Equalities event, david clifford, third sector research centre, 8 nov 2012
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Equalities event, david clifford, third sector research centre, 8 nov 2012
- 1. Voluntary sector organisations and spatial inequality: what do we know? what can we know? David Clifford Third Sector Research Centre
- 2. Spatial patterns in deprivation Deprivation is concentrated geographically •Particular variation at local scale •These differences are persistent •A fundamental feature of social life
- 3. Main question What are the implications of these spatial patterns in deprivation for the voluntary sector? -here, particular focus on distribution of organisations
- 4. Why? (1) Expectations of unevenness ‘some social and geographical contexts seem to provide a much more fertile soil for voluntary action than others’ (Wolfenden, 1978) ‘the resources are frequently not available where the problems are most severe’ (Salamon 1987)
- 5. Why? (2) Unevenness has implications.. ..for equity of provision of services and amenities ..for opportunities to participate in voluntary group activities
- 6. Why? (3) Lack of empirical work.. Is there actually evidence for unevenness? Lack of work examining geographical differences in prevalence of voluntary organisations.. Particular lack of work at local scale
- 7. Basic idea To examine geographical differences in the prevalence of local voluntary organisations
- 8. How? Comparing between local areas with different levels of deprivation Prevalence of local voluntary organisations= No. of ‘neighbourhood’ organisations Survey data (NSTSO 2008) ____________________ Total population Office for National Statistics
- 9. What organisations are counted? • Third sector organisations (charities, CLGs, CICs, IPSs).. • ..that appear on national registers Therefore, more of a focus on ‘formal’ voluntary sector, rather than more ‘informal’ community sector
- 10. A partial perspective • Only organisations working at the local level • Many places of worship not included
- 11. Results: overall pattern 1.8 1.6 Prevalence (per 1,000 people) 1.4 1.2 1 .8 .6 .4 .2 0 100 80 60 40 20 0 Deprivation (percentiles)
- 12. Results: by size 1k-10k 10k-100k .8 .8 .6 .6 .4 .4 .2 .2 0 0 100 80 60 40 20 0 100 80 60 40 20 0 100k+ .8 .6 .4 .2 0 100 80 60 40 20 0
- 13. Results: by main role Delivery of public services Buildings and/or facilities .5 .5 .4 .4 .3 .3 .2 .2 .1 .1 0 0 100 80 60 40 20 0 100 80 60 40 20 0 Deprivation (percentiles) Deprivation (percentiles)
- 14. Results: by receipt of public funding No public income Public income 1.2 Prevalence (per 1,000 people) 1 .8 .6 .4 .2 0 100 80 60 40 20 0 Deprivation (percentiles)
- 15. Results: by role and public funding Delivery of public services Buildings and/or facilities .3 .3 .2 .2 .1 .1 0 0 100 80 60 40 20 0 100 80 60 40 20 0 No public income Public income
- 16. Results: robustness? Differences in propensity to register between different kinds of areas? Differences in propensity to respond to survey between different kinds of areas?
- 17. Results: summary For first time, illustrates significant geographical variation at local level in prevalence of registered voluntary organisations.
- 18. Results: do they matter? Implications for equity of provision: Neighbourhood groups ‘will be able to bid to take over the running of community amenities, such as parks and libraries, that are under threat’.. ‘will be given a right of first refusal to buy state- owned community assets that are for sale or facing closure’ (Conservatives, 2010)
- 19. Results: do they matter? Some communities will be much better equipped than others to take on these new powers Government funding is particularly important to the voluntary sector in the most deprived areas
- 20. Way forward? • Examine specific kinds of organisations – NSTSO: data anonymised – Charity Commission data: search for specific groups • But no information on source of funding – Which organisations would be particularly interesting to look at?
- 21. Beneficiary groups: what information is collected in large scale datasets? David Clifford Third Sector Research Centre
- 22. Ideas for analysis..? • What organisations are you particularly interested in? – Chance to look at what data are available
- 23. Charity Commission (CC) data Information on: •Headline income and expenditure – Detailed income and expenditure streams for those above £500k in income •Local authorities in which operating •Year of registration
- 24. Beneficiary groups in CC data • Children/ young people • Elderly/ old people • People with disabilities • People of a particular ethnic or racial origin • Other charities / voluntary bodies • Other defined groups • The general public/ mankind Beware – charities may have ticked many boxes!
