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Strong and weak ties as predictors of occupational position Strong and weak ties as predictors of occupational position

Strong and weak ties as predictors of occupational position - PowerPoint Presentation

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Strong and weak ties as predictors of occupational position - PPT Presentation

Dave Griffiths and Paul Lambert University of Stirling 18 th March 2012 Sunbelt Conference Redondo Beach CA Work for this paper is supported by the ESRC as part of the project Social Networks and Occupational Structure see ID: 406033

weak ties friends amp ties weak amp friends occupations strong social managers clerks ego assistants individuals prandy wave 2008

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Slide1

Strong and weak ties as predictors of occupational position

Dave Griffiths and Paul LambertUniversity of Stirling18th March 2012Sunbelt Conference, Redondo Beach CA.

Work for this paper is supported by the ESRC as part of the project ‘Social Networks and Occupational Structure’, see http://www.camsis.stir.ac.uk/sonocs/Slide2

Theories

Social interaction: stratification effects can be demonstrated (Chan, 2010; Laumann & Guttman, 1966; Prandy, 1990; Stewart, Prandy

& Blackburn, 1973; Stewart, Prandy, & Blackburn, 1980)Strong and weak ties: Strong ties provide support, weak ties provide substance (Grannovetter 1973, 1983)

Social capital: access to beneficial resources is beneficial in itself (c.f. Lin & Erickson 2008)Occupational differentiation: more detail occupational distinctions provide more robust measures (Jonsson et al. 2009)Slide3

Aims

Do more advantaged occupations have increased access to more beneficial resources?Do Position Generators accurately measure accesses to resourcesDoes composition of strong and weak ties matter?Slide4

Methodology

BHPS 1991-2008Individuals linked to all they are related to, named as a friend or lived with.Individuals placed within networks of all the alters of their alters, snowballed to include all possible friends of friends of friends of friends30k individuals grouped into 9k networksSlide5

Wave 1: Ego (1) lives with parents (2 & 3) and sibling (4)

Wave 3: Ego lives with three friends (5, 6 & 7)Wave 5: Ego lives with partner (8)Wave 7: Ego and partner move in with partner’s parents (9 & 10)Wave 15: Ego shares house with three others (11, 12 & 13)

EgoLives with parents in 1991

Lives with friends in 1993

Lives with partner

in 1995 (away from hometown)

They

move into partner’s parents in 1997 (returning to hometown)

They split up and ego lives in shared house in 2005

This produces a network of 13 individuals in the survey who have lived with the same ego. There would be 18 opportunities for people to name a best friend, possibly creating a network of 31 individuals.

If the sibling has a similar pattern, we could have 22 individuals linkable to the Wave 1 household, and 32 friends. With parent’s (10) friends, this is a network of 64 people.Slide6
Slide7
Slide8

Strong ties

Parent - childGrandparent - grandchildSibling - siblingSpouse - spouseWeak

ties

include ego to:Best friends and housematesS

pouse’s friends and family

Former housemates

Spouse’s former housemates

Son’s spouses former housemates

Friends of son’s spouses former housematesSlide9

Jobs held

Most recent job

CAMSIS

Guveli

%

male

University teaching professionals

1,821

1,076

82.3

2

52.3%

Primary and middle school teachers

4,137

1,036

65.5

4

13.0%

Other managers and administrators n.e.c.

3,865

1,560

63.5

1

71.3%Other secretaries, personal assistants6,3001,88062.353.2%Managers and proprietors in service industries7,6152,63362.3356.3%Accounts and wages clerks, book-keepers8,8722,28359.5535.6%Farm owners and managers2,2661,09458.3877.6%Counter clerks and cashiers4,1831,19055.4530.7%Nurses6,8652,07753.9410.2%Clerks (n.e.c.)12,1973,93752.4530.4%Sales assistants19,2005,66351.9529.3%Other childcare and related occupations3,8821,12351.552.0%Care assistants and attendants of older people5,1861,59446.7512.2%Chefs, cooks, hotel supervisors3,7941,21543.5644.5%Carpenters and joiners3,1351,09842.3699.1%Metal working production and maintenance4,2271,69341.5697.5%Storekeepers, warehousemen/women4,54385837.5582.5%Cleaners, domestics12,4683,78436.4719.2%Bar staff3,6811,16136.0541.0%Drivers of road goods vehicles5,7051,99534.5795.8%

20 most common occupations

Source: BHPS 1991-2007Slide10

%

of all BHPS networks with at least one…

University teaching professionals

13.4%

Primary and middle school teachers

12.4%

Other managers and administrators n.e.c.

16.7%

Other secretaries, personal assistants

21.9%

Managers and proprietors in service industries

26.0%

Accounts and wages clerks, book-keepers

22.6%

Farm owners and managers

8.8%

Counter clerks and cashiers

13.3%

Nurses

21.3%

Clerks (n.e.c.)

