1

The social capital of the rural migrants

in Shanghai

Danching Ruan and Gina Lai

Hong Kong Baptist University

This research was substantially supported by a grant from the Research Grants Council of

Hong Kong Special Administrative Region (HKBU 2142/03H). The support from the Research Committee (FRG/02-03/I-39) of Hong Kong Baptist University is also gratefully acknowledged.

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I. Background

1. The socialist legacy: Institutionalized rural-urban divide

2. Internal migration in China: from “still water” to 120 Million (from 1985-present)

3.Changing social landscapes in Chinese cities—locals vs. outsiders (mostly rural migrants)

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II. Method• Data from a survey conducted in the summer of 2005 i

n Shanghai.

• Three stage cluster sampling: 7 districts from 18 sub-districts; 16 wards and 43 neighborhood committees.

• Data were collected through face-to face interviews from a sample of 1835 local Shanghai residents, aging from 16 to 60, and a sample of 2817 migrants, also aging from 16 to 60 (students were excluded from both samples).

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III. Social contacts and social capital

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住所邻居 nieghbor (%)

86%

11% 3%

mostly shanghai

50/50

mostly non local

你的朋友大多是上海人还是外地人 (%)friends

94%

4% 2% all or mostly shanghai

50/50

all or mostly notshanghai

你平常接触的人大多是上海人还是外地人 (%)daily contact

92%

7% 1% all or mostly shanghai

50/50

all or mostly notshanghai

Locals

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住所邻居 (%) neighbor

40%

23%

37% mostly shanghai

50/50

mostly not shanghai

你的朋友大多是上海人还是外地人 (%)Your friends inShanghai are mostly

19%

23%58%

all or mostly shanghai

50/50

all or mostly notshanghai

你平常接触的人大多是上海人还是外地人 (%)Peopleyou meet everyday are mostly

38%

25%

37%

all or mostly shanghai

50/50

all or mostly notshanghai

Non-locals

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Non-locals Locals Occupation Occupational Prestige

.008 .1041 是否有科学研究人员 scientist 95

.0344 .1526 是否有大学教师 professor 91

.0317 .1700 是否有法律工作人员 lawyers 86

.1195 .2278 是否有工程技术人员 engineer/technician 86

.0933 .3471 是否有医生 doctor 86

.0407 .1984 是否有政府机关负责人 Government official 80

.1426 .3979 是否有中小学教师 school teacher 77

.1679 .3499 是否有企事业负责人 boss of an enterprise 71

.0702 .1635 是否有经济业务人员 persons in business field (e.g. accountant)

64

.0679 .2817 是否有行政办事人员 clerical worker 53

.1046 .3144 是否有民警 police 52

.0530 .1907 是否有护士 nurse 48

.3219 .4975 是否有司机 driver 25

.2997 .2365 是否有厨师、炊事员 cook 24

.4749 .4469 是否有产业工人 worker 20

.2105 .2289 是否有营销人员 sales people 15

.3083 .1597 是否有饭店餐馆服务员 waiter 11

.1182 .0469 是否有家庭保姆计时工 maid 6

N=2209* N=1835

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Position Generator Variables

Mean/Percentage(Locals)

Stddev Mean/Percentage(migrants)

Stddev

Range 46.5 29.89 27.29 29.67

Upper reachability

70.5935 29.02042 44.2933 32.54227

Number of occupations

4.5139 3.41323 2.6673 2.111

Percent having ties to officials

19.84 39.888 4.07 19.774

Percent having ties to bosses of enterprises

34.99 47.706 16.79 37.391

Percent having ties to people in education and culture fields

70.95 45.410 33.45

47.194

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If any fromShanghai (%)

If any from Shanghai (%)

Occupation

0.4 8.28 是否有科学研究人员 scientist

2.1 11.12 是否有大学教师 professor

2.0 13.19 是否有法律工作人员 lawyers

4.3 17.82 是否有工程技术人员 engineer/technician

5.1 28.12 是否有医生 doctor

2.9 16.78 是否有政府机关负责人 Government official

6.8 33.13 是否有中小学教师 school teacher

8.7 27.68 是否有企事业负责人 boss of an enterprise

2.5 12.70 是否有经济业务人员 persons in business field (e.g. accountant)

