Journal of Applied Computing and Information Technology

ISSN 2230-4398, Volume 16, Issue 1, 2011-12

Incorporating the NACCQ publications:
Bulletin of Applied Computing and Information Technology, ISSN 1176-4120
Journal of Applied Computing and Information Technology, ISSN 1174-0175

Issue Home  Home  Authors  Reviewers  About 
Box Refereed Article A2:

Locating women in the New Zealand computing industry

Alison Hunter, PhD
Manukau Institute of Technology - Te Whare Takiura o Manukau, Manukau, New Zealand

Hunter, A. (2012). Locating women in the New Zealand computing industry. Journal of Applied Computing and Information Technology, 16(1). Retrieved September 26, 2017 from


It is well recognised that women are under-represented in computing occupations in many Western countries, but is the situation similar in New Zealand? This article presents a quantitative analysis of gendered employment patterns in New Zealand's computing industry. Findings from analysis of 2001 and 2006 census employment data demonstrate that women are now well represented in some newer computing occupations in New Zealand, but they remain significantly under-represented in traditional computing roles such as programming and systems analysis. Furthermore, New Zealand women in computing do not have pay parity with men. On some occasions during the early days of computing in New Zealand women participated more equally in number but they have always experienced pay discrimination.


women, computing, New Zealand, occupations, discrimination

1. Introduction

It is well recognised that women are under-represented in computing occupations in many Western countries. The proportion of women in computing roles in the USA has been stated as 26% to 29% (Bartol & Aspray, 2006; Zarrett et al., 2006; McKinney et al., 2008). In the UK, women hold approximately 15% of computing positions (Griffiths, Moore, & Richardson, 2007) and similar proportions were observed throughout the European Union (Panteli et al., 1999). In Australia the percentage of women in computing has steadily declined for around two decades (von Hellens & Nielsen, 2001), dropping to approximately 25% in 2001 (Byrne & Staehr, 2005).

The under-representation of women is particularly marked at the higher levels of computing work. Stockdale and Stoney (2007, p. 27) described a 'vertical gender segregation' which results in disproportionately low numbers of women in computing managerial positions and high numbers in lower level computing occupations in Australia. A similar glass ceiling for women in computing is reported in the UK (Griffiths, Moore, & Richardson, 2007; Knights, 2009; Panteli et al., 1999) and in the USA (Hemenway 1995; McKinney et al. 2008).

Claims that women are paid less than men holding the same positions in the computing industry are also common. For example, pay inequity for women in computing has been reported in the USA (Klawe, Whitney, & Simard, 2009; Hemenway, 1995), the UK (Griffiths, Moore, & Richardson, 2007; Knights, 2009; Tattersall, Keogh, & Richardson, 2007), and Australia (Byrne & Staehr, 2005; von Hellens & Nielsen, 2001).

The participation of women in computing education mirrors their employment situation. Charles and Bradley (2006) identified a predominance of men in computer science programmes in 21 countries, and similar gender imbalance was observed in the Netherlands (Rommes et al., 2007) and the Republic of Korea (Charles & Bradley, 2006). This disparity is worsening in some countries. For example, in the USA women received 20% of undergraduate computer science degrees in 1994 but only 17% in 2004 (Computing Research Association cited in Pham, 2007), and in Australia the percentage of women entering computing programmes has steadily declined since 1999 (Lewis, Lang, & McKay, 2007; Fisher, 2007).

Interestingly, these patterns are not found in all countries. Men and women participate roughly equally in computer science degrees in Malaysia (Othman & Latih, 2006), and women constitute at least half of university computing enrolments in some Mediterranean and Asian countries (Newmarch, Taylor-Steele, & Cumpston, 2000). Almost two fifths of female computing professionals in New South Wales, Australia, are non-English speaking women mainly from Asian countries (Alcorsco & Ho, 2006), matching the high number of women from Asian backgrounds studying towards computing degrees in Australia (von Hellens & Nielsen, 2001).

