Imelda Connolly, National College of Industrial Relations, Sandford Road, Dublin 6.
E-mail: imeldaconnolly@tinet.ie
Paper presented at the conference: “Ireland, Europe and the Global ‘Information Society’: A Conference for Social Scientists” Dublin, April 24-25, 1997.
A theoretical three step mechanism to explain genderisation of different activities is presented and explained. This mechanism is then applied to new technologies and the Internet in particular. The Internet is shown to be highly genderised. Some new experimental results are presented. If the postulated theory proves to be robust across a range of further tests and analyses, it should enhance the effectiveness of efforts to influence the processes and degrees of genderisation in new technologies.
A theoretical framework for gender differentiation in new technology and the Internet.
A theory for the genderisation of activities..............................................................................2
Step 2: Classification................................................................................3
Step 3: Maintenance.................................................................................3
New technologies as a test of this theory.................................................................................4
Applying this theory of genderisation mechanisms to the Internet..............................................5
Step 2 Classification.................................................................................7
Step 3 Maintenance..................................................................................8
Conclusion..............................................................................................................................9
Appendix 1 Risk-taking experiment.........................................................................................10
Appendix 2 Anlaysis of gender bias in magazines.....................................................................16
Appendix 3 student first year enrolment figures.........................................................................17
Gender identification of texts....................................................................................................18
References...............................................................................................................................14
All societies in the world perpetuate social differences between the genders with customs, clothes, work-roles and pastimes which differentiate and define what constitutes a ‘woman’s world’ and a ‘man’s world’. These customs and differentiated sex roles vary from place to place and so for example, 88% of medical graduates in Denmark are female while females represent only 44% of medical graduates in Italy, (Eurostat 1995), bricklayers are predominantly women in the former Soviet Union yet in Ireland you will only find male bricklayers. Sex roles also change over time so that for instance, in the early 1900’s most teachers were male and now women dominate in the teaching profession.
When we look at stereotypical sex roles it is relatively easy to understand the development of some persistent and traditional gender differences in areas such as child care and warfare. Females are biologically equipped to undertake the care and nursing of their young babies and children and it is easy to see that once this role has been established as a ‘female role’, gender differentiation is likely to occur within the area of child care. Results from a wide range of research by for example, Maccoby and Jacklin (1979) have established that, in general, males are more aggressive than females. This tendency towards aggressiveness, combined with the greater physical strength of males over females and the vulnerability of pregnant and lactating females, helps to explain why males in all societies predominately engage in warfare. Warfare is understood to be part of a ‘man’s world’. Once a successful pattern of activity has been established, it is understandable that this pattern could be reproduced from generation to generation and from society to society.
Gender equality agendas have helped to raise public awareness of previously unconscious levels of acceptance for patriarchal values, powers and status within our society. Sexual discrimination legislation has been introduced to correct gender discriminating policies within the legal, political, and employment areas, while efforts continue to introduce more ‘politically correct’ language in publications and the media generally, so that an ethos of gender equality is established. These developments leave us with the impression that eventually by a slow process of elimination, all areas of sexual discrimination will disappear from our society and men and women will be equal academically, socially, legally, financially and politically. But we have to ask the question, will this happen?
In order to understand more fully the genderising processes which may occur within an activity or occupation, it is necessary to examine the processes which lead to an occupation being dominated by one gender. To date, explanations which attempt to account for the different gender ratios within occupations, activities and new technologies, have lacked a theoretical framework. While researchers on the Internet have, for instance, examined the ratios and contents of male and female postings to newsgroups and mailing lists, these facts of themselves do not explain fully why females are underrepresented on newsgroups or why they fail to access the Internet in the first place. I am proposing a three-step mechanism which I believe helps to explain the processes by which some activities, occupations and new technologies in particular, become gendered.
Step 1 Initialisation.
