Gender Inequality in the Workplace: A Study on Salaries and Recruitment

Research 1
Name
Tutor
Institution
Date

Research 2
1.0 Introduction
Gender inequality has been a hot topic in the recent decades. Males and females have been said to be
treated unfairly in different quotas. It is moral to treat people equally and judge them according to their
abilities and not gender, race, region or even color. Despite the extent of civilization and education, the
former have not been able to eliminate this archaic and backward practice among some people. Various
researchers have found that the female gender has been the greatest victim of this vice (McKinsey,
2010). It has been found that organizations that have employed the female gender in top management
positions have always shown success in their progress than those organizations that have purely males
in the top management (McKinsey, 2010). The organizations with male managers only have been found
to be having not only financial difficulties but also social problems.
A research conducted by Institute of gender and research at Stanford University found that male
workers took credit away from female workers who had been found to be doing better in their areas of
jurisdictions. Male counterparts would attribute this to luck and not their individual efforts (Major &
McFarlin, 2012). In another dimension, some hiring managers have been found to paying attention to
males than females when it comes to employment. They have the perception that male workers were
more talented especially I technical assignments than females (Roxana, 2013).
It has not been clear why the problem of gender discrimination is still far from ending. There are many
questions than answers as to why discrimination in terms of gender especially against females is still
being practiced in some societies. Researches have been done but there still exist gaps. It is for this
region that this research sought to unravel the reasons behind the discrimination and whether indeed
females have suffered discrimination in work places in terms of salaries and recruitment. To answer the
research question two data sets were used. One dataset containing a sample of 1000 workers was
sourced from Australian taxation office. The data contained variables such as salaries and number of
female and males in various occupations. Another data was collected by the research to aid the study
answer the research question adequately. The data was collected through the use of questionnaires.
The disadvantage of using questionnaire in data collection was found to be lack of honesty in some
responses.

Research 3
2.0 Summary statistics
a) Gender Occupation cross-tabulation
Occupation Gender
Male Female Grand
Total
Clerical & Administrative worker 16 80 96
Community & Personal service workers 27 54 81
Consultants & Apprentices 36 45 81
Laborers 51 24 75
Machinery operators & Drivers 50 2 52
Managers 55 33 88
Not specified 94 83 177
Professionals 74 116 190
Sales workers 16 45 61
Technicians & Trade workers 85 14 99
Grand Total 504 496 1000
Table 1
Graphical representation of Occupation distribution by gender
Clerical & Administrative worker
Community & Personal service workers
Consultants & Apprentices
Labourers
Machinery operators & Drivers
Managers
Not specified
Professionals
Sales workers
Tecnicians & Tradeworkers
0
40
80
120
80
54 45
24
2
33
83
116
45
14
gender and occupation graph
Male
Female
Figure 1

Research 4
In order for the research to establish whether there were more males and females or vice versa, the
research decided to analyze the distribution of both gender by occupation. This analysis sought to find
the proportion of males and females in each profession to establish whether there are glaring
disparities. The graphical analysis above shows that out of the 10 professions, the proportion of males
was higher than that of females in 5 of them. The proportion of females was also high in the remaining 5
professions. For example the proportion of females was high in clerical and administrative jobs. They
were 80 while the males were 16. Their proportion was also high in community and personal service
jobs. Their number was 54 while the males were 27. The number of females was 45 and females were
16 among consultants and apprentices. Lastly, the number of females was also high among sales and
professional workers. Their number was 116 and 45 respectively while that of their counterparts was 74
and 16 respectively. The occupations where the males were the majority were among laborers, machine
operators, technicians and managers. Their number was 51, 50, 85 and 55 respectively. Their
counterparts in those professions were 24,2,33, 83 and 14 respectively.
b) Scatterplot of Salary and gender.
0.8 1 1.2 1.4 1.6 1.8 2 2.2
0
50000
100000
150000
200000
250000
300000
350000
f(x) = 21149.6140552995 x + 13836.7004608295
R² = 0.05029249767553
Salary and gender amount
Gender
Salary-wage amount
Figure 2
c. Correlation
Table of relationship results
gender Salary/
wage
gender 1
Salary/wage 0.22425988
9
1
Table 2
In order to establish whether there is a relationship between gender and salary, the research employed
the Pearson correlation test to determine the same. The Pearson correlation coefficient runs from 0 to 1
where 1 can either be positive or negative. A value of zero indicates no relationship between variables.