In New Zealand, the under-representation of women in computing has been a concern for some time. Studies into the gender inclusiveness of computing courses during the 1990s concluded that teaching and learning environments in tertiary institutions had the effect of excluding women (Ryba & Selby, 1995; Selby 1997a; Selby, 1997b; Selby, Ryba, & Young, 1998). Recent media headlines such as Women wanted in IT (Bland, 2007) and We want you, ICT Industry tells Girls (Hedquist, 2007) indicate that little has changed and suggest that New Zealand women in computing face similar barriers to women in other Western countries. 1

The primary contribution of this paper is to provide a detailed analysis of gender distribution within New Zealand's computing industry. A secondary contribution is to investigate claims of gendered income patterns within the sector. The analysis is based mainly on census data from 2001 and 2006, but some other earlier data sources are also considered. 2 The paper is divided into four sections: The first explains the instruments used by government to quantify employment data. The second presents two tables containing data relating to computing occupations over the period 2001 to 2006. The third section questions whether the current under-representation of women has been a consistent feature of the computing industry in New Zealand. Some contradictory reports regarding women's involvement in the early period of computing in New Zealand are discussed. The final section addresses in detail the issue of gendered pay patterns in the computing sector and investigates whether part-time work satisfactorily accounts for the apparent pay discrimination.

2. Data Sources

Finding precise employment data for the computing industry in New Zealand is a challenge, due to the growing diversity of roles and different statistical measures used by government. A distinction is made between technician and professional roles in computing in the New Zealand Standard Classification of Occupations 1999 (NZSCO), a schedule that categorises jobs for statistical purposes (Statistics New Zealand, 2001). The Department of Labour (2006, p.4) defined 'Computing Professionals' according to minor group 213 of the NZSCO schedule:

IT professionals perform analytical, conceptual and practical tasks which support the efficient and secure provision of information technology to government, commercial and industrial organisations, and individuals. Occupations in this group include: business and systems analysts, multimedia specialists, web developers, software engineers, database and systems administrators, network professionals, and support and test engineers. The majority of occupations in this group have a skill level which is commensurate with a bachelor degree or higher qualification.

A range of other computing occupations are classified as technical, and by implication these require less analytical thinking and lower level training. Most of these occupations are included in NZSCO minor group 312 'Computer Equipment Controllers'. This category includes jobs such as Computer Programmers, Computer Support Technicians, and Computer Operators. The Department of Labour (2006, p.12) defined these technical roles as follows:

These occupations cover technicians who assemble, install, maintain and repair computer hardware, software and related equipment; provide technical advice and support to users of computer software and hardware; and prepare programs to control data processing by computers.

This classification system is unsatisfactory as the terminology is out-dated and the classifications are unsuitable for the wide range of contemporary computing roles (for example, the terms Computer Equipment Controllers, Computer Operator, and Data Processing are no longer in common use). Further, it undermines the status of Computer Programmers and others who are likely to consider themselves professionals rather than technicians.

A preferable system, the ANZSCO (Australian and New Zealand Standard Classification of Occupations) schedule, more accurately reflects current occupations in the industry. ANZSCO classifies occupations according to skill level and specialisation, and groups them on the basis of similarities in these measures (Australian Bureau of Statistics, 2005). 3 Within this structure ANZSCO identifies approximately 34 ICT occupations (3 management, about 25 professional, 4 technical, 1 clerical, 1 sales). Statistics New Zealand has not yet committed entirely to ANZSCO classifications and uses the NZSCO classifications at times in order to retain comparative data (R. Haig, personal communication, October 30, 2007).

Locating accurate income data for computing work is also difficult. Statistics New Zealand provides two datasets: (1) Census data which allows for comparison of total personal income by occupation and gender (i.e. income from all sources, not just wages and salary) (Statistics New Zealand 2008), and (2) Income Survey data which itemises weekly income from wages, salary and other sources by gender, but not by occupation (Statistics New Zealand, 2006). Since the Income Survey data is clearly unsuitable for the purpose of this paper, census total personal income data have been used for the analyses. This appears to have been the approach used by Byrne and Staehr (2005) in their analysis of gendered pay rates in the Australian computing industry. While using total personal income rather than work-related earnings is not entirely satisfactory, data from Statistics New Zealand (2006) show that income from wages, salary, and self-employment constitute 93.6% of the average weekly income for people in paid employment ($762 out of $814). Further, there was very little difference between males and females in this regard (94.4% and 92.3% respectively). This justifies the use of total personal income in the analysis of gendered income patterns as outlined in this paper.

3. Data Analysis and Findings

3.1 Gender Analysis for 2001 and 2006 using NZSCO

Five occupations (NZSCO) were selected for a preliminary analysis of gender distribution in New Zealand's computing industry. The number employed, the gender proportions, and median income for these occupations in 2001 and 2006 are presented in Table 1.

