kul Is River. The method of measuring the income distribution by a co-efflcjent is to compare the local observed percentage dIslrlbuUon against the degree of deviation from the median income.

The calculation is b~sed on a methodology devised by P M Smith and R J Gray. (Social Indicators for Tampa, Florida, Urban Studies Bureau, University of Florida, 1972).

The index is calculated in the following way:

1. Where xy is the percentage in a given income category for local area j ..

2. Where Wi is the difference between the mid-point value of an income category and that of the median income (Median income calculated for household heads for the Metro region is R4 255,18).

3. The cut-off point for the income dIstribution of household heads is +R15 000, however an upper interval has been calculated as RI5 000 to R29 850. The Internal average of the upper income group is R22 424,50.

Example:

The median income of household heads (4255,18) subtracted from the mid-point of a particular income category (example 500-999) 750, multiplied by the percentage of occurrences in that particular income category. Summed overall categories in each local area. 27

APPENDIX 6

INEQUALITY INDEX

Low - Index High + Index

Bridgetown - 4054,4 Akasfa Park + 8653,2 Ha nover Pa rk - 3996,7 Fresnaye + 7376,1 Ileldeveld - 3791,7 Camps Bay + 6256,0 Kew Town - 4255,0 MUnerton + 4937,9 Lavender Hill - 4370,3 Estate + 5H2,l LotlI" River - 2939,6 Kenilworth + 4178,7 Manenberg - 4283,0 Mead owrJ dge + 7535,1 Pa rkwood - 3693,2 Newlands + 8184,9 Retreat - 3709,6 Constantia + 9387,5 Hangberg - 4409,6 Bishopscourt +10041,4 Guguletu - 4907,8 LIandudno + 7309,9 Lango - 4786,0 St James + 6552,9 Nyanga - 4705,9 Pine lands + 5178,4 Ocean View -...3786,5 Belgravia + 5774,6 Bonteheuwel - 4088,3 Chantecler + 8143,3 Kalksteenfontein - 4816,2 Eversdale + 7344,1 Valhalla Park - 4747,4 Welgemoed +11999,7 Elsies River - 3911,5 Kenridge + 9603,5 Uitsig - 4008,6 Belvedere +16336,6 Range - 4517,8 Panorama + 8956,9 Bishop Lavis - 4221,8 Plattekloof +11695,1 Ravensmead - 3412,1 Scottsdene - 4070,0 Mfuleni - 4629,4 APPENDIX 7

HEAD OF HOUSEHOLD INCOME BY NUMBER OF PERSONS PER HOUSEHOLD - COLOURED (5% SAMPLE - 01 REGION)

PERSONS PER HOUSEHOLD HEAD OF HOUSEHOLD INCOME

None 0- 500- 1000- 1600- 2000- 2500- 3000- 3500- 4000- 4500- 5000- 6000- 7000- 8000- 15000 TOTAL 499 999 1599 1999 2499 2999 3499 3999 4499 4999 5999 6999 7999 14999 +

6 5 58 25 8 6 3 5 8 a ° 135 % 0,09 0,07 0,91 0,39 0,12 0,09 0,04 0,01 0,06 0,07 0,06 0,12 0,01 0,00 0,01 0,00 2,12 2 48 11 136 94 58 39 39 27 21 15 1~ 29 13 553 % 0,75 0,17 2,14 1,48 0,91 0,61 0,61 0,42 ~,33 0,23 0,22 0,45 0,11 0,03 0,20 °0,00 8,72 3 58 12 110 95 67 106 51 64 54 42 36 30 31 21 23 802 % 0,93 0,18 1,73 1,49 1,05 1,67 0,80 1,00 0,85 0,66 0,56 O,~7 O,~8 0,33 0,36 0,01 12,64

71 14 96 86 79 '[109 80 85 82 72 46 63 53 27 40 3 1006 % I,ll 0,22 1,51 1,35 1,24, 1,71 1,26 1,34 1,29 1,13 0,72 0,99 0,83 O,~2 0,63 0,04 15,86

5 75 12 100 119 86 107 85 73 74 61 H 57 53 25 45 1023 % 1,18 0,18 1,57 1,87 1,35 1,68 1,34 1,15 1,16 0,96 0,74 0,89 0,83 0,39 0,70 0,06 16,13

