Wage Differentials, Occupational Segregation, and ... - Springer Link

Eastern Economic Journal, 2011, 37, (178–196) r 2011 EEA 0094-5056/11 www.palgrave-journals.com/eej/

Wage Differentials, Occupational Segregation, and Gendered Creativity Perceptions in the Chinese Science and Technology Sector: Beijing and Wuhan a Gale Summerfield , Xiao-yuan Dongb, Nahid Aslanbeiguic d and Jie Hu a Women and Gender in Global Perspectives Program (WGGP) and Human and Community Development and Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign, 320 International Studies Building, 910 South Fifth St., Champaign, IL 61820, USA. E-mail: [email protected] b University of Winnipeg – Economics, 515 Portage Avenue, Winnipeg, Manitoba R3B 2E9 Canada. E-mail: [email protected] c Economics, Finance, and Real Estate, Monmouth University, W. Long Branch, NJ 07764, USA. E-mail: [email protected] d Institute of Mathematic Economics and Technology, Chinese Academy of Social Sciences, Beijing, China. E-mail: [email protected]

We examine the relationship between gender wage differentials and occupational segregation in small and medium-sized science and technology (S&T) firms in Beijing and Wuhan, using ethnographic material in addition to survey data from 202 firms. Although we find little evidence of overt discrimination against female workers, we discover significant gender wage gaps due to occupational segregation, influenced by cultural stereotypes, including perceptions of creativity differences among men and women. Research on gender issues in Chinese S&T may be limited, but scholarship on actual or perceived gender differences in creativity in the sector is, to the best of our knowledge, non-existent. Our analysis is a step toward filling that void. Eastern Economic Journal (2011) 37, 178–196. doi:10.1057/eej.2010.21 Keywords: gender; employment; China; creativity; science and technology JEL: J16; O15

INTRODUCTION Over the past three decades, China has launched a series of science and technology (S&T) initiatives that build capacity, promote research and development (R&D), mobilize personnel, and infuse technology into all sectors of the economy.1 Perhaps the most important of these measures is the establishment of 53 science parks, two of which are relevant to this paper. The most developed is the Zhongguancun Science Park (Z-Park), which has the longest history and spans 100 square kilometers in Northwest Beijing. Home to hundreds of research institutes and universities, it produces more than 100,000 graduates each year. In 2006, the Park housed some 18,000 companies, including 1,500 foreign firms, and generated $85.75 billion in revenue, including $12.6 billion in exports [Beale 2007].2 The second park is located in Wuhan, the largest city in central China. As coastal areas experience cost pressures, Wuhan, a transportation hub and a source of cheap labor, offers

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attractive opportunities for investment in S&T. The city houses 52 institutions of higher education and graduates 25,000 students in science every year [Arndt 2008]. Although they have not generated an abundance of innovation [Wang 2000; Cao 2001, 2004], Chinese science parks have increased productivity, countered wage and cost inflation, and diversified exports.3 They have also created substantial opportunities for Chinese women professionals, who, unlike the majority of female workers in export processing zones, are highly educated, earn some of the highest salaries in the nation [China Statistical Yearbook 2006], and are more likely to move up the promotion ladder. Many of their potentials, however, have not been tapped. Women are typically crowded into low-salary positions in human resources (HR), administration, marketing and finance but are significantly underrepresented among high-salary R&D personnel engaged in the actual scientific and technological work [Shen and Ge 2005, p. 6]. In this paper, we examine the relationship between gender wage differentials and occupational segregation in small and medium-sized S&T firms in Beijing and Wuhan, using ethnographic material in addition to survey data from 202 firms. Although we find little evidence of overt discrimination against female workers, we discover significant gender wage gaps due to occupational segregation, influenced by cultural stereotypes, including perceptions of creativity differences among men and women. Research on gender issues in Chinese S&T may be limited, but scholarship on actual or perceived gender differences in creativity in the sector is, to the best of our knowledge, non-existent. Our analysis is a step toward filling that void. It also contributes to the larger literature on gender issues, which examines the reasons for women’s underrepresentation in S&T.4 In particular, our study connects with Virginia Valian’s work [1999, 2005]. Even in environments such as China, where there is a concerted effort to treat men and women equally in the workplace, gender schemas — ‘‘implicit, or nonconscious, hypotheses about sex differences’’ [Valian 1999, p. 2] — create disparities that accumulate over time and slow down women’s advancement. As Valian [2005] and our study demonstrate, women are as likely to be influenced by gender schemas as men. We extend this literature by examining the contribution of gendered perceptions of creativity to occupational segregation in the S&T sector in two major Chinese cities.