3.1 22.62 是否有行政办事人员 clerical worker

7.4 26.87 是否有民警 police

2.6 16.20 是否有护士 nurse

10.6 40.93 是否有司机 driver

0 18.20 是否有厨师、炊事员 cook

14.4 37.33 是否有产业工人 worker

6.7 17.55 是否有营销人员 sales people

4.4 11.01 是否有饭店餐馆服务员 waiter

1.0 2.07 是否有家庭保姆计时工 maid

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• IV. What helps?

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Summary of Regression Results Having good local friends

Range N of Occ. Upper.

Reachability

cadre boss

District (ref=Luwan)

Xuhui (17) *

Yangpu (14) * * * * *

Baoshan (31) * * * * *

Pudong (79) *

Jiading (45) *

Qingpu (27) * * * * *

Men/Age

Education (ref=primary or below)

Junior high school * * * *

Senior high school * * * *

College (non-degree) * * *

University or above

Occupation (ref=worker in commerce)

Agricultural worker

Service worker * *

Clerical worker * *

Self-employed / owner of private business

* * *

Manufacturing worker * * *

Cadre / managerial worker / professional worker / other

* *

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Summary of Regression Results (cont.)

Having good local friends

Range N of Occ.

Upper. Reachability

cadre boss

Time spent in Shanghai * * * *

First time leaving home -* -* -* -* -*

Understand SH dialect a bit -* -*

Not understand at all -* -* -* -*

Speak only a little bit of Shanghai dialect

-* -* -*

Cannot speak Shanghai Dialect -* -* -* -*

Origin (ref=Anhui)

Jiangsu .

Zhejiang * * * * *

Other provinces

Neighbors (ref= All or mostly non-locals)

* *

Daily contacts All or mostly locals

* * *

50/50 * * *

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社会网络变量 平均值 /百分比

标准差 *平均值 /百分比

* 标准差

Locals migrants

网络顶端 ( 最高声望 ) Upper reachability

70.5935 29.02042 44.2933 32.54227

网络差异 ( 职业个数 ) N of occupations

4.5139 3.41323 2.6673 2.111

与领导层纽带关系Tie to leaders

19.84 39.888 4.07 19.774

与经理层纽带关系Tie to bosses

34.99 47.706 16.79 37.391

与知识层纽带关系Tie to the people in education and culture fields

70.95 45.410 33.45

47.194

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Migrants std max min N

社会网络变量 平均值 /百分比

标准差 最大值 最小值 样本数

网络顶端 ( 最高声望 )Upper reachability

44.2933 32.54227

95 0 2209

网络差异 ( 职业个数 )N of occupations

2.6673 2.111 17 0* 2209

与领导层纽带关系Tie to leaders

4.07 19.77 1 0 2209

与经理层纽带关系Tie to bosses

16.79 37.39 1 0 2209

与知识层纽带关系Tie to the people in education and culture fields

33.4547.19

1 0 2209

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Locals std max min N

社会网络变量 平均值 /百分比

标准差

最大值

最小值

样本数

网络顶端 ( 最高声望 )Upper reachability

70.5935 29.02042

95 0 1835

网络差异 ( 职业个数 ) N of occu.