For an activity to become gendered there must be some mechanism or mechanisms which initially cause one gender or the other to predominate. This initial step could be purely random. For example if a new activity initially involved a small number of people, say perhaps, five people, four of one gender and one of the other, then this accidental ratio may cause the activity to be associated with one gender rather than the other. Alternatively, the initialisation step may be complex and arise from a long socialization process. For instance, the new activity may arise in an area which is already dominated by one gender. This is illustrated in Nigeria where females are the main agricultural workers and food producers and this has led to female domination of the sale of goods in the Nigerian market-place. Another example can be seen in the fact that although men predominate in the computer field, women’s association with typing has led to their cross-over to the field of word-processing, which is currently dominated by women.
Step 2 Classification.
Once an activity attracts more members of one gender than the other, the activity may become classified as being a ‘feminine’ or a ‘masculine’ activity. Alternatively the activity may be labelled masculine or feminine for stereotypical socialisation reasons. For example, technologies such as food processors, microwave cookers, knitting machines and washing machines are labelled ‘feminine’ due to their association with domestic work, which is stereotyped as ‘female work’.
Step 3. Maintenance.
Once an activity has become labelled, a mechanism or mechanisms are required to maintain or enforce the stereotyping.
For example, the attractiveness of an occupation varies according to the proportion of males and females employed. Males are attracted to already male dominated occupations and as Madeline Heilman, (1979) found out, they express interest in occupations which are predicted to have future female participation at the 10% to 30% level. They are not, however, interested in careers which have a predicted 50% or more participation by females. Females tend to avoid occupations which are already male dominated, but are more attracted to these jobs when the predicted future female participation increases above the token level.
The status of an occupation varies according to the proportion of males and females employed. When the majority of workers in a field are female, the apparent ‘professionalism’ and image of that occupation changes, and at this stage males are often actively recruited to redress the balance and improve the ‘status image’ of the job. However, as John Touhey (1974a, 1974b) has shown, female dominated occupations are less attractive to both males and females.
When members of one gender attempt to enter a field dominated by the other gender, impeding or promoting mechanisms may operate. An impeding mechanism appears to operate when females move into a ‘male designated’ occupation such as engineering, business, or computer science. They tend to hit what Hymowitz & Schellhardt (1986) termed the ‘glass ceiling’, an invisible barrier which blocks them from obtaining the top positions. On the other hand, a promoting mechanism seems to operate when males enter a ‘female designated’ occupation such as nursing, primary level teaching or librarianship. They tend to experience what Christine Williams (1995) describes as the ‘glass escalator effect’. They are moved along an invisible ‘up’ escalator to higher pay and status than their female colleagues.
This balancing act between male or female domination of an occupation and the subsequent shifting of status within occupations, acts as a filter controlling access to these occupations. If the mechanism is not too rigid, it is possible for the gender identification to drift with time. If we look at a technology such as the telephone, we find that originally the telephone was marketed as a ‘male’ technology to be used for business purposes. At first; ‘private calls’ were charged at a higher rate than ‘business calls’: Spender, D. (1995) Over time however, women increased their social use of the phone and so extended the intended use of this technology. As many studies have shown, females now use the residential phone more than men: Martin, M. (1991)
What patterns of gender differentiation occur when a new activity is invented which is a novel experience for everyone in that society? In our present-day society this is occurring on a daily basis. More inventions have been made within the last two decades than in all the years since the beginning of civilisation. New technologies are developing and ‘mutating’ exponentially, and these technologies result in rapidly changing work patterns and life styles. It is estimated that the future jobs of 90% of the children currently in pre-school have not been invented yet. (Women And Work 1996)
New technologies may appear to arrive in our society ‘baggageless’ and unencumbered by traditional attitudes and societal gender prohibitions. These technologies develop within our modern-day society, which, as previously mentioned, gives great lip-service to the principle of equal rights for males and females, thereby leading us to expect non-gender differentiated patterns within new technology usage. It is very surprising then when we discover that this is not the case.
