Node Publications


Connected Lives

Connected Lives project by Real Life Methods (RLM) explored the dynamics of social networks and ‘community’ interactions, through a multi-dimensional neighbourhood case study. Their approach brought together perspectives from disciplines isuch as health, transport studies, human geography, informatics and sociology. Researchers at RLM investigated how different social groups construct networks of friends, relatives, neighbours and service providers, and how these networks are maintained over time and across space.
RLM chose an inner city district of Leeds with a heterogeneous population and diverse levels of affluence. Researchers at RLM investigated how and why the social networks they discovered were perceived to be important to these groups. They were also keen to understand the interaction between travel, communication technologies, and transport service provision and the creation and maintenance of these networks.
RLM explored which research methods are appropriate for understanding networks and communities and how these methods can be combined to create “fuller accounts” of communities. Their main research methods were:

  1. Participatory social mapping
  2. Regular fieldsite walkarounds and walking interviews
  3. Interactive diaries, with qualitative interviews
  4. Qualitative and quantitative techniques for representing neighbourhood and networks.


Duration: 2005-08

Researchers: Andrew Clark, Nick Emmel, Frances Hodgson, Jon Prosser


Family Background in Everyday Lives

This project investigated the role and the concept of ‘background’ in the inheritance, creation, and maintenance of family and interpersonal relationships. RLM researchers were interested in the interplay between where a person comes from, both in a geographic and social sense, and the ways in which they are connected to and differentiated from a variety of others. Researchers at RLM explored how differences in background are narrated and negotiated within families as well as the manifestations of background in family rituals and ceremonies and everyday practices and experiences.

The primary research methods used were: 


RLM also commissioned questions in a national omnibus survey. The survey data was used to gauge popular expressions of 'family background' in a nationally representative sample, so that RLM researchers could understand how widespread different conceptions and experiences of background are, and how these are related to conventional socio-demographic variables.

Duration: 2006-08

Researchers: Stewart Muir, Jennifer Mason, Carol Smart

Living Resemblances

RLM researchers investigated the social significance of family resemblances or likenesses. They explored how people make sense of, live with and theorise about all kinds of family resemblances, from physical likenesses to resemblances in temperament, character, emotion, behaviour or health. RLM was interested in the societal fascination with family resemblance, and they explored how this is played out and what it says about contemporary understandings of kinship, genetic inheritance, and identity. Researchers at RLM wanted to find out why ideas and assumptions about resemblances seem to matter so much, and what role they play in family life and outside it.

Their methods included:


Duration: 2005-08

Researchers: Katherine Davies Jennifer Mason, Carol Smart, Lynne Cameron, Brendan Gough, Josephine Green, Jon Prosser

Young Lives

In ‘Young Lives’ project RLM investigated the nature and dynamics of young people’s lives and times across three domains:

Researchers at RLM explored young people’s identities, their values and role models. RLM researchers also investigated how young people construct life-plans and how they make sense of their past, present and future
Young Lives used a blend of qualitative and quantitative methods in a longitudinal time frame:


Duration: 2005-08. This project had continuation funding under the ESRC Timescapes programme until 2012.

Researchers: Anna Bagnoli, Sarah Irwin,  Bren Neale, Jennifer Mason, Jon Prosser.