RESEARCH METHODOLOGY AND PRELIMINARY FINDINGS Initial ethnographic study in Beijing Our research began in June 2007 with ethnographic studies of six companies, five of which were located in Z-Park. This section describes the method and preliminary findings of the ethnographic study in Beijing. Using a purposeful sampling method, we conducted semi-structured, in-depth interviews with firm designated managerial personnel, including four (HR) managers or directors — three of whom were female — a female chief executive officer (CEO), a male chief engineer, a female accountant, and several other female employees.5 Three co-authors, two of whom are native speakers, conducted interviews in Chinese. We used a survey instrument that included open-ended questions; subjects were encouraged to respond with as much detail as they felt comfortable. The firms represented a wide range of productive activity in S&T, including software and hardware development, information management platform, electronic publishing, electric power equipment, and R&D in environmental protection. They ranged Eastern Economic Journal 2011 37


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in size — small, medium, and large — and ownership structure — private, public, foreign, and domestic. Our interviews confirmed the highly competitive nature of the sector. Even telecommunication firms that receive preferential treatment from the government complained about the intensity of competition. The cut-throat environment — frequently attributed to internal market forces instead of accession to the World Trade Organization (WTO) — compels firms to regularly reform ownership structures, reduce prices, advertise, and develop new technologies and products. Workers are expected to consistently work hard, remain flexible, and learn new skills. Some firms report being forced to reduce entry salaries by 17–40 percent. Turnover rates are high, reaching 20–30 percent each year, which is consistent with findings in other studies [see Cao 2004, p. 658; Zhou 2005, pp. 1125–26; Tan 2006, p. 839]. Turnover is partly involuntary since some firms rank employee performance annually and routinely fire the bottom 5–10 percent of their workforce.6 Overtime work is common in the industry. A 2004 survey of Chinese women workers in IT discovered that almost 70 percent work more than 8 hours a day [Shen and Ge 2005, p. 5]. Our interviewees were reluctant to discuss work hours or days due to the recent death of an IT employee, which had been connected to excessive overtime work and received much negative publicity. Employees of one firm, however, stressed that they enforced a ‘‘strict annual vacation policy,’’ indicating that without it, workers would work year round. Medium and large-sized firms provided several types of social insurance or benefits to their workers — pension, health, unemployment, housing pool fund, work injury, and reproduction — which cost them 40 percent of the wage bill. Three of the six firms had trade union representation. The government affiliated All China Federation of Trade Unions (ACFTU) is the only legally sanctioned union in China.7 ACFTU discourages strikes but provides a range of social and educational activities for workers. A large, foreign-owned software manufacturer reported having a female employee office that organized activities and helped women exchange views and solve common problems. None of the firms we interviewed had All China Women’s Federation (ACWF) representation.8 At our interview sites, the female share of employment ranged from 15 to 53 percent. Women’s share of mid-level (11–38 percent) and high-level (0–25 percent) management was lower. Almost all interviewees insisted that there was no gender discrimination in hiring, a statement that must be discounted. With one exception, the average age of workers in S&T firms we visited was less than 30. The age at which urban women give birth to their first, and most likely only, child is also less than 30. The law mandates that reproduction insurance be funded exclusively by employers [Drouin and Thompson 2006, p. 47]. Maternity benefits, which are regulated by municipal and county governments, include time off for medical exams during pregnancy, maternity leave to give birth (minimum of 3 months), paternity leave (a few days), medical costs for mother and child, and daily time allowances for breastfeeding. It is difficult to believe that firms would be insensitive to these costs under cut-throat competition. Most firms insisted that they did not discriminate against women in compensation. However, they revealed strong beliefs in gender stereotypes. Women were ‘‘appropriately’’ crowded into HR, accounting, and back office operations. Men were regarded as much better performers in R&D and production, sale and customer support of products that have high technological content.9 Male and female employees commented on factors that promote occupational segregation in Eastern Economic Journal 2011 37