Let us consider for example the Internet. This is a new technology which was invented in the late 1960’s and which has become readily available to the public within the last 5 years. The best ‘guesstimates’ indicate that there are approximately 42 million Internet users, although these participation rates are still low in relation to overall populations, with for example, only 10% of the US population and 1% of the Irish population on-line. (NBC 1997, Kiberd, D. 1997) Research indicates that males presently dominate the Internet and females represent between 10-30% of the Internet population. GVU (October 1996) Gender differentiation has therefore occurred within this area of technology and established that the Internet is part of ‘a man’s world’.
Nevertheless, over time the proportion of female Internet users has increased. Early surveys of Internet users indicated female participation at 10%, while the most recent surveys show that particularly in the United States where college access to the Internet is standard, females represent about 30% of users. Within Europe however, where Internet usage is still in its early stages, females represent just 15% of users. So we can see that gradually the percentage of female participation on the Internet can be expected to rise, although only time will tell how gendered the activity will remain.
Step 1 Initialisation.
The development of the computer and the Internet arose from a marriage between military needs and scientific academic interests. Early computers were designed to carry out military calculations during World War Two, while the Internet was designed during the Cold War to carry information successfully from one computer to another in the event of a nuclear attack. Military personnel and scientific and engineering departments of universities are male dominated and so their associated connection with both computers and the Internet appears to have contributed to a male dominance of these technologies.
Another factor which may be responsible for male dominance of the Internet is indicated in the results of the 1995 Motorola Report. This Report claims that males are more likely to see themselves as ‘a risk-taker’, ‘innovator’, ‘leader’, ‘ideas person’, and a person who is ‘familiar with IT’ (Information Technology). Females on the other hand were more likely to see themselves as a ‘follower’, as a ‘cautious person’ and a person who is ‘scared of new technology’.
I devised an experiment to test whether or not, in practice, males take more risks than females. The results of the experiment are shown in Appendix 1 (Figures 1-3, Table
1). Figure 3 shows that males on average took greater ‘perceived’ risks than females. These results might be explained in the following way:
Society appears to adopt a protective attitude towards females which leads to a restrictive style of child-rearing, education, life-style and employment opportunities for females. The ‘hidden curriculum’ of gender stereotyping and segregation which permeates the educational system often leads to gender differentiated subjects, career choices and expectations for success. Femininity as a stereotypical ideal is not portrayed as compatible with technological competence, or with doing dangerous or risky things. As a result of these trends, it appears that females, in general, are less adventurous and less likely to take risks than males in our society and are consequently cautious in approaching new technologies. When technologies have become more established within a society, as in the case of the car, women are then more likely to participate.
Males on the other hand are reared in a less restrictive manner than females, they are allowed more personal freedom even from a very early age, and are expected to be out-going, adventurous and risk-takers. While this approach to life results in greater levels of deaths and accidents among males, it also contributes to the situation where males are early adopters of new and unproven machines and technologies. The process of socialisation which males and females in our society experience therefore affects the initialisation process of a new technology. Females are more likely to withdraw from ‘scary’ new technologies such as the Internet until they are well established, which therefore appears to have facilitated a male domination of this new Internet technology.
Step 2 Classification
Survey after survey confirms that males dominate the Internet. VNU (1996) GVU (January 1994, October 1994, April 1995, October 1995, April 1996, October 1996) However, within the Internet and IT industry, many believe that this fact is accidental and that the Internet is not a gendered technology. In fact many go so far as to believe that the Internet is a totally democratic technology and communication tool, without any ‘social context information’ which could indicate status, power or gender. Kiesler et al. (1984) As one user wrote:
“You, for example, have no way of knowing if I am a janitor or a university president or an illegal alien – we can simply communicate on the basis of our ideas, not on any not on any preconceived notions of what should be expected (or not expected) from one another.” Herring, S. C. (1993)
The apparent ‘democratic neutrality’ of the Internet is however largely a myth since VNU (1996 ) and GVU (April 1995, October 1995, April 1996, October 1996 ) surveys confirm that the Internet is monopolised by upwardly mobile educated white males, and is not being significantly accessed by females or lower socio-economic groups.