Table 1. Number employed in two minor groups of computing occupations (NZSCO) in 2001 and 2006, with median income and gender distribution included

The data in Table 1 reveal several significant trends in employment and gender distribution in the computing industry over the period 2001 to 2006. Firstly, the total number of people employed in the five occupations increased by 26%, but this increase was not spread evenly across occupations. There was a 44% increase in the number employed in the 'professional' occupations, whereas the number employed in the two 'technical' occupations actually decreased by 29% (numbers in each 'professional' occupation increased, but decreased in each 'technical' occupation). Secondly, the overall increase was also not spread evenly across genders, with the overall proportion of females dropping from 29% to 23%. The proportion of females in the 'professional' occupations remained fairly stable over the period, but dropped noticeably in the 'technical' occupations. This suggests that when the number of people employed decreases, the decrease is more significant for females than males. In addition, males out-numbered females in all occupations except Computer Operator in 2001, but by 2006 all five occupations were dominated by males. The proportion of males increased for three of the five occupations over the period. In 2001 females were least represented amongst Computer Application Engineers and Computer Programmers, and this remained unchanged in 2006.

Further patterns indicative of a deteriorating situation for women are evident, especially when income is considered. For example, the two occupations with the highest proportion of females in 2001 (Systems Manager and Computer Operator) were also the occupations with the lowest median incomes, and this remained unchanged in 2006. A 5% increase in the number of female Systems Managers over the period 2001 to 2006 appears to be a positive sign for women, but is less so when income is considered. Systems Managers received the smallest increase in median income compared with the other four occupations (6.6% compared with 16.8%, 13.6%, 17.9%, and 21.4%). In comparison, Computer Operators, the occupation with the greatest decrease in female participation (13%), received the greatest increase in median income (21.4%). This suggests that increased female participation is linked with smaller increases in income, whereas increased male participation is associated with larger increases in income.

3.2 Gender Analysis for 2006 using ANZSCO

ANZSCO classification of occupational data from the 2006 Census allows a more detailed analysis of gender distribution within computing occupations. Data concerning the computing industry were extracted from the census dataset and are shown in Table 2.

Table 2. Number employed in computing occupations (ANZSCO) in 2006, with gender frequencies and proportions included

A number of patterns in the 2006 participation rates of women in the computing industry emerge in the data in Table 2. Although females occupied approximately 35% of all positions they were not evenly distributed throughout the different categories of occupations. Females were under-represented in four of the five categories: Managerial (22%), Professional (28%), Technician (29%), and Sales (23.5%). Conversely they were over-represented in lower status Clerical positions (86%). The zero number of female Chief Information Officers is concerning because it suggests that women are not actively participating in decision making at the strategic level of computing management.

The ANZSCO professional category identifies 28 occupations whereas NZSCO identifies only three (refer Table 1). The increased number of professional roles reflects the expansion of the industry, its growing diversity, and the increased specialisation of computing work. Although females occupy only 28% of professional occupations overall, there are some (usually newer) occupations in which females are either equally or overly-represented: Technical Writing, Training, Business Analysis, Database Administration, Graphic Design. However females remain significantly under-represented in the traditional computing roles of Systems Analysis and Programming in which the greatest numbers are employed - just as they were in 2001.

The data in Tables 1 and 2 confirm that women are substantially under-represented in many computing roles. Some computing occupations do have a more equal gender distribution, but the number of people employed in these roles is often fairly small. Graphic Design is the largest professional occupation employing a representative number of women. In addition, data in Table 1 raises the issue of pay parity and this is considered later in this paper.

4. Have Women Always Been Under-Represented?

The previous section highlighted the under-representation of women in computing work since 2001. Data from various other sources give an uncertain picture of the situation prior to this.

Some reports of early gatherings of computing workers during the 1960s and 1970s suggest that there were few women employed in the industry at that time. For example when the New Zealand Computer Society held its first formal meeting in 1961 all 12 of the people attending were men, and the first 50 applicants for membership over the following few months included only one woman (New Zealand Computer Society, 1961-1965). Similarly when a seminar on The Practical Applications of Data Communications in New Zealand was held in 1977 only 4 of the 116 attendees were women (New Zealand Computer Society, 1977). A more precise measure of the early employment situation for women in computing is provided by Jackson (1983) who revealed a gender imbalance in all except one of the occupations he studied in 1982. Table 3 presents this data.

