IDEAS home Printed from https://ideas.repec.org/a/sae/envira/v51y2019i6p1217-1224.html
   My bibliography  Save this article

Characterising labour market self-containment in London with geographically arranged small multiples

Author

Listed:
  • Roger Beecham

    (School of Geography, University of Leeds, UK)

  • Aidan Slingsby

    (City, University of London, UK)

Abstract

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.

Suggested Citation

  • Roger Beecham & Aidan Slingsby, 2019. "Characterising labour market self-containment in London with geographically arranged small multiples," Environment and Planning A, , vol. 51(6), pages 1217-1224, September.
  • Handle: RePEc:sae:envira:v:51:y:2019:i:6:p:1217-1224
    DOI: 10.1177/0308518X19850580
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0308518X19850580
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0308518X19850580?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Beecham, Roger & Lovelace, Robin, 2022. "A framework for inserting visually-supported inferences into geographical analysis workflow: application to road safety research," OSF Preprints mfja8, Center for Open Science.
    2. Beecham, Roger & Tait, Caroline & Lovelace, Robin & Yang, Yuanxuan, 2022. "Connected bikeability in London: which localities are better connected by bike and does this matter?," OSF Preprints gbfz8, Center for Open Science.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:envira:v:51:y:2019:i:6:p:1217-1224. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.