There are a number of factors which lead me to conclude that the Internet has been gendered and has been classified as a ‘male-interest’ technology.
(1) Internet magazines are generally displayed on newsagent shelves beside specifically labelled ‘male-interest’ magazines such as ‘Esquire’, and ‘GQ’.
(2) The media, in general, assume that the Internet user is male. Newspaper articles, Radio and TV programmes and advertising generally feature males and present male experts within the field. To test out the gender bias of Internet magazines I carried out a survey which analysed back-issues of the Internet magazines, ‘Wired’ and ‘.net’, the male-interest magazines, ‘GQ’ and ‘Esquire’ and the female-interest magazines, ‘She’ and ‘Cosmopolitan’. The results of this analysis are provided in Appendix 2. I found that the gender bias of magazines can be determined from the relative percentages of male, female and child models used in magazines. If you compare the profile of ‘Wired’ and ‘.net’ magazines with the ‘female interest’ magazines, it can be clearly seen that the Internet magazines are marketed and therefore labelled as a ‘male interest’, which subsequently limits the attractiveness of the Internet for potential female Internet users.
(3) Private communications with Nora Brophy (DCU) indicate that the title of a course in IT can profoundly affect the gender representation within that course. This is best illustrated by two computer courses offered by DCU. Both of these courses involve a similar level of computational skills. One is entitled ‘Computer Applications’ and males represent the majority of students in this course. The other computer course is called ‘Computational Linguistics’ and in this case females form the majority of the students. See Appendix 3 for information on the first year admission rates for these courses. It appears that the use of the word ‘linguistics’ which is associated with stereotypical female skills has an influence on students applying for these courses.
To test this labelling mechanism further, I have devised an experiment which is currently on-going and which should confirm or refute this initial impression on a more scientific basis.
Step 3 Maintenance
On the surface, the Internet appears to be a ‘depersonalised ’ technology which lacks ‘social context information’. Kiesler et al. (1984). While audio and visual means of communication on the Internet are becoming more widespread, at the moment, on-line communication primarily takes place through text only and users can ‘hide behind’ gender- and status-neutral ‘handles’. What mechanisms are therefore operating which can account for the underrepresentation of females on the Internet?
Research shows that many women feel uncomfortable with aspects of the on-line community. Herring, S. (1993, 1994), Shade, L. (1993), Spender, D. (1995) Susan Herring (1994) for example found that many women felt intimidated by the type of discourse and flaming which can occur on-line and which Herring describes as “a rough and ready form of justice on the virtual frontier.” As a result, many females leave the Internet, while others resort to confining themselves to the use of email among their friends and to the use of moderated women-only mailing lists instead of the more public newsgroups. Herring suggests that the communication styles of many users were so gendered that other users regularly infer the gender of a user just from the communication style used.
In order to test whether this skill exists consciously or unconsciously in the community at large, I have devised an experiment which is currently on-going, to test people’s ability to determine the gender of the authors of different on-line texts. Further details of this experiment are supplied in Appendix 4.
The number of subjects who have participated in this experiment to date has not been large enough to be statistically significant but early indications show that females are more skilled at determining textual gender than males. It is hoped that over the next few months when sufficient subjects have participated in this experiment, more robust conclusions may be drawn. If it proves to be true that people in general and females, in particular, can determine the gender of an author from text alone, and if the majority of on-line texts are of masculine origin, then this could explain why females lose interest, feel intimidated, and feel disenfranchised by the Internet.
If this three step model proves to be robust, it should make it easier (if it is desired) either to enforce or to counteract genderisation processes within new activities and technologies.
The results of the Motorola (1995) Survey shows that men perceive themselves to be risk-takers and women perceive new technology to be risky. Previous research into risk-taking has concentrated on children’s risk-taking behaviours (RTB’s) while playing in public places, during games and has been inferred from statistical data on road and other accidents. Research into adult RTB’s has concentrated on games, car driving, and involved issues such as sexual promiscuity, AID’s and drug use, criminality, road deaths and accidents.