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S&T firms, holding that women suffer hard-to-overcome ‘‘shortcomings’’ such as lack of creativity. A collage of their comments follows. There are ‘‘few smart excellent women’’ workers. Women are less likely to be ‘‘self-driven,’’ ‘‘energetic,’’ and ‘‘open-minded.’’ They are more likely to take orders than initiatives and have difficulty coping with the ‘‘pace of technological change.’’ As workers, men are ‘‘innovative and willing to overcome’’ problems; as leaders, they are more ‘‘tolerant, receptive and dignified.’’ Women’s ‘‘earnestness, discipline, patience and stability’’ qualify them for some positions — HR or accounting (particularly auditing). But their attention to detail blinds them to ‘‘the big picture.’’ Female leaders are more ‘‘emotional’’ and averse to diverse opinions. The female CEO of one firm, where 53 percent of employees were female, praised women’s abilities. Even she, however, used stereotypical characterizations to describe gender differences. Male CEOs are ‘‘more energetic’’ and ‘‘adventurous.’’ Female CEOs are stable and risk averse. Companies with female CEOs, she explained, do not grow fast but last longer. Interviewees conceded that cultural norms impede the advancement of women professionals in S&T. Socializing with male clients invites gossip and criticism. Women are often reluctant to apply for jobs that require travel because they are considered unsuitable for women. Kitching and Jackson explain that ‘‘women travelling on business are subject to harassment, with special female-only hotels being set up to protect [them] from unwelcome attention and even violence’’ [2002, p. 151]. The HR director of one firm found women to be good in sales due to their honesty. The HR director of another firm, which made high-technology products, was reluctant to hire women in the sales department. The firm obtained orders, which were high in value and long in duration, through a competitive bidding process. This required ‘‘multidimensional collaboration, social networks and human contacts.’’ Women do not have adequate social networks and are outperformed by men.10 The difficulty of combining marriage and work was repeatedly acknowledged. Women bear an inordinate share of family responsibilities. One interviewee said the company does not like to hire pregnant women and warns new recruits not to get pregnant during their probationary period. Another observed that motherhood takes a toll on women’s labor force participation, some quitting their jobs after the completion of their maternity leaves. Many expressed the view that the S&T industry is for young employees, who presumably do not have children. Motherhood and age increase the ‘‘pressure and sacrifice’’ of ‘‘career advancement.’’11

Survey in Beijing and Wuhan We used our ethnographic results to design a broader survey of small and mediumsized firms in S&T in Beijing and Wuhan. The survey explored gender wage differentials, occupational segregation, and perceptions of the sector’s suitability Eastern Economic Journal 2011 37


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as a place of employment for women professionals. In addition, we probed respondents’ opinions on gender differentials in creativity. The China Association of Small and Medium Enterprises (CASME), which has local affiliates in both cities, administered the survey. Firms — 107 in Beijing and 101 in Wuhan — were chosen randomly by CASME from an enterprise list. Beijing firms were located in two main zones: Z-Park and Shangdi; Wuhan enterprises were chosen from the Guanggu IT zone (Optics Valley). Firms’ administrative records provided data on business operation such as sales revenue, capital assets, employment, workforce composition, and wages for three consecutive years (2004–2006), allowing us to create panel data that enriched our regression estimates. CASME personnel interviewed senior or mid-level managers or firm designated employees on gender differences and creativity perceptions. The qualitative data were provided for 1 year (2006). In China, firms treat responding to independent scholar surveys as optional. Surveys conducted by CASME or other government agencies are, on the other hand, taken very seriously. Although CASME did not reveal the response rate, we are reasonably sure that it was quite high. The high compliance rate created a sample that was representative of its respective population. To improve representation, we eliminated some outliers based on size, which reduced the number of firms to 103 in Beijing and 99 in Wuhan.