4.5139 3.41323

18 0 1835

与领导层纽带关系 Tie to leaders

19.84 39.888

1 0 1835

与经理层纽带关系 Tie to bosses

34.99 47.70 1 0 1835

与知识层纽带关系 Tie to the people in education and culture fields

70.95 45.41 1 0 1835

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社会网络变量 平均值 /百分比

标准差 *平均值 /百分比

* 标准差

Locals migrants

网络顶端 ( 最高声望 ) Upper reachability

70.5935 29.02042 44.2933 32.54227

网络差异 ( 职业个数 ) N of occupations

4.5139 3.41323 2.6673 2.111

与领导层纽带关系Tie to leaders

19.84 39.888 4.07 19.774

与经理层纽带关系Tie to bosses

34.99 47.706 16.79 37.391

与知识层纽带关系Tie to the people in education and culture fields

70.95 45.410 33.45

47.194

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Neighbors of the locals

0

20

40

60

80

100

mostly Shanghai 50/50 mostly non-Shanghai

Daily contacts

0102030405060

all shanghai mostlyshanghai

50/50 mostly notshanghai

all notshanghai

Friends

0102030405060

all shanghai mostlyshanghai

50/50 mostly notshanghai

all notshanghai

19

Neighbors of the migrants

0

10

20

30

40

50

mostly Shanghai 50/50 mostly non-Shanghai

Daily contacts

0

10

20

30

40

all shanghai mostlyshanghai

50/50 mostly notshanghai

all notshanghai

Friends

0102030405060

all shanghai mostlyshanghai

50/50 mostly notshanghai

all notshanghai

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政府给社会底层的人一些帮助是公平的 (%)government should help the poor

0102030405060

strongagree

agree neutral disagree strongdisagre

don’t know

农民和城里人子女应该享有相同的受教育机会 (%)equal educational opportunities for all children

0

20

40

60

80

strongagree

agree neutral disagree strongdisagre

don’t know

农民和城里人应该有平等的就业权利 (%)equal rights for employment

0102030405060

strongagree

agree neutral disagree strongdisagre

don’t know

21

外来人口为上海经济发展做出了巨大的贡献 (%)major contribution to the Shanghai economy

01020304050

strongagree

agree neutral disagree strongdisagre

don’t know

外来人口大量进城，给市民生活带来了方便 (%)making life more convenient

0

10

20

30

40

strongagree

agree neutral disagree strongdisagre

don’t know

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外来人口大量进城，增加了城市就业压力 (%)increase unemployment

01020304050

strongagree

agree neutral disagree strongdisagre

don’t know

外来人口大量进城，扰乱了城市的治安 (%)increase crime

01020304050

strongagree

agree neutral disagree strongdisagre

don’t know

外来人口大量进城，城市环境受到了损害 (%)damaging living environment

0.010.020.030.040.050.0

strongagree

agree neutral disagree strongdisagre

don’tknow

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Independent Variables Unstandardized Coefficients Standardized Coefficients

Sex (1=men) -.01 -.003

Age .003 .01

Education (reference=University)

Junior high -.29 -.07

Senior high -.34 -.08

College (non-degree) -.004 -.001

Neighbors (reference=all or mostly Shanghainese)* -.36 -.06

Daily contacts (reference=all or mostly Shanghainese) -.01 -.002

Friends (reference=all or mostly Shanghainese)*** 1.64 .18

Having non-Shanghainese as good friends*** .72 .11

District (reference=Luwan)

Xuhui* -.66 -.11

Yangpu .09 .02

Baoshan .49 .08

Pudong -.27 -.06

Jiading* -.69 -.09

Qingpu -.38 -.06

Constant 5.36***

R-squared .10

Adjusted R-squared .09

N 1764

Table 3 Regression of Negative Attitudes

* p<.05** p<.01

*** p<.001

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Independent Variables Unstandardized Coefficients Standardized Coefficients

Sex (1=men) .002 .001

Age* .008 .05

Education (reference=University)

Junior high .17 .05

Senior high* .36 .10

College (non-degree) .20 .04

Neighbors (reference=all or mostly Shanghainese) .05 .01

Daily contacts (reference=all or mostly Shanghainese)* -.39 -.06

Friends (reference=all or mostly Shanghainese) -.19 -.03

Having non-Shanghainese as good friends -.03 -.01

District (reference=Luwan)

Xuhui -.12 -.03

Yangpu .26 .06

Baoshan** -.54 -.12

Pudong -.32 -.09

Jiading*** -1.01 -.16

Qingpu* -.46 -.09

Constant 4.53***

R-squared .06

Adjusted R-squared .05

N 1787

Table 4 Regression of Positive Attitudes

* p<.05** p<.01*** p<.001