A survey of the literature on RTB in risk-taking games is ambiguous and sometimes contradictory. For example, some research has shown that males take greater risks than females, Slovic, 1966, Ginsburg & Miller 1982, Walesa, 1975, that females take greater risks than males, Lamm et al 1979, cited in Hargreaves, D. J. & Davies, G.M. (1996) or that there are no gender differences in RTB. (Arenson 1978)
In order to clarify these issues and provide a more comprehensive data base over a wider age range, I carried out an RTB experiment involving 338 subjects, 152 females and 186 males ranging in age from 7 to 62 + years. A computer program was devised which allowed subjects to adopt strategies using different levels of risk while playing a simple game. The object of the game was to obtain as high a score as possible. The game had 10 cards and subjects could choose to turn over as many cards as they liked. One of these cards was however a ‘dud’ card. The position of this dud card was chosen randomly by the computer for each run of the game. One point was awarded for each card successfully turned over, but if the dud card was turned, the subject was awarded zero points for that run. Increasing the number of cards increased the likelihood of locating the dud card but also increased the possible score.
Figure 1 shows that the optimum guess rate is to turn 4.5 cards on average, i.e. to choose to turn over 4 cards for half the number of turns (i.e. five turns) and 5 cards for the remaining five turns.
FIGURE ONE
Figure 2 shows the results of the subjects, analysed with respect to age. All age groups on average are conservative and score below the optimum guess rate. In other words they choose less than 4.5 cards. The graph also highlights a distinct age difference. Younger subjects on average take less risks than the older age groups. These are of course average results and within each age group there were individuals who took higher or lower risks. Some individuals consistently turned over 8 or 9 cards and others consistently turned only 1 or 2 cards.
FIGURE TWO
Figure 3 shows the average scores of the males and females. It can be seen from this graph that on average, males take more risks than females. Another interesting result from this graph is that both male and female children have almost identical scores until they reach 12 years of age. It is only from adolescence onwards that the scores differ.
FIGURE THREE
Table 1
Table 1 shows an ANOVA analysis of the data
(a) Shows there is a significant difference between male and female results for the 15-19 year olds. These results are significant at the 95% level.
(b) Shows there is a significant difference between male and female results for the 20-24 year olds. These results are significant at the 98% level .
(c) Shows there is a significant difference between male and female results for the combined results of the 15-24 year olds. These results are significant at the 99.5% level.
Table 1
The gender bias of magazines can be determined from the relative percentages of male, female and child models used in magazines. If you compare the profile of Wired and .net magazines, with the other magazines, it can be clearly seen that Internet magazines are male-orientated.
| Males | Females | Children | |
| Wired (averaged over 6 issues) | 77% | 19% | 4% |
| .net (one individual sample) | 74% | 22% | 4% |
| GQ (averaged over 6 issues) | 80% | 16% | 4% |
| Esquire (one individual sample) | 89% | 9% | 2% |
| SHE (averaged over 6 issues) | 23% | 56% | 21% |
| Cosmopolitan (one individual sample) | 25% | 69% | 6% |
| Computational Linguistics | Males | Females | Computer Applications | Males | Females | |
| 1991/1992 | 6 | 12 | 1991/1992 | 62 | 23 | |
| 1992/1993 | 4 | 17 | 1992/1993 | 93 | 37 | |
| 1993/1994 | 7 | 16 | 1993/1994 | 101 | 29 | |
| 1994/1995 | 6 | 19 | 1994/1995 | 108 | 22 | |
| 1995/1996 | 7 | 19 | 1995/1996 | 106 | 24 | |
| 1996/1997 | 9 | 16 | 1996/1997 | 102 | 27 |
A group of male and female Third Level students were invited to discuss on-line, five topics, namely:
Here is a small sample of the non-edited replies supplied by the students, arranged under the five question headings. Subjects in this experiment read a selection of statements and indicate whether they believe a male or a female wrote each of the comments.
Question (1) Is it safe to eat beef?