6 58 12 78 108 80 110 74 66 62 40 31 52 34 15 34 3 857 % 0,91 0,18 1,23 1,70 1,26 1,73 1,16 1,04 0,97 0,63 0,48 0,82 0,53 0,23 0,53 0,04 13 ,51 84 14 112 112 77 127 84 59 49 38 29 29 34 14 27 ° 889 % 1,32 0,22 1,76 1,76 1,21 2,00 1,32 0,93 0,77 0,59 0,45 0,45 0,53 0,22 0,42 0,00 14,02 8 35 40 H 29 58 25 18 20 17 3 9 ° 361 % 0,55 0,11 0,63 0,69 0,45 0,91 0,39 0,28 0,31 0,26 0,11 0,04 0,14 0,00 5,69 9 25 3 22 23 18 34 26 15 10 16 8 12 6 2 ° 214 % 0,39 0,04 0,34 0,36 0,28 0,53 0,41 0,23 0,15 0,09 0,12 0,18 0,09 0,03 0,06 0,00 3,37

10 18 17 27 30 31 13 8 10 2 179 % 0,28 0,06 0,26 0,42 0,47 0,48 0,20 0,11 0,12 0,15 0,06 0,11 0,01 °0,00 0,03 °0,00 2,82 11 17 13 12 16 13 14 6 5 3 2 2 109 % 0,26 °0,00 0,20 0,18 0,25 0,20 0,22 0,09 0,06 0,07 0,01 0,04 0,01 0,03 0,03 °0,00 1,71 12+ 23 8 19 44 22 38 12 8 8 6 7 3 2 212 % 0,36 0,12 0,29 0,69 0,34 0,59 0,18 0,12 0,12 0,09 0,11 0,11 0,04 0,03 0,01 0,06 J ,3 ~ TOTAL % 519 102 801 789 570 778 506 439 397 318 247 314 231 113 201 15 6340 8,18 1,60 12,63 12,44 8,99 12,27 7,98 6,92 6,26 5,01 3,89 4,95 3,64 1,78 3,17 0,23 100,00 29

APPENDIX 8

EDUCATION LEVELS FOR SELECTED HIGH AND LOW INCOME SUBURBS (PERCENTAGE)

HIGH INCOME AREAS

Fres- Camps New- Cons tan- Bishops- Llan- Evers- Welge- Ken- Pano- Platte- naye Bay lands tia court dudno dale moed ridge rams k.1oof

Sub A, B, Std 1 4,4 6,7 5,3 9,7 2,7 13,4 5,5 8,7 16,4 Std 2 2,9 1,5 2,0 4,5 8,3 3,7' 6,4 ~,5 9,6 11,0 Std 3 3,9 2,6 2,2 3,1 3,7 4,6 3,1 1,4 Std 2,4 2,1 3,5 5,2 1,4 7,4 3,7 2,6 2,7 Std 5 6,3 5,3 3,3 6,1 6,7 8,3 1,8 3,7 2,6 2,7 11,0 Std 6 5,8 7,0 5,3 5,0 10,8 3,7 4,6 6,1 2,7 1,4 5,6 Std 7 7,8 5,7 3,3 3,8 1,4 4,2 1 t 4 3,7 4,8 Std 8 11,2 13,2 11 ,3 12,1 9,4 16,7 14,3 15,6 7,9 9,6 5,6 Std 9 9,3 3,5 4,7 4,5 2,7 8,3 2,8 2,8 6,1 4,1 5,6 Std 10 26,3 32,0 25,7 24,2 20,3 25,0 23,0 16,5 30,6 17,8 39,0 Bachelors Degree or equilavent 4,9 3,8 ll,8 6,0 17,6 12,5 2,8 5,5 8,7 5,6 5,6 Masters 0,5 0,6 1,1 0,2 0,4 2,7 0,9 Doctorate 0,5 0,6 a,s Std 10 + Diploma 10,8" 13,0 15,8 12,3 18,9 12,5 14,3 17,4 9,6 13,7 Std 8 + Std 9 + Diploma 3,4 1,5 0,3 1,5 0,8 5,4 4,2 2,3 0,9 Std 7· or lower + Di ploma 0,5 1,4 Diploma + Degree ll,O Bachelor 1,5 1,2 1,5 1,6 2,7 4,6 7,3 3,9 4,1 Diploma + Masters Diploma + Doctorate 0,4 Unknown 0,9 0,7 0,2 6,8 5,6 100,0 100,0 TOTAL 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0

r 30

APPENDIX 8 (Contd)

EDUCATION LEVELS FOR SELECTED RIGH AND LOW INCOME SUBURBS (PERCENTAGE)

