Monitoring gender remuneration inequalities in academia using biplots
Gender remuneration inequalities at universities have been studied in various parts of the world. In South Africa, the responsibility largely rests with individual higher education institutions to establish levels of pay for male and female academic staff members. The multidimensional character of t...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Operations Research Society of South Africa (ORSSA)
2008-06-01
|
Series: | ORiON |
Online Access: | http://orion.journals.ac.za/pub/article/view/59 |
id |
doaj-a0d0c8072538408f8e282dc7639a3528 |
---|---|
record_format |
Article |
spelling |
doaj-a0d0c8072538408f8e282dc7639a35282020-11-24T22:20:59ZengOperations Research Society of South Africa (ORSSA)ORiON2224-00042008-06-0124110.5784/24-1-5959Monitoring gender remuneration inequalities in academia using biplotsIS WaltersNJ le RouxGender remuneration inequalities at universities have been studied in various parts of the world. In South Africa, the responsibility largely rests with individual higher education institutions to establish levels of pay for male and female academic staff members. The multidimensional character of the gender wage gap includes gender differentials in research output, age, academic rank and qualifications. The aim in this paper is to demonstrate the use of modern biplot methodology for describing and monitoring changes in the gender remuneration gap over time. A biplot is considered as a multivariate extension of an ordinary scatterplot. Our case study includes the permanent fulltime academic staff at Stellenbosch University for the period 2002 to 2005. We constructed canonical variate analysis (CVA) biplots with 90% alpha bags for the five-dimensional data collected for males and females in 2002 and 2005 aggregated over faculties as well as for each faculty separately. The biplots illustrate, for our case study, that rank, age, research output and qualifications are related to remuneration. The CVA biplots show narrowing, widening and constant gender remuneration gaps in different faculties.http://orion.journals.ac.za/pub/article/view/59 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
IS Walters NJ le Roux |
spellingShingle |
IS Walters NJ le Roux Monitoring gender remuneration inequalities in academia using biplots ORiON |
author_facet |
IS Walters NJ le Roux |
author_sort |
IS Walters |
title |
Monitoring gender remuneration inequalities in academia using biplots |
title_short |
Monitoring gender remuneration inequalities in academia using biplots |
title_full |
Monitoring gender remuneration inequalities in academia using biplots |
title_fullStr |
Monitoring gender remuneration inequalities in academia using biplots |
title_full_unstemmed |
Monitoring gender remuneration inequalities in academia using biplots |
title_sort |
monitoring gender remuneration inequalities in academia using biplots |
publisher |
Operations Research Society of South Africa (ORSSA) |
series |
ORiON |
issn |
2224-0004 |
publishDate |
2008-06-01 |
description |
Gender remuneration inequalities at universities have been studied in various parts of the world. In South Africa, the responsibility largely rests with individual higher education institutions to establish levels of pay for male and female academic staff members. The multidimensional character of the gender wage gap includes gender differentials in research output, age, academic rank and qualifications. The aim in this paper is to demonstrate the use of modern biplot methodology for describing and monitoring changes in the gender remuneration gap over time. A biplot is considered as a multivariate extension of an ordinary scatterplot. Our case study includes the permanent fulltime academic staff at Stellenbosch University for the period 2002 to 2005. We constructed canonical variate analysis (CVA) biplots with 90% alpha bags for the five-dimensional data collected for males and females in 2002 and 2005 aggregated over faculties as well as for each faculty separately. The biplots illustrate, for our case study, that rank, age, research output and qualifications are related to remuneration. The CVA biplots show narrowing, widening and constant gender remuneration gaps in different faculties. |
url |
http://orion.journals.ac.za/pub/article/view/59 |
work_keys_str_mv |
AT iswalters monitoringgenderremunerationinequalitiesinacademiausingbiplots AT njleroux monitoringgenderremunerationinequalitiesinacademiausingbiplots |
_version_ |
1725772909182451712 |