Characterising labour market self-containment in London with geographically arranged small multiples
Bibliographic Data
| ID | 4140995 |
|---|---|
| Authors | R Beecham (0000-0001-8563-7251, University of Leeds, corresponding author), Aidan Slingsby (0000-0003-3941-553X, City, University of London) |
| Year | 2019 |
| Volume | 51 |
| Issue | 6 |
| Pages | 1217-1224 |
| Publication date | 2019-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environment and Planning A Economy and Space (JOURNAL) |
| Journal identifiers | ISSN: 0308-518X • E-ISSN: 1472-3409 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/0308518x19850580 |
| OpenAlex | W2945935841 |
| Language | EN |
| Citations received | 3 |
| References cited | 4 |
We present a collection of small multiple graphics that support analysis and understanding of the geography of labour-market self-containment across London's 33 boroughs. Ratios describing supply-side self-containment, the extent to which working residents access jobs locally, and demand-side self-containment, the extent to which local jobs are filled by local resident workers, are first calculated for professional and non-professional occupations and encoded directly through geographically-arranged bar charts. The full distribution of workers into-and out-of- boroughs that underpins these ratios is then revealed via Origin-Destination flows maps (OD maps) - sets of geographically-arranged choropleths. In order to make relative and absolute comparison of borough-to-borough frequencies between occupation types, these OD maps are coloured according to signed chi-square residuals: for every borough-to-borough pair, we compare the observed number of flows to access professional versus non-professional jobs against the number that would be expected given the distribution of those jobs across London boroughs. Our geographically-arranged small multiples demonstrate potential for spatial analysis: a rich, multivariate structure is depicted that reflects London's economic geography and that would be difficult to expose using non-visual means
Archaeology · Borough · Business · Demographic economics · Economic geography · Economics · Geography · Sociology · Land Use and Ecosystem Services · Mathematics · Spatial and Panel Data Analysis · Urban Design and Spatial Analysis
| Citations per year | 1 |
|---|---|
| Citation span | 2023 - 2026 (4) |
| Highly cited | No |