Table 3. Percentage of women employed in computing occupations in 1982

When compared with data in Tables 1 and 2, two important trends are apparent. Firstly, the only occupation in which women were over-represented in 1982 was Data Entry, the least skilled occupation. A similar pattern exists today with women most highly represented in Data Entry Operator and Word Processing roles. Secondly, almost half of the Applications Programmers in 1982 were women - a noticeably larger proportion than those reported in Tables 1 and 2. This suggests that women may not always have been so severely under-represented during the 50-year history of New Zealand's computing industry.

Several writers have proposed that women were more prominent in the early years of the computing industry and that under-representation is a recent phenomenon. For example, Frances Allen noted this point on receiving the Turing Award (Association for Computing Machinery, 2007) and Kraft (1979) observed that many of the first Computer Programmers employed to work with the ENIAC computer were women, possibly, he suggested, because programming was considered low status work at that time. Light (1999) and Gürer (1995) similarly described the significant contributions of women in the pioneering days of computing and argued that this early involvement of women has been made invisible by the under-reporting of women's achievements. A review of data in Tables 2 and 3 suggests that in New Zealand the proportion of women Computer Programmers may have dropped as much as 35% during the period 1982 (46%) to 2006 (11.6%).

Trends in the proportion of women undertaking study for the computing industry add another perspective to this issue. The number of women earning degrees in Computer Science in the USA actually rose until 1985 but has declined since (Varma, Prasad, & Kapur, 2006). Data show a similar pattern in New Zealand. A report on the post-study experiences of the first students enrolled in the New Zealand Certificate in Data Processing course during the years 1967-1978 (126 students in total) showed that twice as many women enrolled in the programme than men (Offenberger, 1984). In comparison, data from the University of Auckland showed that during 1989 to 1996 the average percentage of women studying computing at first year was 26% (Selby, Ryba, & Young, 1998), and in the Department of Computer Science there was a steady decline in the proportion of women students from 23.8% in 1999 to 18% in 2005, despite departmental initiatives over that period designed to attract more female students (Hosking, 2005). These data suggest that prior to the early 1980s some women were actively seeking careers in the computing industry in New Zealand, particularly in programming roles. However after an initial enthusiastic foray into IT work, fewer women subsequently chose to pursue careers in computing, particularly in traditional computing roles such as programming.

5. Further Analysis - Gender and Income

Table 1 showed that women were more highly represented in the two lowest paid computing occupations. Since these occupations also have the lowest skill requirement it is not clear that gender impacted on the income levels for these occupations. However Table 1 also showed that increased female participation in an occupation was accompanied by the smallest increase in median income. This suggests there might be a discriminatory gender factor impacting on the incomes of women in computing.

There is some evidence of historical gender related pay inequity in New Zealand's computing industry. Beardon (1985, p. 114) reported that in the late 1970s the average male salary in computing was $10,600, whereas the average female salary was only $7,700. Further, men routinely received on average 5% more pay than women for the same work and also received more valuable perks. Even the few men employed as Data Entry Operators received on average 20% more pay than women for identical work.

In order to investigate whether similar pay inequities exist today, five computing occupations were selected for analysis, and income data for these occupations was extracted from the 2006 Census of Population and Dwellings. The occupations selected and the reason for their selection is explained in Table 4.

Table 4. Computing occupations selected for analysis of gender related pay inequity

The 2006 Census reports total personal income levels in increments of $5,000. In order to simplify analysis income bands were aggregated into six larger bands. Table 5 presents the number of males and females whose total personal incomes fit within the aggregated bands for each occupation. The total number in each occupation in Table 5 is slightly less than the totals shown in Table 2 due to the fact that some census respondents did not declare their income.

Table 5. Total personal income by gender for five computing occupations (numbers of employees and proportions for each gender)

These data suggest that a greater proportion of females receive lower incomes than men for each of the five occupations. For example the two professional occupations with the greatest proportion of females, Graphic Designer and Database Administrator, both have a much higher proportion of women receiving income under $40,000 than men (63% and 67% female, 48% and 24% male). This apparent inconsistency can also be seen in Figures 1 and 2 in which a total personal income between $30,001 and $40,000 is received by a greater proportion of females in comparison to a total personal income between $70,001 and $100,000 received by a greater proportion of males, for each of the occupations.