- 25. NSTSO data • Information on: size, age, local authority, scale of operation • Information on sources of income • Questions relating to relationships with local authority
- 26. Beneficiary groups in NSTSO data • More detailed • More focused: asked for no more than 2/3 boxes
- 27. Beneficiary groups in NSTSO data • Older people • Children (under 15) • Young people (aged 16-24) • People with physical disabilities • People with learning difficulties • People with mental health needs • People from Black and Minority Ethnic communities… ..and others
- 28. Opportunity to relate to theory.. • Billis and Glennerster (1998) – idea of comparative advantage: – voluntary organisations can have an advantage compared with other sectors when catering for certain categories of user disadvantage – Therefore, may be particular impetus for government to fund these groups?
- 32. David Clifford d.clifford@tsrc.ac.uk www.tsrc.ac.uk – under ‘Publications’
Editor's Notes
- Starting point – lots of the day will be about particular groups of people and equality issues – focus on gender, ethnicity, etc. But here focus on equalities issues in terms of spatial inequality – and how this might be manifest in the voluntary sector Focus on some of our work. But definitely want this to be an interactive session -this is a hard thing to examine. -what do you think? What might be the best way forward? Want to learn from you (definitely not that I have all the answers! – Just familiar with the data) Part of a team of researchers – very much want to acknowledge their input
- Starting point: Local scale – variation within cities Not the same that saying that the causes are geographical (neighbourhood effect) Not the same as saying that the majority of the poor live in poor areas Nevertheless, one of the fundamental features of social life – driven by labour and housing markets which sort people over space: some people can choose where they live, others can’t When we’re talking about equalities, this would seem to be an important issue
- Collective nature of associational life -particular importance of social context for organisations ? (vs. more individual forms of civic action?
- i.e. why do this? Expectation of uneveness. Salamon – resource insufficiency a ‘failure’ of VS in general, but particularly manifested in certain areas. Therefore philanthropic ‘particularism’ may be manifested spatially, with certain communities well served and others less so.
- To extent to which these organisations involved in providing services/amenities. ie. Where focus on specific community of interest, allows responsiveness to this community – but need not in the aggregate tie in with broader social goals of ensuring equity of access to services and amenities 2. Participation considered a structural element of social capital (associated with cultural aspects like trust) which is a characteristic of communities that facilitates coordination and cooperation for mutual benefit.
- In other words, expectation of differences, and these differences are important- but we haven’t shown this!! (Studies have looked at volunteering – but not voluntary organisations) (those that have – often US.) (Not nationally representative) Lack of work at local scale esp significant -know that variations in levels of deprivation esp significant at local, rather than say regional level – expectaion of uneveness at this level -focus on neighbourhood organisations as part of BS: The government’s reform agenda is designed to give new powers and rights to neighbourhood groups in order to help communities address local issues (for example, in being able to bid to take over the running of community amenities, such as parks and libraries, that are under threat). One of the stated ambitions is that ‘every adult in the country becomes an active member of an active neighbourhood group’ (Conservatives, 2010) **Sum up – three reasons for why? 1) expectation; 2) Potentially important; 3) lack of previous work
- Prevalence – number of organisations per 1,000 people Local – those working at the neighbourhood scale Geog differences – i.e. differences across the country
- i.e. that’s why we’re doing it – what about how? Comparing between areas according to IMD – multidimensional measure of deprivation Prevalence= counting organisations in an area and dividing by number of people there. (Multiply by 1000) NSTSO – only way of identifying those that work at neighbourhood level. Not possible before. i.e. only counting those working locally – not those working nationally or regionally.
- National registers provided sampling frame for survey. Advantages – nationally represenative; not just charities (useful given different traditions of philantrhopy vs mutual aid in different kinds of areas); large sample size i.e. overall organisations with an ‘institutional’ structure – i.e. separate from their environment. Unregistered organisations are not included. Raises question about – what do we not see? What about patterns of unregistered organisations? This is an empirical question – but one v difficult to answer One hypothesis would be is that there is also more unregistered activity in less deprived areas (measuring informal volunteering – gradient less steep with deprivation, but still – if anything - higher in less deprived areas)
- Need to be very clear about what we’re measuring – and what we’re not. Certain caution needed. Organisations that say that they work nationally not included Increasingly, places of worship will be in our sampling frame – but weren’t at the time of the survey. So, a partial perspective on voluntary activity – but an important perspective nevertheless?
