Analysing Multiple Types of Connections within a Network

1. Analysing Multiple Types of Connections within a Network Dave Griffiths University of Stirling 18th September 2009

2. What do networks attempt to measure? • Limitations in knowing what to analyse • Limitations in researching elites • Methods available for understanding structure across spheres of influence

3. Network analysis analyses networks • Network theory is about analysing ties between actors • How we define ‘ties’ determines the meaning we generate • In many situations, there are multiple types of ‘ties’ available * school friends – classroom, lunchtime or at home • How do we prioritise what types of ties are important?

4. Problem within Elites research • Researching elites and power an important sociological concept • Useem’s (1984) Inner Circle details how controlling elites know each other • How do we define how people ‘know’ each other?* mutual board memberships mask personality clashes* clubs not always frequented* who knows who is invited to each others homes • Data we hold might be misleading; most relevant data unobtainable

5. Problem with interlocking directorates • We regard two companies as well-connected if they hold a mutual board member • We analyse the network of companies connected by mutual board members • Bart’s (1982) Structural Hole theory suggests connections between boards facilitated by one individual are not well-connected • Therefore, do mutual board membership ties tell us much about how information can flow through boards of governance? • Does information only flow through board meetings?

6. Research question • How do we analyse various modes of relationships between actors, without drowning in data? • Which types of ties do we focus upon, and which can be ignored? • How do you measure the centre of a network when it alters under every type of tie studied?

7. Methodology • Data collected on 187 UK quangos* more specifically, on their 2,858 directors • All information published by quangos and biographical directories coded, including* school and university attended* corporate and charitable directorships* employers* memberships of professional associations and private clubs* institutions awarding honorary degrees • Data coded as whether present (as of 01/01/07) or previous • 27 different networks constructed linking quangos through these assorted ‘ties’ • Density of networks ranged from .04 to .54

8. Basic overview of networks

9. The problem of merging data

10. More manageable networks Charities Affiliations School Companies

11. Interlocking quangocrats

12. What do we analyse? • Multiple levels of connections between quangos • Different descriptions lead to important network differences occuring • Therefore, research question needs to contextualise what types of connections we measure • When we are studying elites and connections, however, all potential ties are important in their own ways • A method of identifying the most important types of ties is important

13. Relationship between degree and centrality

14. Corporate and quango ties Companies Quangos

15. Degree and centrality in two-mode

16. Identifying the most central organisation • Component analysis = how many times an institution appears in the largest component • Core analysis = how many times an institution appears in the tightest core of the network • Therefore, which quangos are consistently in the best positions, and which are consistently in the worse?

17. Most connected quangos • Arts and Humanities Research Council; Audit Commission; Bank of England; BBC; Biotechnology and Biological Sciences Research Council; British Council; British Museum; Channel 4; Culture North West; Economic and Social Research Council; English Heritage; English Partnership; Environment Agency; Health Protection Agency; Heritage Lottery Fund; Higher Education Funding Council; Historic Royal Palaces; Imperial War Museum; Learning and Skills Council; Medical Research Council; National Consumer Council; National Maritime Museum; National Museum of Science and Industry; National Museums Liverpool; National Portrait Gallery; Natural Environment Research Council; North West Development Agency; Northern Lighthouse Board; Nuclear Decommissioning Authority; Qualifications and Curriculum Authority; Quality Improvement Agency; Royal Botanic Gardens Kew; Tate; Victoria and Albert Museum; VisitBritain

18. Least connected quangos • Agricultural Wages Board; British Potato Council; British Shipbuilders; Commission for Patient And Public Involvement; Criminal Injuries Compensation Authority; Culture South West; Energywatch; Engineering Construction Industry Training Board; Firebuy; Football Licensing Authority; Home-Grown Cereals Authority; Horticultural Development Council; Independent Living Funds; Investors in People; LEASE; Living East; Meat and Livestock Commission; Milk Development Council; Oil and Pipelines Agency; Office of the Children’s Commissioner; Parole Board; Partnerships for Schools; Public Lending Right; Remploy; Royal Marines Museum; Royal Navy Submarine Museum; S4C; Security Industry Authority; Stonebridge HAT; Tote; Trinity House; Valuation Tribunal Service.

19. Most marginalised quangos

20. Central narrative • Corporate interests lowly prioritised within quango networks • Little evidence of occupancy of multiple quango boards • Consistency amongst other indicators of social connections between directors • Ties to the cultural elite creates connections • Multiple types of interest important; strongly bonding to one type lessens network position

21. Conclusions • Empirical meaning can be gathered from exploring the full range of potential connections between actors • Analysing the differences between networks in terms of impact of degree on centrality can identify which types of connections are atypical • If consistent structures can be observed, you can start to create your narrative of what is occurring