LOW INCOME AREAS

Han- Kew Laven- Manen- Park- Hang- Gugu- Ocean Kalk- Val- Elsies B:lshop over Town der berg wood berg letu View steen- halla River Lav:ls Park Hill fontetn Park

Sub A,B, Std 1 15,3 13,4 19,7 17,0 13 ,0 16,4 15,0 18,9 17,6 27,1 18,0 16,0 Std 2 8t~ 6,4 8,7 10,4 12,6 13,7 7,9 8,4 12, I 12,9 6,8 5,8 Std 3 10,5 7,9 10,8 9,8 9,4 8,9 9,5 8,4 8,0 5,3 7,7 7 , ~ Std 13,9 14,6 12,7 14,1 12,6 17 ,I 10,8 12,8 15, I 12,2 12,0 11,2 Std 5 16,5 20,1 17,9 17,2 17, I 17,8 12,4 16,5 17.6 19,1 13,8 17,6 Std 6 18,8 19,8 14,0 17,5 18,1 15,1 17,8 13 ,3 10,1 13,5 17,5 17 , ~ Std 7 6,4 9,5 9,4 5,2 6,8 6,8 9,3 10,2 9,5 3,6 7,0 8,7 Std 8 5,8 4,4 4,4 4,1 5,8 2,1 9,4 5,8 5,0 2,0 4,0 6,7 Std 9 1,1 1,5 0,6 1,2 0,6 3,2 0,3 0,7 1,8 2,6 Std 10 1,5 1,2 1,1 1,1 1,3 3,2 1,2 1,3 2,3 1,9 Bachelors Degree or equilavent 0,2 0,6 0,0 0,0 0,3 0,0 Masters degree Doctorate Std '10 + Diploma 0,3 0,1 0,4 0,6 Std 8 + Std 9 + Diploma 0,5 0,6 0,2 0,3 0,6 0,7 0,4 1,2 0,4 Std 7 or lower + Diploma 0,1 0,6 0,1 Diploma + Degree Bachelor Diploma + Masters Diploma + Doctorate Unknown 0,8 0,6 0,5 2,0 1,7 1,4 0,8 1,8 5,0 2,3 7,7 4,7

TOTAL 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 E;) 75.00 - 100.00 .60.00 - 74.90

1IIIlill45.00 - 59.90 ~ 30.00 - 44.90 ITlJ 15.00 - 29.90 D 0.00 - 14.90 PERCENT PRODUCED BY REATER CAPE TOWN LOCAL AREA BASE seAL CALFDRM <- ~ ... 0 N.II.RILEY I: 836000 o z MS 1980 DIRECTOR TYPE OF TENURE ~. '1-1. ~ CENSUS TECHNT;:~v~~~~GEHEH HOME OWNERSHIP <- ~

Appendix 9A •

1ii175.00 - 100.00

•. 60.00 - 74.90

.45.00 - 59.90 ~ 30.00 - 44.90 OJ] 15.00 - 29.90 o O. 00 - 1 4 . 90 PERCENT PRODUCED BY REATER CAPE TOWN CALFDRM LOCAL AREA BASE seAL N.W.RILEY 1980 DIRECTOR TYPE OF TENURE 1:836000 MS CENS US' ECHH I ~:~v ~~=~GEMEH PUBLIC RENTED Appendix 98 III 75,00 - 100,00 11160,00 - 74,90

IIIIIIII45,00 - 59,90 § 30,00 - 44,90 rrn 15,00 - 29,90 o 0,00 - 1 4 . 90 PERCENT CAPE TOWN LOCAL AREA BASE SCALE ~~ N.W.RILEY I : 836000 \ ~ T MS 1980 DIREcrOR TYPE OF TENURE 'i CEN SUS ECtfNI~~~v~~GO'EH PRIVATE RENTED .. -~

Appendix 9C IDI~ ,=- II

IlD 14.82 - 58.62 .9.25 - 14.82 1ID11115.77 - 9.25 §j2.75 - 5.77 [IT] 0.67 - 2.75 00.00 - 0.67 DWELLING UNITS PER HECTARE PRODUCED BY REATER CAPE TOWN CAL FORM LOCAL AREA BASE N.W.RILEY seAL s~~ ~ 1980 DIRECTOR ~ ~ MS '-836000 "'-: ~ CENSUS 'ECHNT~:~v~~:~GEt1[N HOUSING DENSITY 'i ~ . ~ Appendix 10 13 2.49 - 4.99 .2.00 - 2.49 III 1.50 - 1.99 §:l1.00- 1.49