FIRM AND EMPLOYEE CHARACTERISTICS Table 1 summarizes some of the characteristics of firms in our sample. Companies producing computer software and hardware each account for about one-third of the total number of enterprises, with Beijing firms having a relatively higher focus on hardware production. Judging by revenues, employment, or assets, Beijing enterprises are considerably larger than those in Wuhan; compared to Wuhan, Beijing enterprises also have higher capital–labor ratios and higher labor productivity (sales per employee). However, firms in both regions are relatively young. The overwhelming majority are privately owned, and production and sales concentrate on satisfying domestic demand. One-fourth of the firms trade with other countries. However, the share of exports in sales revenue is much lower (5 percent). WTO accession has produced no effect on 35 percent of firms. A small portion (13 percent) has seen their sales increase or drop. More than half (51 percent) report that their environment has become more competitive. Partial or complete foreign ownership, however, is rare in our sample — less than 3 percent — confirming the sector’s inability to attract foreign or venture capital [Wang 2000, pp. 23–24; Zhou 2005, p. 1126]. The share of companies with some degree of government ownership is low, less than 3 percent. Thus it is not surprising that only some 20 percent of enterprises have trade unions or women work committees.12 Although the government mandates that urban enterprises — regardless of their ownership structure — provide a host of social insurance and benefits to their employees, the compliance rate is not impressive [Dunaway and Arora 2007]. Twenty-seven percent of the firms in our survey do not provide any type of health insurance to their workers. Fifty percent report that their workers have no pension plans.13 Nearly 99 percent of firms impose minimum education requirements ranging from a 3-year university degree to a Ph.D. However, only 72 percent specify the same requirements for male and female employees. The most popular method of recruiting employees is through special arrangements with institutions of higher education. Eastern Economic Journal 2011 37


183 Table 1 Summary statistics of S&T firm characteristics, 2006a

Real wage (yuan/month) Share of female employees Sales revenue (1,000 yuan/year) No. of employees Assets (1,000 yuan) Sales per employee (1,000 yuan/year) Assets per employee (1,000 yuan) Share of exports in sales Firm age (year) Share of managerial personnel Share of R&D and engineers Share of HR and accountants Share of sales persons Share of service personnel Share of production workers Share of other workers Minimum education requirement 3-year university degree 4-year university degree Master’s degree Ph.D. Main products Software Hardware Other IT and high-tech. products Other products Male and female have the same education requirements CEO is a woman Ownership Joint stock corporation Solely private-owned firm Partnership and cooperatives Solely state-owned firm Partially state-owned firm Solely foreign-owned firm Foreign joint venture Have union or women committee Require a test for recruitment Provide training 8–5 regular work hours Monday–Friday regular week No. of firms No. of observations

Full sample

Beijing

Wuhan

2,435 0.269 6,836 121 2,261 35.0 12.5 0.052 5.6 0.110 0.210 0.112 0.355 0.082 0.093 0.037

2,622 0.290 10,160 135 3,733 44.0 13.1 0.051 5.4 0.111 0.155 0.113 0.492 0.073 0.020 0.036

2,231 0.246 3,222 107 660 25.1 11.7 0.052 5.8 0.109 0.271 0.110 0.206 0.092 0.173 0.039

0.470 0.267 0.059 0.188

0.447 0.194 0.000 0.330

0.495 0.343 0.121 0.040

0.342 0.342 0.198 0.119 0.718 0.084

0.194 0.466 0.252 0.087 0.654 0.097

0.495 0.212 0.141 0.152 0.788 0.071

0.292 0.406 0.218 0.005 0.030 0.005 0.020 0.203 0.906 0.950 0.614 0.406 202 574

0.117 0.583 0.252 0.000 0.019 0.000 0.010 0.136 0.835 0.932 0.583 0.320 103 299

0.475 0.222 0.182 0.010 0.040 0.010 0.030 0.273 0.980 0.970 0.646 0.495 99 275

a Statistics presented in this table represent the unweighted mean values of the firms in the sample. Source: Authors’ survey.