(a) Given the current uncertainties regarding the beef processing industry, it is probably wise to think about whether beef is, in fact, safe for human consumption. While it would certainly seem logical not to eat beef until such time as the uncertainties have been resolved, this logic has certainly not been applied in my case. I suppose I have, to a certain extent, been persuaded by the blurb issued by the Departments of Agriculture both here and in other countries which have been found to have casesof BSE, while the fears of such countries as Russia and Egypt in banning Irish beef seem to me a over-reaction to the situation. I feel, given that agriculture is such an important industry in this country has led to many people feeling that an attack on an element of this industry is almost an attack on the nation itself. Thus my persistence in consuming its products may be more to do with a defence of the country and its interests than anything else.
Is it safe to eat beef? To be honest, I simply don't know. Nonetheless, I am willing to take the risk. _____________________________________________________________________
Question (2) Is the university points system fair?
(b) 2-No, definitely not!!! I believe that the whole education system needs revising in Ireland because it doesn’t prepare you for the outside world. I did my Leaving Cert. two years ago and I remember it being a very stressful time. I think that it is a shame that there is so much emphasis on points. I hope a time will come when people will be able to do the courses they want without worrying about points.
In America , there are so many colleges that you have the option of choosing which one you would prefer, I don’t know if that will ever happen in Ireland. ____________________________________________________________________
Question (3) What should be done about Sellafield nuclear station?
(c) (3) I think that it should be better regulated. Enough isn't being done to ensure its run properly. When safety has been breached in the past not enough was done to make sure it didn't happen again. Also, the fumes given off by the station drift towards the east coast or Ireland and have quite obviously caused an increase the cancer and leukaemia levels. It isn't fair that people who have nothing to do with the station should suffer like this. I know there is no way British Nuclear Fuels are going to shut down the plant, so all I can hope for is for it to be better regulated by the British government. Also, the Irish government should do its part and put pressure on the British government for regulation and for compensation for the station's victims. ___________________________________________________________________
Question (4) Is marriage necessary?
(d) 4)Is marriage necessary? I don't think marriage is necessary unless the couple was going to have a baby. In some circumstances the couple would be better off financially if they were married, I think that is a shame because its like they are being forced to get married. When children are involved I think couples should get married if they love each other and are already 100% committed to each other.
_________________________________________________________________
Question (5) Can we trust Irish politicians?
(b) (5) In my opinion it depends on the individual politicians and parties. It wouldn't be fair to throw them all together under one generalisation. I personally will never note for Fianna Fail or any of its politicians. Over the years they have shown themselves to be so devious and two-faced and not to be trusted. For a gun runner like Charlie Haughey to have become Taoiseach was a disgrace. Also, during the peace-process with Albert Reynolds as Taoiseach he said one thing and did another. The picture of him shaking hands with John Hume and Gerry Adams was a disgrace. As soon as he was out of government he was stabbing the British government in the back and showing his real staunch republican views. Also, the Minister for Justice, Maire Geoghan Quinn, releasing all those IRA prisoners as a sign of "peace" was despicable. These were people who had bombed and killed innocent people and had years left on their sentence. Personally, I trust the majority of the other politicians in the Dail but there is no way I will trust Fianna Fail. _____________________________________________________________________
Arenson, S. J. (1978) ‘Age and Sex Differences in the Probability Preferences of Children’ Psychological Reports, 43, 697-698.
Eurostat, (1995) ‘Women and Men in the European Union. A Statistical Portrait’, Brussels, ECSC-EC-EAEC.
Ginsburg, H. J. & Miller, S. M. (1982) ‘Sex Differences in Children’s Risk-taking Behavior’, Child Development, 1982, 53, 426-428.
GVU (January 1994) ‘GVU’s First WWW User Survey’ Atlanta, Graphics, Visualization & Usability Center, Georgia Institute of Technology.
GVU (October 1994) ‘GVU’s Second WWW User Survey’ Atlanta, Graphics, Visualization & Usability Center, Georgia Institute of Technology.