[]] 0.50 - 0.99 D 0.00 - 0.49 PERSONS PER HABlTABLE ROOM PRODUCED BY CAPE TOWN CALFORN AREA BASE . N.W.RlLEY MS 1980 DIRECTOR CENS US J ECHN 1 ;:~V ~~;:GEt1EH OCCUPANCY RATES

Appendix 11 3J

APPENDIX 12

NUMBER OF HAlllTABLE ROOMS PER DWELLING BY NUMBER OF PERSONS PER I!OUSEIWUJ - COUJlf'f.IJS (METROPOLITAN AREA - 5% SAMPLE)

PERSONS 2 3 5 6 8 9 J 0+ . T01 AI. PER ROOM ROOMS ROOMS ROOMS ROOMS ROOMS ROOMS ROOMS ROOMS ROOMS 1l0USE- HOLD

17 62 I b o l_~,251. 0,92% 0,23% 0,01% °0,00% °0,00% °0,007., °0,00% O,OO:t 2 86 168 206 99 17 6 583 1,27% ° 1 2,50% 3,06% 1,47% 0,25% 0,08% 0,00% 0,01% °0,00% °0,00% 8,67% 3 87 223 319 168 45 8 6 ° o 856 1,29% 3,31% 4,74% 0,66% 0,11% 0,08% 0,00% 0,00% °0,00% 0,00% 12,73% 77 207 311 73 10 3 ° ° 1074 1,14% 3,08% 4,62% 1,08% 0,14% 0,04% 0,01% 0,00% 0,00% 15,98%

5 46 220 307 64 15 6 2 1076 0,68% 3,27% 4,56% 0,95% 0,22% 0,08% 0,02% °0,00% °0,00% 16,01% 6 30 132 429 255 44 16 3 ° ° 910 0,44% 1,96% 6,38% 3,79% 0,65% 0,23% 0,04% 0,00% 0,00% 0,01% 13 ,54% 7 25 108 447 281 48 21 10 3 ° ° 943 0,37% 1,60% 6,65% 4,18% 0,71% 0,31% 0,14% 0,04% 0,00% 0,00% 14,03%

8 9 177 126 13 377 0,13% 0,65% 2,63% 1,87% 0,19% °0,00% °0,00% °0,00% 5,61% 9 9 22 105 72 13 230 0,13% 0,32% 1,56% 1,07% 0,19% °0,00% °0,00% °0,00% 3,42% 10 3 19 88 72 10 2 195 0,04% 0,28% 1,30% 1,07% 0,14% 0,02% °0,00% 0,01% °0,00% °0,00% 2,90% 11 2 53 40 13 118 0,02% 0,10% 0,78% 0,59% 1 2 0 ° ° 0,19% 0,01% 0,02% 0,00% 0,00% 0,00% 1,75% 12+ 2 20 80 88 14 217 7 6 0,02% 0,29% 1,19% 1,30% 0,20% 0,10% 0,08% °0,00% °0,00% °0,00% 3,22% TOTAL 393 1232 2756 1835 355 100 39 8 ° 6719 5,84% 18,33 41,01 27,31 5,28% 1,48% 0,58% 0,11% 0,00% 0,01% 100,00 % % % % 32

REFERENCES

1. Social Science Research Council (1968) "Research on Poverty" p. 5, Heinemann Educational Books Ltd

2. TOImsend, P (1970) "The Concept of Poverty", p.2l, Heinemann Educational Books Ltd

3. Smith, D M (1973) "The Geography of Social Well-Being in the United States", p.136, McGraw-Hill

4. Drewnowski, J EScott, W (1966) "The Level of living Index" United National Research Institute for Socia 1 Development, pp17-22, Report No.4

5. Reilly. EM: Social Indicators An Introduction and Bibliography, unpublished mimeograph

6. Smith, D M (1977) "Patterns in Human Geography" pp.166-l70, Penguin Education

7. Reiss, A J et al. (1961) "Occupations and social status", p.116, The Free Press of Glencoe Inc.

8. Reiss, ibid p.116

9. Mitchell, E R (1971) "Some social implicati~ns of high density housing" pp.18-29. American Sociological Review, Vol 36

10. Medical Officer of Health, , Annual Report 1981, p.73

11. City Engineer's Department, City of Cape Town (1980) "Crime in the Council's Housing Estates" p.12.