Newspaper and Internet advertisements are less popular but significant. Less than 15 percent recruit through internal recommendations, private labor agencies, or job fairs. The majority of firms screen job applicants using knowledge, skill, and personality tests. Once hired, new recruits receive orientation (a few days) and position training (a few weeks). Continuing employees are periodically trained to update and enhance their skills. About 61 percent of firms have regular work hours (8–5); only 40.6 percent have a 5-day work week (Monday–Friday). Eastern Economic Journal 2011 37


184 Table 2 Occupational distribution of S&T employees in Beijing and Wuhan Full sample Total employment 2004 2005 2006 By occupation (2006) Managerial personnel R&D and engineers HR and accountants Sales Services Production Other

Beijing

% female

Total employment

Wuhan

% female

Total employment

% female

17,671 20,981 24,263

25.5 24.4 23.9

10,836 13,093 14,842

24.1 23.1 22.5

6,835 7,888 9,421

27.9 26.5 26.1

2,121 8,542 2,408 7,736 1,598 3,910 878

22.9 15.2 60.8 22.4 7.6 23.6 38.9

1,367 4,517 1,646 6,196 681 431 492

23.1 11.0 58.7 22.7 2.5 20.0 37.8

754 4,025 762 1,540 917 3,479 386

22.5 20.0 65.2 21.4 11.5 24.0 40.4

Male

Female

Male

Female

Male

Female

8.4 22.4 25.2 29.9 2.1 15.9 5.9 100.0

8.9 33.9 5.7 40.4 5.6 2.9 2.6 100.0

9.1 14.3 27.9 40.5 0.5 2.5 5.4 100.0

6.5 35.9 3.0 13.5 9.1 29.5 2.5 100.0

5.9 27.7 17.2 11.4 3.6 28.9 5.3 100.0

By sex and by occupation (%) (2006) Managerial personnel 8.8 R&D and engineers 39.2 HR and accountants 5.1 Sales 32.5 Services 8.0 Production 16.2 Other 2.9 Total 100.0 Duncan index 2004 2005 2006

0.217 0.232 0.214

0.258 0.268 0.252

0.175 0.204 0.171

Source: Authors survey.

Table 2 presents summary statistics of the distribution of employees in our sample by gender and occupation. Women constitute 23.9–25.5 percent of the total employment in the sample, although their share is higher in Wuhan compared to Beijing.14 The distribution of women across occupations is uneven, suggesting occupational segregation.15 Women are concentrated in HR and accounting in addition to a category called ‘‘other,’’ which primarily includes clerks and assistants. In comparison, the proportion of women in R&D, engineering, and customer service is much lower. Using gender distributions across occupations for 2004–2006, we obtained a Duncan Index of 0.214–0.232 for the whole sample, 0.252–0.268 for Beijing, and 0.171–0.204 for Wuhan.16 Our estimates are similar to that (0.246) Zhang and Dong [2008, p. 92] calculated from Chinese manufacturing and high-end service sectors. It is noteworthy that women account for a larger share of R&D and engineers in Wuhan than in Beijing and the degree of occupational segregation is also lower in Wuhan than in Beijing. This difference may be due to the fact that enterprises in Beijing are relatively more cutting edge, judging by larger capital–labor ratios and higher labor productivity. In addition, Beijing has relative superiority in location as well as Eastern Economic Journal 2011 37


