Mobilitiy and participation geographies
-
Upload
everydayparticipation -
Category
Presentations & Public Speaking
-
view
1.055 -
download
0
Transcript of Mobilitiy and participation geographies
Locating Narratives of Mobility and Participation
Andrew Miles and Adrian Leguina
University of Manchester
Some framings The contemporary crisis of social mobility - The Social Mobility and Child
Poverty Commission’s Social Mobility Index (2016). Inequalities in mobility chances profoundly geographical
‘The London Vortex’ (Savage et al 2015); Escalator regions (Fielding 1989, 1992); Eurostars and Eurocities (Favell 2008)
Rebalancing our Cultural Capital (Stark et al 2013); ‘London and the English Desert’ (Dorling and Hennig 2014)
Typologies of middle-class mobility: Merton (1968) locals and cosmopolitans; Stacey (1967) traditionalists and non traditionalists; Watson (1964) spiralists and burgesses.
Widdop and Cutts (2012) ‘Impact of Place on Museum Participation’
Brake on mobility and participation geographies - Methodological nationalism and measurement focus of the dominant tradition in both social mobility and participation research
Savage et al (2005), ‘elective belonging’ of the middle-class mobile
How incoming middle-class people ‘claim moral rights over place’, ‘announcing their identities’ through their capacity to move to place that is congruent with their life story, and which is therefore symbolically as well as functionally important to them
Thereby ‘Elective belonging pitches choice against history, as the migrant consumer rubs up against dwellers with historical attachments to place’
•Process and interplay of movement, mobility and culture•Symbolic importance of places•Analysis of talk in texts
The National Child Development Study
xBorn
19581st Child 1984 2nd Child
1987Age 7 Age 11 1991 2000
Age 42
2004
Age 46
Age 16
Age 23
1981
Age 33
Gets married
Parents’ social class
Parental interest in school work
Free school meals
Mother smoking
Parental divorce
Maths and reading tests
Teachers’ assessment of child’s behaviour
Exam results
Job 1 Job 2 Job 3
Voting behaviour
Psychological well being
Working hours preferences
Savings
Domestic division of labour
Union membership
Training and skills
Social participation and identity project
Undertaken by CRESC and CLS in 2008/09 - the first major qualitative study of NCDS members
Aim – to conduct longitudinal analysis of changing forms of participation and identity, both by analysing testimony from the interviews and through linkage to previous quantitative waves of the NCDS
Aim - 60 cohort members in three geographic regions, SE England, NW England and Scotland. Subsequent boost sample of 60 interviews in Wales commissioned. Total of 220 interviews achieved
Theoretically- driven sampling. Stratified in terms of social mobility measured by social class in childhood to produce 20 interviews with stable working class, 10 with stable service class, 20 upwardly mobile and 10 downwardly mobile in each region
Structure of the interview and topic guide
Average 90-minutes semi structured interview divided into six sections:
Neighbourhood and belonging Social participation and leisure activities Friendships Life story and trajectories Identities (self, class, work, generation, national, gender) Experience of the NCDS
Quantitative data analysis• Participants from NCDS8 (age 50) were linked to NCDS3
(age 16). If missing, it was replaced by NCDS7 (age 46) or NCDS2 (age 11) respectively (8693 cases).
• Overall distribution of NCDS8(7) and NCDS3(2) linkage in terms of selected socio-demographics
Gender % Marital status % Children %
Male 51.2 Single & never married 10.1 No children 16.6
Female 48.8 Married 70.6 +1 children 83.4
Separated from Spouse 3.0
Divorced 15.0
Widowed 1.2
Text mining of interview data• Computer Assisted Qualitative Data AnalysiS (CAQDAS)
• Our approach rests in ‘dictionaries’ (words selected by the researcher). These are compared against the texts loaded into the software (‘corpus’), returning the frequencies with which these words occur
Corpora
Text mining of interview data
• Objective of the analysis is to explore the texts on the basis of word frequencies
• Central to the analysis is to ‘create’ a dictionary of individual words and multiword expressions which is consistent with subject in study.
• Software: Spad (still experimental stage and not very flexible for more elaborated analysis). Procedure:
Creating a dictionary• Clean interview extracts and copy them into a plain file.
Include demographics from surveys
• First step in Spad consists on cleaning (‘lemmarizer’ and ‘repeated segments’ tools): delete non-relevant words, detect similarities and create ‘grouped’ dictionary entries. Done mostly manually
• For participation we analysed a dictionary of 349 entries, and 236 for class identity in two separate analysis. These come from a subsample of 30 interview extracts
• Spad produces a ‘lexical contingency table’ to be analysed using correspondence analysis
Correspondence analysis
• Multivariate technique used to analyse categorical data, structured as contingency tables
• Data commonly used in cultural studies come from surveys:
(statistical) individuals are surveyed people and variables are questions operationalized as categorical variables (choice of one or more options)
• The objective of CA it is the study of the diversity of response patterns through the reduction of their dimensionality on factorial axes that retain maximum variability, providing summary values which can be plotted as clouds to visualise interrelations among individuals and categorical variables
• The graphical representation of CA is its most important outcomes. Every individual and category is represented by a point, and closeness between two points represents the degree of association between two corresponding individuals (or categories)
Simple correspondence analysis
Simple correspondence analysis of textual data: Like regular SCA but…
•Data structure: rows = dictionary, columns = individuals and demographics
•Meaning: number of times a word/phrase is repeated by respondents (of certain characteristics). In the same way as regular SCA, words and individuals act as active frequencies of the table, while demographics are supplementary
•Objective of the analysis is to find patterns of keywords common to individuals and certain groups defined by selected demographics
Dictionary Cells = Frequencies extracted from each corpus
Corpora
Patterns of social mobility by region
Place 2008 Stable serviceUp: W toSer
StableW
Up: Int toSer
Down: Ser toW
Down:Int toW
North East 21.3% 58.5% 81.5% 20.2% 6.9% 11.5%
North West 21.9% 53.9% 65.5% 24.2% 13.6% 20.8%
Yorkshire and The Humber
24.0% 50.3% 72.1% 25.7% 11.2% 16.7%
East Midlands 20.6% 53.1% 71.5% 26.3% 10.8% 17.7%
West Midlands 22.3% 50.5% 76.6% 27.2% 7.1% 16.3%
East of England 28.6% 38.8% 70.0% 32.6% 9.5% 20.6%
London 27.9% 41.9% 58.0% 30.2% 12.5% 29.5%
South East 32.5% 36.1% 60.2% 31.4% 11.6% 28.2%
South West 30.7% 36.8% 65.5% 32.4% 10.2% 24.4%
Wales 22.5% 50.8% 72.0% 26.7% 7.3% 20.7%
Scotland 23.4% 52.7% 73.7% 24.0% 8.0% 18.2%
Geo-mobilities
20.0%30.0%40.0%50.0%60.0%70.0%80.0%90.0%
100.0%
NorthEast
NorthWest
Yorkshireand TheHumber
EastMidlands
West Midlands
EastofEngland
London
South East
South W
est
Wales
Scotland
Stable service
Stable W
Up: W to Ser
Up: Int to Ser
Participation: mobiles and movers
Finishing thoughts for now Relationship between socio-spatial mobility and
participation is complex Text analysis an interesting and promising way of finding
patterns in large volumes of qualitative material and thereby bridging the gap between quantitative data and the interview
Clear that there are ‘semantic fields’ of participation and class talk distinguished by socio-spatial mobility trajectories
Lots of work to do…