Figure 1.

Figure 2.

Two statistical tests were used to investigate this apparent pay discrimination. A chi-square test showed a significant difference in total personal income between males and females for each of the five occupations. The Kruskal-Wallis test applied to consider the ordinal ranking of categories (Conover, 1980) showed that males receive a higher total personal income than females. Table 6 summarises these results.

Table 6. Summary of statistical tests used to investigate income disparity in five occupations

These findings provide some evidence that women are paid less than men in similar occupations in the computing industry in New Zealand. However it is possible that there are factors other than gender which impact on the income levels of women. For example, if income is related to years of experience then it is possible that women who have interrupted their careers to raise a family will earn less than their male counterparts. Data that would allow investigation of this issue are not readily available. Another possibility is that women are more likely than men to be employed part-time and will therefore receive less income. Table 7 shows the gender proportions for full-time and part-time work for each of the occupations under investigation.

Table 7. Proportion of males and females working full-time or part-time

For all of the occupations there are a greater proportion of women than men working part-time and this difference is particularly marked for the three occupations with greatest female participation (Graphic Designer, Database Administrator, Data Entry Operator).

To determine whether the part-time factor adequately explains the disparity in income between men and women, the two occupations with the least gender difference in part-time employment proportion (Systems Analyst) and the greatest difference (Database Administrator) were further investigated. Two different scenarios were investigated:

The adjusted data for each scenario is shown in Table 8.

Table 8. Total personal income by gender for five computing occupations (adjusted numbers of employees)

When the same statistical tests used previously were performed on the adjusted data a significant difference at the 0.1% level was again found for both occupations for each of the scenarios, as seen in Table 9. This suggests that a difference in the full-time/part-time employment of men and women does not adequately explain the gender differences in total personal income.

Table 9. Summary of statistical tests used to investigate income disparity using adjusted data

This preliminary analysis points to the presence of gender based pay discrimination in the computing sector in New Zealand. The findings are consistent with the similar reports from other countries noted earlier.

6. Discussion - Why the Lack of Women in Computing is Important

The current lack of women in computing in New Zealand (and elsewhere) is an important matter. The under-representation of women in the industry means that women are not proportionately involved in technological developments and consequently it is likely that women's interests are not considered when new technologies are designed. Justice requires that women are involved in 'shaping the world' (Margolis & Fisher, 2002; Wajcman, 2007). Income discrimination and any inequity of employment opportunity for women are further examples of injustice (Panteli, Stack, & Ramsay, 1999).

More women in computing would also bring greater diversity to teams working in the industry and, as argued elsewhere, would likely improve communication within those teams, thereby improving the current inefficiency of many such teams (Hunter, 2012). More women taking up computing careers would also help address the current skills shortages which are negatively affecting the computing industries of many countries, including New Zealand (Hunter, 2012).

For the reasons briefly outlined above, steps need to be taken to encourage more women to participate in the computing industry in New Zealand. For example, educational institutions need to prioritise increased female participation in computing courses, and research is required to better understand girls' career choices and lack of interest in computing careers. Within the industry a women's support and advocacy group is needed to replace the now defunct Women in Technology organisation, and men have a responsibility to examine their role in perpetuating a male culture in the workplace. Professional bodies such as the New Zealand Computer Society can also take positive steps to attract more women into the industry, for example by upholding female role models. Current successful initiatives such as the annual Programming Challenge for Girls need to be encouraged and widely reported.

7. Conclusion

The position of women in the early period of New Zealand's computing industry is unclear, with conflicting reports of female participation in computing careers and education. The initial interest of some women appears to have declined since the 1980s. However the analyses presented in this paper confirm that the contemporary computing industry in New Zealand is predominantly a male domain. The proportion of women employed in many computing occupations is decreasing, despite recent efforts to attract more women into the industry. In addition, the proportion of women studying towards computing careers is also dropping. Five professional computing occupations are more attractive to women than others - Technical Writer, ICT Trainer, Graphic Designer, ICT Business Analyst, and Database Administrator. It seems there are some powerful factors affecting the choices women make regarding careers and education in computing, leading to small numbers of women in New Zealand's computing industry. Data presented in this paper also provides some evidence of pay discrimination within the industry despite the government's commitment to equal pay for equal work since 1961 and equal pay legislation enacted in 1972. Further data is required to give greater clarity about this issue.