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education and research, both of which attract a stronger pool of R&D and engineering personnel. We asked respondents to comment on whether the S&T sector is a suitable place for women’s employment. A significant majority — (164; 79 percent) — answered in the affirmative. Three sets of reasons were offered.17 (A) Most frequently cited (71) was the diverse array of advantages not open to women in other sectors: support, good salaries and benefits, meritocracy, and ‘‘freedom and vitality.’’ Many (18) emphasized gender equity as a winning feature. Both female and male respondents believed that women can excel in the sector because they are free to develop their capacities and demonstrate their strengths in oral and written communication, team work and ‘‘sense of responsibility.’’ Several (8) were happy that women could hold jobs in sales. An equal number touted the stability of women’s positions. (B) A significant number (67) emphasized their work environment or culture. A sizeable group (34) characterized their workplace as ‘‘nice,’’ ‘‘comfortable,’’ ‘‘quiet,’’ and ‘‘beautiful,’’ a place where they could feel ‘‘good’’ or ‘‘happy.’’ Some (22) found their work environment to be stress free or ‘‘easy.’’ Others (8) liked the style of management, ‘‘harmonious corporate culture,’’ or the attention bosses or CEOs paid to women. (C) Finally, a small group of respondents (8) appreciated the gendered division of labor in the workplace. ‘‘HR’’ positions were more suitable for women compared to ‘‘technical positions.’’ Only 21 percent of respondents found the sector unsuitable for women workers. Male respondents, who outnumbered women by a margin of two to one, emphasized long hours, work intensity and stress (13), and fatigue (8). Female respondents found the work too stressful (7) or unfair (2) for paying lower benefits and salaries.

OCCUPATIONAL SEGREGATION AND WAGE DIFFERENTIALS We use firm-level data to estimate the impact of occupational segregation on gender wage differentials. Because reliable compensation information by sex is unavailable, we estimate the relative wages of female as compared to male workers from wage is a geometric average regressions.18 We assume that the average wage of a firm (W) f ¼ WSf W1S of wages paid to female (Wf) and male (Wm) workers, that is W m , where f Sf and 1Sf represent the female and male shares of employees, respectively.19 The logarithm of the average wage takes the form: ¼ Sf logðWf Þ þ ð1 Sf Þ logðWm Þ log W ð1Þ

¼ logðWm Þ þ Sf ðlog Wf log Wm Þ:

Writing log(Wf)log(Wm) ¼ log(Wf/Wm) ¼ f and replacing log(Wm) by a linear stochastic function of its determinants, l0 þ X0 l þ u, we have the wage equation: ð2Þ

¼ l0 þ fSf þ X 0 l þ u logðWÞ

where X is a vector of variables that determine the wage, holding constant the effects of gender; the Greek letters are unknown parameters, and u is a random disturbance term. In this equation, the coefficient of the share of female employees, f, provides an estimate of the gender wage gap in log form; the anti-log of f is the ratio of female to male wages Wf /Wm. Variables included in X allow wages to change systematically across occupations and cities over time (2004–2006); they also Eastern Economic Journal 2011 37


186 Table 3 Determinants of wages in S&T firms in Beijing and Wuhan, 2006a Dependent variable=log wage

Share of female employees Wage ratio of female to male Share of R&D and engineers R&D Share Beijing Share of managerial personnel Share of HR and accountants Share of sales persons Share of customer services Share of production workers Share of exports in sales Assets per employee (1,000 yuan) Firm age (year) Software Hardware Other S&T products Sole owner private firm Partnership and cooperatives Solely state-owned firm Partially state-owned firm Solely foreign-owned firm Foreign joint venture 3-year university degree 4-year university degree Master’s degree Ph.D. Have union or women committee

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(1)

(2)

(3)

(4)

Coefficient (Std. err.)