GVU (April 1995) ‘GVU’s Third WWW User Survey’ Atlanta, Graphics, Visualization & Usability Center, Georgia Institute of Technology.
GVU (October 1995) ‘GVU’s Fourth WWW User Survey’ Atlanta, Graphics, Visualization & Usability Center, Georgia Institute of Technology.
GVU (April 1996) ‘GVU’s Fifth WWW User Survey’ Atlanta, Graphics, Visualization & Usability Center, Georgia Institute of Technology.
GVU (October 1996) ‘GVU’s Sixth WWW User Survey’ Atlanta, Graphics, Visualization & Usability Center, Georgia Institute of Technology.
Hargreaves, D. J. & Davies, G. M. (1996) ‘The Development of Risk-taking in Children’, Current Psychology: Developmental Learning Personality Social, Spring, 1996, 15, (1), 14-29.
Heilman, M. E. (1979) ‘High school Students’ Occupational Interest as a Function of Projected Sex Ratios in Male-Dominated Occupations’, Journal of Applied Psychology, 64, (3), 275-279.
Herring, S. C. (1993) ‘Gender and Democracy in Computer-Mediated Communication’, Electronic Journal of Communication, Special Issue on Computer-Mediated Communication, 1993, 3, (2).
Herring, S. (1994) ‘Gender Differences in Computer-Mediated Communication: Bringing Familiar Baggage to the New Frontier’, Keynote Talk at panel entitled “Making the Net*Work*: Is there a Z39.50 in gender communication?”, Miami, American Library Association Annual Convention, June 27, 1994.
Hymowitz, C. & Schellhardt, T. (1986, March 24) ‘The glass ceiling: Why women can’t seem to break the invisible barrier that blocks them from top jobs’, Wall Street Journal, A special report: The Corporate Woman, pp. 1, 4-5
Kiberd, D. (1997) ‘Why we must rush to embrace the information revolution’ The Sunday Business Post, Agenda, March 30, 1997.
Kiesler, S., Siegel, J., & McGuire, T. W. (1984) ‘Social Psychological Aspects of Computer-Mediated Communication’, American Psychologist, 39, (10), 1123-1134.
Maccoby, E. E. & Jacklin, C. N. (1974) ‘The Psychology of Sex Differences’, Stanford, California, Standford Univeristy Press.
Martin, M. (1991) ‘Hello Central?: Gender, technology and culture in the formation of telephone systems’, Montreal, Kingston: McGill-Queen’s University Press.
Motorola, (1995) ‘Prepared for the future? The British and Technology: A Motorola Report’, London, Motorola LTD and MORI.
NBC (1997) ‘PCTV Users group’ March 29th 1997
Shade, L. R. (1993) ‘Gender Issues in Computer Networking’ Talk given at: Community Networking: The International Fre-Net Conference, Carleton University, Ottawa, Canada, August 17-19, 1993.
Slovic, P. (1966) ‘Risk-taking in Children: Age and Sex differences’, Child Development, 1966, 37, 167-176.
Spender, D. (1995) ‘Nattering on the Net. Women, Power and Cyberspace’, Melbourne, Spinifex Press.
Touhey, J. C. (1974a) ‘Effects of Additional Men on Prestige and Desirability of Occupations Typically Performed by Women’, Journal of Applied Social Psychology, 1974, 4, (4) 330-335.
Touhey, J. C. (1974b) ‘Effects of Additional Women Professionals on Ratings of Occupational Prestige and Desirability’, Journal of Personality and Social Psychology, 1974, 29, 86-89.
VNU (1996 October) ‘VNU Internet Lifestyle Report’, London, VNU Newmedia in Association with Oracle.
Walesa, C. (1975) ‘Children’s approaches to chance- and skill-dependent risk.’ Polish Psychological Bulletin, 6, 131-138.
Williams, C. L. (1995) ‘Still a Man’s World. Men Who Do ‘Women’s Work’, Berkeley and Los Angeles, California, University of California Press, Ltd. Women and Work (1996) ‘The Facts about Women and Work’. Available from http://www.academic.org/work.html