Who’s in? Lifestyle data and geographical research
Lifestyle databases offer up-to-date, geographically relevant data about individuals. Yet, their application has been slow to extended beyond marketing and into geographical research. This apparent paradox is considered with reference to geocomputation. The unknown quality of the data generates appr...
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Unité Mixte de Recherche 8504 Géographie-cités
2000
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oai:doaj.org-article:be0fe1fea9c94d07a99193074cba3f532021-12-02T11:14:42ZWho’s in? Lifestyle data and geographical research1278-336610.4000/cybergeo.4343https://doaj.org/article/be0fe1fea9c94d07a99193074cba3f532000-02-01T00:00:00Zhttp://journals.openedition.org/cybergeo/4343https://doaj.org/toc/1278-3366Lifestyle databases offer up-to-date, geographically relevant data about individuals. Yet, their application has been slow to extended beyond marketing and into geographical research. This apparent paradox is considered with reference to geocomputation. The unknown quality of the data generates apprehension amongst potential users. Respondents to lifestyle surveys are self-selecting, creating bias in the dataset. Young adults are identified as least likely to return a survey and pensioners more likely. The level of population coverage achieved by the survey varies geographically. Hence, whilst lifestyles offer rich sources of micro-level data to cross-validate or supplement Census-based analysis, greater scientific credential remains as a pre-cursor to academic acceptance.Richard HarrisUnité Mixte de Recherche 8504 Géographie-citésarticle1991 UK CensuslifestylegeocomputationGeography (General)G1-922DEENFRITPTCybergeo (2000) |
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DE EN FR IT PT |
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1991 UK Census lifestyle geocomputation Geography (General) G1-922 |
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1991 UK Census lifestyle geocomputation Geography (General) G1-922 Richard Harris Who’s in? Lifestyle data and geographical research |
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Lifestyle databases offer up-to-date, geographically relevant data about individuals. Yet, their application has been slow to extended beyond marketing and into geographical research. This apparent paradox is considered with reference to geocomputation. The unknown quality of the data generates apprehension amongst potential users. Respondents to lifestyle surveys are self-selecting, creating bias in the dataset. Young adults are identified as least likely to return a survey and pensioners more likely. The level of population coverage achieved by the survey varies geographically. Hence, whilst lifestyles offer rich sources of micro-level data to cross-validate or supplement Census-based analysis, greater scientific credential remains as a pre-cursor to academic acceptance. |
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article |
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Richard Harris |
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Richard Harris |
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Richard Harris |
title |
Who’s in? Lifestyle data and geographical research |
title_short |
Who’s in? Lifestyle data and geographical research |
title_full |
Who’s in? Lifestyle data and geographical research |
title_fullStr |
Who’s in? Lifestyle data and geographical research |
title_full_unstemmed |
Who’s in? Lifestyle data and geographical research |
title_sort |
who’s in? lifestyle data and geographical research |
publisher |
Unité Mixte de Recherche 8504 Géographie-cités |
publishDate |
2000 |
url |
https://doaj.org/article/be0fe1fea9c94d07a99193074cba3f53 |
work_keys_str_mv |
AT richardharris whosinlifestyledataandgeographicalresearch |
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