0.790 (0.134)*** 0.459

0.289 (0.124)** 0.749 0.008 (0.412) 1.505 (0.199)*** 0.414 (0.474) 0.231 (0.402) 0.101 (0.393) 0.087 (0.455) 0.151 (0.381)

0.485 (0.116)*** 0.615

0.251 (0.122)** 0.778 0.305 (0.382) 1.318 (0.199)*** 0.001 (0.449) 0.072 (0.348) 0.489 (0.351) 0.699 (0.392)* 0.355 (0.348) 0.244 (0.153) 0.051 (0.011)*** 0.008 (0.004)** 0.003 (0.044) 0.066 (0.049) 0.042 (0.054) 0.038 (0.040) 0.175 (0.041)*** 0.352 (0.082)*** 0.093 (0.068) 0.062 (0.071) 0.126 (0.096) 0.031 (0.073) 0.011 (0.075) 0.065 (0.097) 0.107 (0.076) 0.058 (0.044)

0.248 (0.153)* 0.090 (0.014)*** 0.009 (0.003)** 0.023 (0.040) 0.178 (0.043)*** 0.054 (0.049) 0.058 (0.044) 0.208 (0.043)*** 0.414 (0.077)*** 0.070 (0.074) 0.098 (0.066) 0.026 (0.126) 0.047 (0.068) 0.187 (0.073)** 0.138 (0.091) 0.065 (0.069) 0.091 (0.048)*


187 Table 3 (Continued) Dependent variable=log wage

(1)

(2)

(3)

(4)





0.060 (0.038) 0.142 (0.037)*** 0.189 (0.063)*** 7.689 (0.387)*** 14.51 0.00 0.349 574

0.223 (0.056)*** 0.065 (0.038)* 0.152 (0.037)*** 0.205 (0.044)*** 7.569 (0.100)*** 16.28 0.00 0.346 574

0.284 (0.053)*** 0.060 (0.035)* 0.143 (0.035)*** 0.177 (0.071)** 7.445 (0.361)*** 17.76 0.00 0.458 574

Provide training 2005 2006 Beijing Constant F test for 0 slope P value R2 No. of observations

0.063 (0.044) 0.147 (0.043)*** 0.068 (0.036)* 7.795 (0.047)*** 11.80 0.00 0.080 574

a

The table presents OLS estimates with heteroscedasticity-robust standard errors reported in parentheses. ***, **, and *: Significance levels of 1, 5 and 10 percent, respectively. Source: Authors’ survey.

control for firm characteristics such as products, ownership type, age, export share, assets per employee, composition of the workforce, and educational requirements.20 These covariates take into account effects of gender segregation by occupation and firm attribute. We use OLS to estimate equation (2); wage regression estimates are presented in Table 3.21 We first regress the average firm wage on the share of female employees only controlling for year and city effects (see column (1)). The female share estimate has a negative sign and is significant at the 1-percent level, indicating that firms with larger female shares pay lower wages. Based on equation (2), the estimate of female share implies that female employees earn only 45.9 percent of male employee wages. As an estimate of the raw gender wage gap, this is larger than the estimates of gender wage gaps in urban China commonly reported, which are in the range from 0.7 to 0.8. As we control for sex segregation measured by workforce composition and firm characteristics below, the estimated gender wage gap becomes more in line with the estimates of the existing studies. In column (2), we introduce variables for workforce composition to discern the effects of occupational segregation. Summary statistics show that in Beijing, R&D and engineering personnel account for a smaller proportion of the workforce, and women constitute a smaller share of R&D and engineering personnel. We introduce an interactive dummy variable for Beijing with the share of R&D and engineering personnel to test whether it has the same impact on wages in Beijing and Wuhan. As can be seen from column (2), while the sign of female share remains negative and statistically significant, the quantitative estimate increases noticeably from 0.790 to 0.289, or by 63 percent. Estimates also show that the average wage is positively correlated with the proportion of personnel in R&D and engineering, sales, customer service and production, and negatively correlated with the proportion of personnel in management, HR, and accounting. However, Eastern Economic Journal 2011 37


