Communities in Roma Sampling Communities in Roma Sampling Slides for presentation to  ISNMI debate  on Methodological questions of Roma surveys, Cluj, July 13th 2008 D it S d U i Dumitru Sandu, University of Bucharest it f B h t

1

Is it good to cluster by   Roma ethnic communities in Roma sampling, in the  current Romania? •benefits •costs •alternatives What we know about community vs sparse residence of Roma as relevant for  sampling? Experience basis  to answer: p •PROROMA survey, World Bank,  National Agency for Roma (NAR), 2005 •RIB Roma Inclusion Barometer, Soros Foundation Romania (SFR), 2006 •Work attitudes survey (WA), Roma sample of  999 adult persons of 18 years old  and more Soros Foundation Romania and Gallup Organization, May 2008*. •Community Census of Migration, IOM, GOR, 2001 Structure of the presentation: •What are the Roma characteristics that gives the “sampling situation”? •RIB  sampling design and its evaluation •How many Roma live in their ethnic communities •How are Roma clustered in their ethnic communities as compared with sparse ones *The The author of the presentation as not involved in designing the sample for WA but the sampling design was exactly  author of the presentation as not involved in designing the sample for WA but the sampling design was exactly the same. The implementer of the sampling scheme was professor Mircea Comsa from Babes‐Boliay University. I  thank SFR for allowing me the use of  some data from WA data basis before publishing them.  

2

High community  inclusion

about 70% of Roma people live in  communities  that are larger than 20 hhds

High  g heterogeneity by

residential pattern,

Roma  R characteristics  that are relevant  for sampling    and interviewing and interviewing 

degree and type of Roma identification, 

huma capital

low education stock

economic capital

low income,high unemployment , poor housing

i h b High poverty by

challenges

accessibility

network capital

Low visibility by

marginal location in   localities,  poor communication  infrastructure

lower bridging vs bonding social capital

marginal location, low institutionalised marginal location low institutionalised identity,  identity high mobility 3

Profile of RIB sample, 2006

Sampling design

a three stage probability sample with stratification in the first  stage

Stages

1 locality with Roma 2. Roma communities  of A or B type (see previous slide)  within locality within locality 3. Roma self identified persons after screening within in A/B  communities or in locality

Sample volume p

1500 by design and  1387 as implemented y g p

Spread of the sample in 97 localities out of 1735 localities recorded with at least 9  Roma in 2002 census

4

Basic stratification scheme for Roma Inclusion Barometer* •A stratification  by locality size and  residential type of locality as identified in 2002 national  census and by residential pattern as derived from PROROMA survey •Stratification scheme applied for the 1735  localities having at least 9 Roma people in 2002 census

Locality type

Probable distribution of Roma by locality type, function of the results of PROROMA survey** C. without any A. well identified Roma B. ppoorlyy identified Roma communityy communities of at least Roma communities of identification in 20 hhds at least 20 hhds locality Total

Commune, under 200 Roma

3.3

3.3

6.9

13.5

commune, 201-600 Roma

9.2

3.4

8.1

20.7

communa, over 600 Roma

13.3

4.5

8.9

26.7

city,under 800 Roma

3.8

1.6

3.0

8.4

city, over 800 Roma

22.2

2.9

5.6

30.7

total

51.9

15.7

32.5

100.0

•For details see http://dumitru.sandu.googlepages.com/SelectiaesantionuluideromiFSD06b.pdf •** Dumitru Sandu, Roma Communities , Social Map, NAR‐WB, Bucharest p, , ,, July 2005, available y , also at http://www.anr.gov.ro/docs/statistici/Roma_Social_Mapping_187.pdf

5

Comparing PROROMI and RIB survey data with  Roma population data at national level 2002

Degree of urbanisation % Cultural area % 11 BC NT SV VR 12 GL IS 13 BT VS 21 AG DB PH 22 BZ BR 23 G TL IL CL 31 DJ MH OT 32 GJ VL 41 DOBR 51 AB HD 52 BV SB 53 CJ MS 54 CV HG 55 BN SJ 61 MM SM 62 AD BH 71 BANAT 80 BUCURESTI Persons pe hhd A Average age off adults d lt %women

Roma population , 2002 census

PROROMA

BIR romi (1387 persoane de peste 17 ani)

39

41

37

6.3 4.3 1.5 7.9 3.8 10.5 9.3 1.9 1.6 3.9 6.6 11.3 1.8 4.4 4.2 89 8.9 4.5 7.2 100.0 4.66

8.1 6.5 3.9 11.3 4.4 11.1 5.8 2.3 2.7 5.6 4.4 8.8 3.2 2.4 3.4 10 3 10.3 0.4 5.5 100 4.67

8.6 2.7 1.3 8.5 3.4 10.4 11.0 2.5 2.3 6.0 3.6 11.9 3.0 1.3 3.8 10 3 10.3 4.7 4.6 100.0 5.64 40 6 40.6 53.0

6

Comments on RIB sampling scheme, PROROMI and census data  1.

