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Internal migration flows in Northern Ireland: exploring patterns and motivations in a divided society Gemma Catney PhD Research Student Centre for Spatial.

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Presentation on theme: "Internal migration flows in Northern Ireland: exploring patterns and motivations in a divided society Gemma Catney PhD Research Student Centre for Spatial."— Presentation transcript:

1 Internal migration flows in Northern Ireland: exploring patterns and motivations in a divided society Gemma Catney PhD Research Student Centre for Spatial Territorial Analysis and Research (C-STAR) School of Geography, Archaeology and Palaeoecology (GAP) Queen’s University, Belfast UPTAP Session 2, RGS-IBG Annual Conference, 2006

2 Residential Segregation in Northern Ireland  Religious residential segregation in NI – media and academic research  New academic research pointing towards residential segregation as either decreasing or staying the same  However, large geographic variations, with some increases in segregation in particular areas, and persistence in others  But why?

3 Internal migration in Northern Ireland  In situ growth and/or migration  Simpson (2004), in Urban Studies  Migration – reinforcement, erosion, creation of residential segregation?  How far is community background important in migration decision-making?  Under-explored and little understood

4 Presentation outline  The geography of migration in NI  Migration rates  Mobility differentials  Internal migration and residential segregation  Migration rates by community background  Global regression: demographic composition and migration  Local regression (GWR)  Before and after migration  Segregation indices, etc.  Further work: current and future  Conclusions

5 Methodology in brief QUANTITATIVE Migration rates and differentials Geographically weighted regression (GWR) SI modelling DATA SOURCES Census of pop. of NI (2001) Census grid square data (1971-2001) Residents (movers and non-movers) Key informants (community reps, property developers, etc.) QUALITATIVE Semi- structured interviews Focus groups Cognitive Mapping

6 In- and out-migration Inflow rate (per 1000 pop.) Outflow rate (per 1000 pop.)

7 VariableMost mobileLeast mobile Age20-24 (17.77%)65-74 (2.56%) GenderFemale (7.89%)Male (7.29%) Community backgroundProtestant (7.50%)Catholic (7.49%) ReligionCatholic (7.19%)Protestant (7.11%) Marital status Separated (but still legally married) (13.71%) Widowed (4.37%) Economically active Economically active (8.56%) Economically inactive (6.50%) Economic activity Full-time student (17.29%) Self-employed (5.49%) Economic inactivity Student (11.00%) Retired (2.59%) QualificationsHigher level qualifications (10.86%) No qualifications (4.79%) Limiting long-term illness (LLTI) No LLTI (8.03%)LLTI (5.92%) Family statusNot in a family (12.16%)In a couple family (5.78%) Ethnic groupOther ethnic group (11.57%)White (7.57%) Resident typeLiving in a communal establishment (24.78%) Living in a household (7.32%)

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9 Internal migration and residential segregation: solving the problem Count (area) data Global regression – demographic composition and migration Geographically Weighted Regression Before and after migration Segregation indices and conc. profiles % Differences (CB)

10 Migration rates by community background Catholic inflow over total inflow Catholic outflow over total outflow

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13 (b) Deciles of % Protestant residents against % Protestant outflow (a) Deciles of % Catholic residents against % Catholic outflow

14 What is GWR?  Normal regression assumes that a relationship between variables holds at each location  Geographically Weighted Regression (GWR) accounts for spatial variations in the relationships between variables  GWR produces regression coefficients at (the centroid of) each selected location, facilitating an assessment of how the relationship between a set of variables changes from place to place

15 GWR and migration  Local variations in the regression between demographic composition and in- and out- migration not accounted for with global regression  Useful in understanding these relationships, and in predicting future change  % residents by community background and inflow / outflow by community background as proportion of all inflow / outflow

16 GWR: Catholic residents against Catholic inflow

17 GWR predictions (independent = 50%)

18 Before and after migration  Examine population after migration (2001) and before migration (2000) Potential issues: Potential issues:  In situ growth: data on births and deaths  Internal migrants only: no GB (or further) data on community background  Possibilities: Proportions (% CB) Proportions (% CB) Segregation indices Segregation indices Concentration profiles Concentration profiles

19 Segregation indices: the role of migration D S S* x P* y x P* x x P* y 2 x P* x 2 Before0.6011680.2714880.3296800.2464220.7535780.2992420.700758 After0.6010590.2714370.3296210.2465180.7534820.2993600.700640 Change-0.000109-0.000051-0.0000590.000095-0.0000960.000118-0.000118

20 Segregation indices: the role of migration  Overall indication of minimal change, with decreasing segregation and greater mixing  But, these are global measures  Can use, for example, % Catholic and Protestant before and after migration  Do show considerable local variations – some areas increasing, some decreasing

21 Other work: current and future  Origin-destination (flow) data  SI modelling  Logistic regression  Principal Components Analysis  Etc  Qualitative research  Interviews, focus groups and cognitive mapping  Selected case study areas (Belfast)

22 Transect: South Belfast

23 Summary and conclusions  Some insight into the geography of migration in NI  Methods for exploring the relationship between internal migration and residential segregation  Migration has a role to play in the creation, reinforcement and erosion of segregation  Positive relationship between demographic composition and migration  Local variations in the relationships  Variable from place to place, but broadly suggests a decline in segregation due (at least in part) to migration

24 Acknowledgements  UPTAP  My supervisor, Dr Ian Shuttleworth, for his comments and advice  NISRA, for the provision of Census data  Department for Employment and Learning (DEL), for funding  Contested Cities, Urban Universities (CU2) research team and funding body (European Programme Peace 2)


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