Women today are succeeding at higher levels of education and are participating in the paid workforce to a greater extent than at any other time in history. This, plus numerous equal opportunity initiatives and 'girls can do anything' campaigns, could have been expected to produce a climate in which women would flourish in a relatively new field such as the IT industry. That this has not happened suggests a new approach is needed to address gender inequities in the sector. More women in computing would help boost productivity in the industry and bring benefit to New Zealand's economy.


1 IT (Information Technology) and ICT (Information and Communication Technology) are alternative terms for 'Computing'.

2 The census scheduled for March 2011 was cancelled due to the devastating earthquakes which occurred in Christchurch in February 2011.

3 Smaller groups are aggregated into progressively larger groups, so that each occupation fits within one of eight major groups.


Alcorsco, C., & Ho, C. (2006). Migrant women and the Australian information, communications and technology sector - A special case? Labour & Industry, 16(3), 109-131.

Association for Computing Machinery. (2007). Fran Allen interview. Retrieved from

Australian Bureau of Statistics. (2005). Information paper: ANZSCO - Australian and New Zealand standard classification of occupations 2005. Australian Bureau of Statistics. Retrieved from

Bartol, K., & Aspray,W. (2006). The transition of women from the academic world to the IT workplace: A review of the relevant research. In J. M. Cohoon & W. Aspray (Eds.), Women and information technology: Research on underrepresentation. (pp. 377-420). Cambridge, MA: MIT Press.

Beardon, C. (1985). Computer culture: The information revolution in New Zealand. Auckland, New Zealand: Reed Methuen Publishers Ltd.

Bland, V. (2007, April 4). Women wanted in IT. The New Zealand Herald, p. E22.

Byrne, G., & Staehr, L. (2005). Women in the Australian IT industry: Where are we now? Australasian Journal of Information Systems, 13(1), 8-18.

Charles, M., & Bradley, K. (2006). A matter of degrees: Female underrepresentation in computer science programs cross-nationally. In J. M. Cohoon & W. Aspray (Eds.), Women and information technology: Research on underrepresentation. (pp. 183-204). Cambridge, MA: MIT Press.

Conover, W. J. (1980). Practical nonparametric statistics (2nd ed.). New York: John Wiley & Sons.

Department of Labour. (2006). Information technology professional: Occupational skill shortage assessment. Retrieved from

Department of Labour. (2007a). Labour market information: Occupational indicators tool (includes census data 1991, 1996, 2001). Retrieved from

Department of Labour. (2007b). Labour market information: Occupational indicators tool (includes census data 1996, 2001, 2006). Retrieved from

Fisher, J. (2007). Australian women in information technology. Australasian Journal of Information Systems, 15(1), 5-7.

Griffiths, M., Moore, K., & Richardson, H. (2007). Celebrating heterogeneity? A survey of female ICT professionals in England. Information, Communication & Society, 10(3), 338-357.

Gürer, D. (1995). Pioneering women in computer science. Communications of the ACM, 38(1), 45-54.

Hedquist, U. (2007). We want you, ICT industry tells girls: Women join forces to promote ICT careers. Retrieved from

Hemenway, K. (1995). Human nature and the glass ceiling in industry. Communications of the ACM, 38(1), 55-61.

Hosking, J. (2005). Departmental annual reports on academic & research matters - Computer science. Auckland, New Zealand: The University of Auckland.

Hunter, A. (2012). The professionalisation of computing work in New Zealand, 1960 to 2010: A feminist analysis. Doctoral thesis, University of Auckland, Auckland, New Zealand.

Jackson, I. (1983). Computers in New Zealand: People, education and training. Dunedin, New Zealand: The Vocational Training Council and the University of Auckland.

Klawe, M., Whitney, T., & Simard, C. (2009). Women in computing - Take 2. Communications of the ACM, 52(2), 68-76.

Knights, M. (2009). Analysis: Women in IT still hit glass ceiling. Retrieved from

Kraft, P. (1979). The routinizing of computer programming. Sociology of Work and Occupations, 6(2), 139-155.

Lewis, S., Lang, C. & McKay, J. (2007). An inconvenient truth: The invisibility of women in ICT. Australasian Journal of Information Systems, 15(1), 59-76.