In principle, cluster sampling with so differentiated units as Roma communities is less indicated  as compared to  to voting areas or constituencies as sampling units. But Roma communities  are  less heterogeneous than localities , communes or cities, and, consequently better units to  cluster compared to localities cluster compared to localities.

2.

Exclusion error (zero or very low probability to include into the sample  Roma from some  territorial units) seems to be higher by using constituencies vs ethnic communities.

3.

RIB scheme from 2006, applied in the same way to WA survey from 2008, is based on a  sampling frame that is in line with self‐identification principle (national census) and probable  selfidentification principle of PROROMI enumeration. Possible exclusion errors in the census are  compensated by the benefits of PROROMA survey that is independent from the census.

4.

Due to the fact that about 70% of Roma population live in own  communities, Census  distribution and PROROMA are consistent.

5.

RIB  and WA data are highly consistent when analyzed – indirect proof of sampling design  scheme validity. h lidit

6.

PROROMI data refers not to selfidentified or heteroidentified Roma but to   “probable  selfidentified Roma”, due to the fact that at least one of the key informants in the PROROMA  survey were Roma from the reference community and the other two were city hall Roma expert  and another person from locality as agreed by the Roma community person and the city hall  representative.  7

Good to use triangulation in Roma social research, as in many other areas

1.

When working with populations like Roma ‐ that have different degrees of  ethnic self‐identification,   rather poor formal institutions identification and are highly mobile – the triangulation is the only  solution: it is good to combine information from official standard censuses community censuses or solution: it is good to combine information from official standard censuses , community censuses or  enumerations of the PROROMA type, standard surveys at individual level and anthropological  approaches.  

2.

Each of the above mentioned approaches have strong and weak points. The solution is not to refuse  some of them  by ideological criteria but to improve by informed criticism each of them and to  f h b id l i l i i b i b i f d ii i h f h d combine  their use. Transforming the limits of personal specialization in one method or another into  value judgment criteria does not help too much.

3.

Roma people in the current Romania,  and by long term tradition, live to a large degree in  p p , y g , g g communities as clusters of neighbored households. Ignoring that basic fact in sampling design  and/or in data analysis is a kind of de‐sociologyzation that could contribute to increasing the  probability of producing statistical artefacts. Survey  on Roma are conditioned by several factors related to sampling design, phrasing of the  questionnaire ethnicity professionalism and strangeness (their quality of being local or nonlocal questionnaire, ethnicity, professionalism and strangeness (their quality of being local or nonlocal  people) of the operators. All these factors should be considered when one assess a Roma survey.

4.

5.

National surveys on Roma could benefit from  expanding the efforts to build a Roma social map for  Romania. Census data could be considered as starting points . Improvements could be accomplished  by building on PROROMA experience. 8

How many Roma are living in Roma ethnic communities:  PROROMI community survey, 2005, % 100% 90% 80%

38 59

70%

67

68

60%

72

73

78

81

71

50% 38 14

27

20

16 Transilvvania

24

Mold dova

10%

16

4 13 24

15

12

9

6

13

13

17 ttotal

13

20%

Olttenia

30%

Cris.‐Maram mures

40%

sparsed

small groups (<20 hhds.)

Munttenia

Bucu uresti

Dobro ogea

B Banat

0%

Data source: PROROMA survey,  National Agency for Roma (NAR),  2005, own computations D.S.  605849  Roma reported persons  from 987 localities. Data basis is  larger than the one reported in  D.Sandu, Roma Communities  Social Map, NAR, Bucharest, 2005  due to the fact that computations   referred to a smaller number of  items that were validate items that were validate  separately. Figures for Bucharest  are rather poor estimates. Their  elimination from the total does  not change too much  the  percentages for the country. percentages for the country.

large groups (>=20 hhds.)

•About 70% of the country Roma population lived in communities larger than 19 hhds, in 2005. •The others live in small  communities (17%) or dissipated among  majority population (12%). •Muntenia and Oltenia are the regions with the largest share of Roma people living in large communities.

9

How many Roma are living in Roma ethnic communities: Roma Inclusion Barometer (RIB), 2006, % 100% non‐answers

90% 33

80% 70%

55 large  communities

60% 50% 40%

37

30% 20% 10%

small  communities

14 9 31

21

sparse  distribution

0% distribution without  distribution including  non‐answers non‐answers

The  reference question in  RIB survey of Soros Foundation Romania (SFR)   was : “What is the percentage of Roma living in your area… ?”.  Living in  large  Roma communities  is the case of persons that declare to have more  than 50% Roma neighbors.  Small communities are, by convention, those  of 25% to 49% Roma neighbors. If the person declares  of having 0 to 24%  % % g p g % Roma neighbors she or he is considered to live in an area with sparse  distribution of Roma.

