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Using Census, Institutional and Geospatial Data to Estimate the Socio-Economic Profile of Post-School Students by Institutional Type
The socio-economic profile of students who are participating in post-school education; and the distribution of their socio-economic characteristics between universities and colleges, between institutions of a similar type, and within particular institutions is not well understood. Part of the reason...
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| Format: | Thesis |
| Language: | English |
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School of Economics
2023
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| _version_ | 1867613265157160960 |
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| access_status_str | Open Access |
| author | Culligan, Samantha |
| author2 | Branson, Nicola |
| author_browse | Branson, Nicola Culligan, Samantha |
| author_facet | Branson, Nicola Culligan, Samantha |
| author_sort | Culligan, Samantha |
| collection | Thesis |
| description | The socio-economic profile of students who are participating in post-school education; and the distribution of their socio-economic characteristics between universities and colleges, between institutions of a similar type, and within particular institutions is not well understood. Part of the reason for this is because potential data sets that could be used to answer this fall short on dimensions needed to fully explore the extent of socio-economic differences amongst student bodies by institutional type. I, therefore, generate a data set that draws on institutional, census, and geospatial information to estimate the socio-economic background of students' home postal code. Using this data set, I compare the mean statistic and generalised entropy index of a range of individual and household socio-economic postal code indicators for student bodies by institutional type to descriptively analyse their socio-economic profile. I show student bodies at traditional universities and Unisa appear socio-economically similar and display higher socio-economic circumstances than that of student bodies at comprehensive universities, universities of technology and TVET colleges who appear socio-economically similar. Between 2008 and 2019, the mean socio-economic profile declined for all student bodies, whereas there was no uniform trend for whether socio-economic heterogeneity was increasing or decreasing over time by university type. Lastly, my findings suggest there is more evidence for horizontal stratification between particular universities (regardless of their institutional type) rather than between university types, or between universities and TVET colleges. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/37101 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:33:23.204Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | School of Economics |
| publisherStr | School of Economics |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/37101 Using Census, Institutional and Geospatial Data to Estimate the Socio-Economic Profile of Post-School Students by Institutional Type Culligan, Samantha Branson, Nicola Leibbrandt, Murray Economics The socio-economic profile of students who are participating in post-school education; and the distribution of their socio-economic characteristics between universities and colleges, between institutions of a similar type, and within particular institutions is not well understood. Part of the reason for this is because potential data sets that could be used to answer this fall short on dimensions needed to fully explore the extent of socio-economic differences amongst student bodies by institutional type. I, therefore, generate a data set that draws on institutional, census, and geospatial information to estimate the socio-economic background of students' home postal code. Using this data set, I compare the mean statistic and generalised entropy index of a range of individual and household socio-economic postal code indicators for student bodies by institutional type to descriptively analyse their socio-economic profile. I show student bodies at traditional universities and Unisa appear socio-economically similar and display higher socio-economic circumstances than that of student bodies at comprehensive universities, universities of technology and TVET colleges who appear socio-economically similar. Between 2008 and 2019, the mean socio-economic profile declined for all student bodies, whereas there was no uniform trend for whether socio-economic heterogeneity was increasing or decreasing over time by university type. Lastly, my findings suggest there is more evidence for horizontal stratification between particular universities (regardless of their institutional type) rather than between university types, or between universities and TVET colleges. 2023-03-02T07:53:05Z 2023-03-02T07:53:05Z 2022 2023-02-20T12:30:14Z Master Thesis Masters MCom http://hdl.handle.net/11427/37101 eng application/pdf School of Economics Faculty of Commerce |
| spellingShingle | Economics Culligan, Samantha Using Census, Institutional and Geospatial Data to Estimate the Socio-Economic Profile of Post-School Students by Institutional Type |
| thesis_degree_str | Master's |
| title | Using Census, Institutional and Geospatial Data to Estimate the Socio-Economic Profile of Post-School Students by Institutional Type |
| title_full | Using Census, Institutional and Geospatial Data to Estimate the Socio-Economic Profile of Post-School Students by Institutional Type |
| title_fullStr | Using Census, Institutional and Geospatial Data to Estimate the Socio-Economic Profile of Post-School Students by Institutional Type |
| title_full_unstemmed | Using Census, Institutional and Geospatial Data to Estimate the Socio-Economic Profile of Post-School Students by Institutional Type |
| title_short | Using Census, Institutional and Geospatial Data to Estimate the Socio-Economic Profile of Post-School Students by Institutional Type |
| title_sort | using census institutional and geospatial data to estimate the socio economic profile of post school students by institutional type |
| topic | Economics |
| url | http://hdl.handle.net/11427/37101 |
| work_keys_str_mv | AT culligansamantha usingcensusinstitutionalandgeospatialdatatoestimatethesocioeconomicprofileofpostschoolstudentsbyinstitutionaltype |