32.3%

Sales

assistants44.8%Other childcare and related occupations13.7%Care assistants and attendants of older people17.3%Chefs, cooks, hotel supervisors13.7%Carpenters and joiners12.2%Metal working production and maintenance16.7%Storekeepers, warehousemen/women11.9%Cleaners, domestics32.4%Bar staff13.7%Drivers of road goods vehicles19.4%Slide11

% of networks linking to

% of those with a link to occ. from all who have CAMSIS…

..over 65

..below 35

Diff.

University teaching professionals

13.4%

22.3%

7.1%

15.2%

Primary and middle school teachers

12.4%

20.3%

6.4%

13.9%

Other managers and administrators n.e.c.

16.7%

17.6%

9.8%

7.8%

Other secretaries, personal assistants

21.9%

21.5%

14.2%7.3%Managers and proprietors in service industries26.0%23.7%18.4%5.3%Accounts and wages clerks, book-keepers22.6%21.5%14.7%6.8%Farm owners and managers8.8%9.0%7.0%2.0%Counter clerks and cashiers13.3%11.9%9.0%2.9%Nurses21.3%20.0%14.9%5.1%Clerks (n.e.c.)32.3%28.2%22.9%5.3%Sales assistants44.8%36.5%36.8%-0.3%Other childcare and related occupations13.7%10.5%11.0%-0.5%Care assistants and attendants of older people17.3%11.4%16.2%-4.8%Chefs, cooks, hotel supervisors13.7%9.9%11.6%-1.7%Carpenters and joiners12.2%8.6%10.0%-1.4%Metal working production and maintenance16.7%12.5%13.5%-1.0%Storekeepers, warehousemen/women11.9%8.3%10.5%-2.2%Cleaners, domestics32.4%22.8%33.4%-10.6%Bar staff13.7%11.7%10.3%1.4%Drivers of road goods vehicles19.4%12.2%23.5%-11.3%Slide12
Slide13

Public private divide

Secretaries

IT/software/ computer experts

educationalistsLaboratory workerHealthcare workers

Managers

PR/ advertising

artists

Farm workers

No strong patterns – plenty of dyads with an obvious working relationship, but linking together unrelated areas (i.e., clothes makers and coal miners linking together)

All ties

Social workersSlide14

Weak ties

(mostly friendship or distant hhld connections)Slide15

Strong ties

(mostly close family/ household sharers)Slide16

mean CAMSIS

most recent job

Ever held

job

%

of people with any link

to category

Education

71.6

4.2%

4.7%

31.0%

Healthcare

56.3

4.7%

5.6%

42.6%

Law

77.4

0.6%

0.7%

8.1%

Financial services

71.31.3%1.9%20.3%Builders42.25.7%7.2%52.9%Car mechanics43.30.9%1.4%17.0%Slide17
Slide18
Slide19

Weak tie

Strong tieSame occupation86.7%13.3%

Different occupation84.0%16.0%

CAMSIS

Weak ties

Strong ties

.

38

.

58

Weak ties

.

46

Correlation between most recent CAMSIS score and the mean of strong and weak ties

Source: BHPS 1991-2008

Percentage of within occupation connections attributable to strong and weak ties.

Source: BHPS 1991-2008Slide20

Conclusions

Position Generators tend to lead to grouping together of occupations with similar stratification positions, but:Can elide nuanced differences between some occupationsPossibly due to the need to focus on selected common occupationsOther forms of network summary may better reflect social distances than PG approachDifferences between strong and weak ties can be observed in patterns of common connections between occupations, with weaker ties dispersed more widely and structurally less shaped by stratification position

Little difference between strong and weak ties in strength of relation between own and alter occupation: both reflect the same overall trend for homophilySlide21

Bibliography

Chan, T. W. (2010). The social status scale: Its construction and properties. In T. W. Chan (Ed.), Social Status and Cultural Consumption (pp. 28-56). Cambridge: Cambridge University Press.Granovetter, M. (1973) The Strength of Weak Ties. American Journal of Sociology, 78(6), 1360-1380.Granovetter, M. (1983) The Strength of Weak Ties: A Network Theory Revisited. Sociological Theory, 1, 201-233.

Jonsson, J.O., Grusky, D.B., Di Carlo, M., Pollak, R., & Brinton, M.C. (2009) Microclass Mobility: Social Reproduction in Four Countries. American Journal of Sociology, 114(4), 977-1036.Laumann, E. O., & Guttman, L. (1966). The relative associational contiguity of occupations in an urban setting. American Sociological Review, 31

, 169-178.Lin, N., & Erickson, B. (2008) Social Capital: An International Research Program. Oxford: Oxford University Press.Prandy, K. (1990). The Revised Cambridge Scale of Occupations. Sociology-the Journal of the British Sociological Association, 24(4), 629-655.Stewart, A., Prandy, K., & Blackburn, R. M. (1973). Measuring the Class Structure. Nature.

Stewart, A.,

Prandy

, K., & Blackburn, R. M. (1980).

Social Stratification and Occupations

. London: MacMillan.