Light, J. (1999). When computers were women. Technology and Culture, 40(3), 455-483.

McKinney, V., Wilson, D., Brooks, N., O'Leary-Kelly, A., & Hardgrave, B. (2008). Women and men in the IT profession. Communications of the ACM, 51(2), 81-84.

Margolis, J., & Fisher, A. (2002). Unlocking the clubhouse: Women in computing. Cambridge, MA: The MIT Press.

New Zealand Computer Society. (1961-1965). Minutes of meetings. In Alexander Turnbull Library, New Zealand Computer Society Collection qMS-1462. Wellington, New Zealand.

New Zealand Computer Society. (1977). Proceedings of a seminar organised by the New Zealand Computer Society in conjunction with the University of Otago. Paper presented to Practical Applications of Data Communications in New Zealand, University of Otago, Dunedin, New Zealand.

Newmarch, E., Taylor-Steele, S., & Cumpston, A. (2000). Women in IT: What are the barriers? In Network of Women in Further Education, Showcase of Strategies for Women in Information Technology Conference. Sydney, Department of Education, Training and Youth Affairs (DETYA).

Offenberger, H. (1984). Training for a new technology: A survey of electronic data processing full-time students. Wellington, New Zealand: N.Z. Vocational Training Council.

Othman, M., & Latih, R. (2006). Women in computer science: No shortage here! Communications of the ACM, 49(3), 111-114.

Panteli, A., Stack, J., Atkinson, M., & Ramsay, H. (1999). The status of women in the UK IT industry: An empirical study. European Journal of Information Systems, 8, 170-182.

Panteli, A., Stack, J., & Ramsay, H. (1999). Gender and professional ethics in the IT industry. Journal of Business Ethics, 22, 51-61.

Pham, A. (2007). Top computer award breaks gender barrier after 40 years. Retrieved from

Rommes, E., Overbeek, G., Scholte, R., Engels, R., & de Kemp, R. (2007). "I'm not interested in computers": Gender-based occupational choices of adolescents. Information, Communication & Society, 10(3), 299-319.

Ryba, K., & Selby, L. (1995). A study of tertiary level information technology courses: How gender inclusive is the curriculum? Wellington, New Zealand: Ministry of Education Research and Statistics Division.

Selby, L. (1997a). A critical analysis of factors affecting the participation of women in tertiary level Computer Science and Information Technology courses. Doctoral thesis abstract, Curtin University of Technology, Perth, Australia

Selby, L. (1997b). Increasing the participation of women in tertiary level computing courses: What works and why? Retrieved January 31, 2012, from

Selby, L., Ryba, K., & Young, A. (1998). Women in computing: What does the data show? Journal of Applied Computing and Information Technology, 2(1), 74-81.

Statistics New Zealand. (2001). New Zealand standard classification of occupations 1999 (Catalogue No. 19.004.0099): Wellington, New Zealand: Statistics New Zealand.

Statistics New Zealand. (2006). New Zealand income survey 2006. Retrieved from

Statistics New Zealand. (2008). 2006 census of population and dwellings: Social sciences data package - census data modules (Module 6) Wellington, New Zealand: Statistics New Zealand.

Stockdale, R., & Stoney, S. (2007). Generating a gender balance: Making introductory information systems courses a positive experience. Australasian Journal of Information Systems, 15(1), 25-39.

Tattersall, A., Keogh C., & Richardson, H. (2007). The gender pay gap in the ICT industry. Retrieved from

Varma, R., Prasad, A., & Kapur, D. (2006). Confronting the "socialization" barrier: Cross-ethnic differences in undergraduate women's preference for IT education. In J. M. Cohoon & W. Aspray (Eds.), Women and information technology: Research on underrepresentation. (pp. 301-322). Cambridge, MA: MIT Press.

von Hellens, L., & Nielsen, S. (2001). Australian women in IT. Communications of the ACM, 44(7), 46-52.

Wajcman, J. (2007). From women and technology to gendered technoscience. Information, Communication & Society, 10(3), 287-298.

Zarrett, N., Malanchuk, O., Davis-Kean, P., & Eccles, J. (2006). Examining the gender gap in IT by race: Young adults' decisions to pursue an IT career. In J. M. Cohoon & W. Aspray (Eds.), Women and information technology: Research on underrepresentation. (pp. 55-88). Cambridge, MA: MIT Press.