B4130 - Cognihoods Measuring our mental maps of the mosaic of social worlds - 08/09/2022

B number: 
Principal applicant name: 
Levi John Wolf | School of Geographical Sciences
Title of project: 
Cognihoods: Measuring our mental maps of the "mosaic of social worlds"
Proposal summary: 

This project will transform our understandings of how neighborhoods “work” by developing a systematic and representative national study to understand neighborhood structure, function, and evolution, the first of its kind in the world. Neighborhoods are fundamental social and built environments for cities. They form the backbone of place-based policy and urban planning, nucleate our urban social communities, and have profound effects on peoples’ health, wealth, voting, and beyond. Often, policymakers and social scientists use administrative areas to stand in for our “neighborhoods,” but studies persistently show that these areas do not reflect peoples’ actual lived experiences. This mismatch between concept and measure reduces the effectiveness of place-based policy and confounds social science. Convenience samples (e.g. hoodmaps.com) or small-scale focus groups have sought to resolve this, but these are often unrepresentative—challenging to validate, reproduce, and generalize.

Instead, I will develop a novel social survey method that is socially-representative, reproducible, and generalizable. First, I will develop an open and reproducible neighborhood survey module with the Avon Longitudinal Study of Parents and Children (ALSPAC). Respondents will be able to draw their neighborhoods, describe them, and relate them to other parts of respondents’ lives. Then, I will seek to understand how potential mis-matches between these lived neighbourhoods and zones used in urban planning may affect political, social, and health inequalities and outcomes. Finally, I will work with the Cohort and Longitudinal Enhancement Resources (CLOSER), the UK’s world-leading network of cohort and longitudinal studies, to deploy this nation-wide and examine both the generality and stability of these lived neighborhoods over time. In addition, I will seek to develop statistical learning techniques that can predict where these communities might arise directly from information on the built environment. Altogether, this will provide the first socially-representative longitudinal study of neighborhood structure and function in the world.

Impact of research: 
Understanding the relationship between individuals and their small urban communities is critical for place-based policy and urban planning. Particularly, things like political efficacy (ability to change community), belonging, and self-percieved segregation/homogenity are important for understanding how to design and deploy urban policy. Practically, if the FLF is successful, the survey module will be rolled out nationwide, allowing for the first socially-representative systematic study of urban neighborhoods. This would be a substantial advance in urban studies, and I would hope to anonymize and release these neighborhood boundary perceptions (depending on disclosure protocols) for planners to use in designing new policy and drawing new political boundaries (e.g. https://ljwolf.org/bce)
Date proposal received: 
Thursday, 18 August, 2022
Date proposal approved: 
Friday, 19 August, 2022
Social Science, Statistical methods, Cohort studies - attrition, bias, participant engagement, ethics, Childhood - childcare, childhood adversity, Environment - enviromental exposure, pollution, Methods - e.g. cross cohort analysis, data mining, mendelian randomisation, etc., Psychology - personality, Physical - activity, fitness, function, Social science, Statistical methods