- Y axis; x-axis – more deprived local areas vs less. [don’t worry about spikes too much] GO THROUGH slowly – ensure they understand! i.e. this means that more organisations per head of population. i.e. overall much higher prevalence in less deprived areas; fewer in more deprived. Curve here – the very most deprived have the higher prevalence than those slightly less deprived
- i.e. also disaggregated certain kinds of organisations according to their income. Three panels: 1-10; 10-100; 100+ Again point out that most deprived on right. i.e. smaller organisations more prev – not necessarily bigger ones (think: which organisations are these?)
- [NB – lots of other main roles too. Just two presented. Also did fields – look at paper]. Again – overall pattern, but in the very most deprived increases again.
- Question asked about whether they received at least some income from government sources – whether from local or central government. Can see that the peak in most deprived (go back a few slides) reflects the presence of govt funding in these areas. (Without these organisations, this peak wouldn’t exist) Emphasise crossing of line – many more local organisations which receive no public funding, than those that do, in less deprived areas. v.v. in more deprived. Would seem to indicate the importance of public funding for these organisations.
- Further disaggregated. i.e. spike in prevalences at high levels of deprivation reflects presence of organisations which receive some govt funding. Again, crossover in buildings graph (quite a common feature – also for those working within ‘fields’ eg economic well being; health and well-being; training; community development/mutual aid). i.e. more non-publicly funded in less deprived than publicly funded; and vice versa.
- Robustness: in other words – are these reflecting real patterns on the ground? Propensity to register: yes, should be sensitive to this. more of an issue when considering implications in terms of voluntary participation, rather than implications in terms of service provision (many of the latter more institutional in character and therefore likely to appear on register) [NB not so much that missing informal out per se, but whether systematic difference in level of formality between different kinds of areas). Response rate? But size of difference, shape of curves – don’t think just this. Judgement – yes, probably. But I don’t think the patterns JUST reflect this. i.e. real, on the ground, unevenness in local formal voluntary sector activity
- i.e. very uneven!
- Recent emphasis on neighbourhood groups Better unevenness than ‘drab disabling unformity of state in decline’. But not so much concern about expressive role – but potential for uneveness in provision of services and amenities. Want your views on this too – do you think these results matter?
- Which kinds of organisations? Difficult to tell from NSTSO because can’t look at their names.. Also, CC data obviously doesn’t include mutuals etc. (for these reasons that initially chose NSTSO). Which kinds of organisations does this reflect? We might be more concerned about differences in some than others -community / village halls -PTAs -scouts -nurseries, playgroups, preschools -youth clubs -community associations, neighbourhood watch -womens groups (WI, Townswomen’s guild) -Rotary, Inner Wheel, Lions, Round Table – i.e. serious leisure? -grantmaking groups **Any questions?
- Second part of the presentation is on the kind of information that is collected on beneficiaries in the largescale datasets that we have used. Haven’t done a lot of work looking at specific patterns for kind of groups
- If you were interested in finding out basic statistics on certain registered organisations: numbers, total income, mapping them..
- For 160,000 organisations..
- Alternative would be to use keywords in name, or activities field, to identify organisations
- More detail provided than CC data, and also includes noncharitable organisations
- More detailed than CC
- Why? Stakeholder ambiguity – less clear-cut differentiation between provider and recepient etc vs more hierarchical state agencies – which can lead to greater sensitivity/ knowledge about client need Funding these groups – i.e. rather than directly providing services Just illustrative really – i.e. these data can be related to theory (though not direct test)
- i.e. illustrative of the kind of information that is available.. i.e. socially disavantaged (stigmatised individuals and groups) – socially excluded/vulnerable people. People with mental health needs, offenders/ex-offenders, asylum seekers, refugees, homeless people, people with addiction problems Personally disadvantaged (require others to act on their behalf since unable to coherently articulate their preferences)– people with learning difficulties Community disdavantage Financial disadvantage i.e. it is indeed some of these groups for whom public funding most important
- Re-emphasise columns
- Re-emphasise columns
- Thank you for listening.. Working paper on statutory income, and on neighbourhood organisations (search for name) **Any questions?