•“What is the percentage  of  Roma living in  you area or zone?”  is a question  that is  relevant for the structure and  for the size  of residence community. The larger the  percentage of Roma perceived neighbors percentage, of Roma perceived neighbors ,  the larger the size of the reference  community. The figures in this diagram are  significant for  the size of the perceived  communities  or  everyday life interactions  communities. •There is a highly significant correlation  (r=0.38, p=0.001) between  the percenteg of Roma neighbors and the percentage of  perceived Roma in the locality. The finding  support the view that  the size of the  perceived Roma community is larger in  i dR it i l i localities with more Roma. •More than half of Roma people feel that  they live in large Roma communities, tha is  to say , having more than 50% Roma  neighbors neighbors. •About 15% Roma people feel that they live  in small Roma communities. •About one third of  Roma people consider   that they do not live in a Roma community  due to the fact that that their neighbors are  Roma in a low percentage.

10

“How many of your neighbors  from the street  or from  the block  where you live are Roma or Gipsy?” 100% 90% 80% 70%

55 70

60% rather all Roma

50%

about three quarters Roma

40%

about half Roma

30%

about one quarter Roma

20%

no/rather no Roma

10%

15 10

0%

SMALL  ROMA COMMUNITY

14

10

20

6 % Roma  on  the street/in the block

% Roma by community type

Data source: Work attitudes survey, Roma sample of  999 adult persons of 18 years old and more Soros Foundation Romania  and Gallup Organization, May 2008. The survey used the same sampling design as for RIB 2006.  Reading example: about 55%  of Roma people live in neighborhoods (on streets or in Blocks) where rather all neighbors are Roma. Adding to these the about 15% Roma that lives on streets or in blocks where about three quarters people are Roma one gets an estimation of about 70%  R Roma living in large communities. The estimation is largely consistent with the ones derived from RIB 2006 and PROROMI  li i i l iti Th ti ti i l l i t t ith th d i df RIB 2006 d PROROMI 2005. 11

Education structure by perceived size of  Roma communities 100% 90%

23

17

14

12

higher

80% 25 70% 37 60%

37

gymnasium

34

50%

27

40% 30%

primary  27

27

30

20% 10%

35 17

19

19

sparse distribution

small communities

large communities

0% non‐answer

illiterate

Data source:  RIB – SFR, 2007, own  computations, DS

•Perceived large  Roma communities ,that are  the main residential environment for Roma people, are  constituted mainly by very low educated people. • It is very likely that the large share of people that did not answer the question on  the percentage of  Roma in the neighborhood do live also in very large Roma communities. In fact they have a very similar  education structure as  people that declare of  having lots of Roma neighbors. •If the previous hypothesis is true one can conclude that RIB data support the PROROMI data that indicate  a proportion of about 70% Roma people living in large  communities (of more than 20 hhds) •The pattern of living  in a sparse distribution is specific for  more educated Roma.  12

Identity profiles by perceived Roma community type, %

sparse  distribution "What is your ethnicity/nationality"

Mother tongue

small  large  unspeci communities communities fied Total

Roma

69

64

64

59

63

Gipsy 

31

36

36

41

37

Romanian

57

51

49

38

47

Romani

39

47

43

59

48

Data source:RIB Data source:RIB – SFR, 2007, own computations, DS. Reading example: 69% of the Roma living out of  SFR, 2007, own computations, DS. Reading example: 69% of the Roma living out of Roma communities define themselves as  Roma, not as Gipsy.

•Roma people in sparse residential pattern, as compared to Roma in small or large communities,   d fi th define themselves in a lower identity way,  more as l i l id tit •Roma vs Gypsy •Having Romanian as mother  tongue, vs Romani

13

A much lower network capital for Roma as compared to the values on a  national representative sample RIB 2006 national representative sample,  RIB , 2006

Having useful connections in business in justice to get a credit to get a job abroad at police at co nt center at county center for health problems at city hall

%national sample 14 17 12 17

%Roma  %Roma sample 3 4 3 5

%national sample/ %Roma sample 4.7 4.5 3.7 3.2

23 21 7 36 22

9 8 3 15 13

2.6 2.6 26 2.6 2.4 1.7

Reading example: only 3% Roma have useful connections to get a job as compared  Reading example: only 3% Roma have useful connections to get a job as compared with 17%, the corresponding figure for the national sample.  It is especially in economic and law area that Roma have a lower network capital as  compared to majority population.

14

Communities in Roma Sampling

thank SFR for allowing me the use of some data from WA data basis before ..... 3. 26 at county center. 7. 3. 2.6 for health problems. 36. 15. 2.4 at city hall. 22. 13.

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