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only the interactive dummy with R&D and engineering is statistically significant. A 1-percent increase in the share of personnel in this category increases the average wage level in Beijing by 1.51 percent, while its impact on firms in Wuhan is statistically insignificant and quantitatively negligible. Thus, there is evidence that women’s underrepresentation in this occupational category plays a more important role in generating gender wage differentials in Beijing. Wage premia for R&D and engineering are smaller in Wuhan perhaps because firms located in this city are technologically less sophisticated and the labor force is not as talented, preventing firms from being discriminating. Controlling for occupational distribution, the estimate of female share increases from 0.790 to 0.289, implying that the wage ratio of female to male employees goes up from 0.459 to 0.749. In column (3), we control for firm characteristics but exclude the variables for occupational distribution. Firms with larger shares of export revenues or higher capital–labor ratio pay higher wages, as do firms that are older or require 4-year university degrees. Wages are higher for partnerships and cooperatives but much lower for solely state-owned firms. They are relatively lower for firms that produce hardware compared to other products. Holding firm characteristics constant, the estimate of female share continues to be negative and statistically significant, but its magnitude increases from 0.79 in column (1) to 0.485 or by 38 percent. In light of changes in female share estimates in columns (2) and (3) relative to (1), occupational segregation appears more important than firm attributes in accounting for gender wage differentials. In column (4), we control for both occupational variables and firm characteristics. The female share estimate is still negative and statistically significant, indicating that, ceteris paribus, female employees earn about 77.8 percent of what their male colleagues earn. This estimate is similar to the estimate (0.776) Dong and Zhang [2009, p. 150] obtained for Chinese manufacturers. The residual gender wage gap of 22.2 percent may be due to a number of factors that require further study. However, we should not leave the subject without making a few observations. Differences in years of education may explain a significant portion of this residual. Even where firms establish equal educational floors for men and women (72 percent), actual education levels may differ. Since women occupy fewer managerial or technical positions, it is reasonable to assume that they would be less educated compared to men. Years of experience, on the other hand, may not play a significant role in explaining why women earn less than men. The average age in this sector is quite low [Cao 2004, p. 658], often less than 30. Turnover, on the other hand, is very high because, as one HR director stated, ‘‘new recruits have high expectations.’’ This view is confirmed by the literature on Z-Park, where ‘‘hardly anyone remains in one position for more than 3 years’’ [Zhou 2005, p. 1126; also see Tan 2006, p. 839]. Job-hopping may lead to higher salaries, but in some cases to loss of seniority as well, especially if it is from a government enterprise to the private sector [Hildebrandt and Liu 1988, p. 301]. Our interview and survey data indicate that there is very little voluntary mobility among women workers. Women’s turnover is usually due to layoff of workers whose performance is ranked in the bottom 5–10 percent. Thus seniority or internal firm experience should work in women’s favor in the S&T sector. Finally, residual wage differences may be due to discrimination. There is very little perception of discrimination in our sample. Only three respondents identified discrimination or unfairness as a characteristic feature of the sector. In contrast, 18 perceived the sector to be non-discriminatory or fair. A study of Chinese women Eastern Economic Journal 2011 37


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professionals in IT shows similar sentiments, where 80 percent of the subjects thought that ‘‘gender is no longer an obstacle to their promotion and development, which they see as determined by knowledge and experience, [and] employment criteria specified by most enterprises’’ [Shen and Ge 2005, p. 7]. However, perceptions may be radically different from reality. It is quite possible that women’s satisfaction with the S&T sector is based on a relative comparison with other sectors, where conditions may be much worse. One area in which discrimination may play a significant role is the award of bonuses. With two exceptions, all firms in our sample paid bonuses. However, only 56 percent paid bonuses to all workers. Bonuses are based on hours of work (12.4 percent), base pay (18.42 percent), and/or performance evaluation (69.17 percent). If women work fewer hours compared to men or are discriminated against in salary payments, it is likely that they would receive lower bonuses. Performance evaluation is a subjective process colored by cultural stereotypes. Several interviewees believed that women’s job performance suffers when they must care for children or the elderly. ‘‘Reproductive responsibilities,’’ a male HR director claimed, ‘‘hurt women’s careers and also adversely impact their ability to learn new skills.’’ A female HR director observed that women workers pay more attention to ‘‘family and children,’’ which ‘‘inevitably affects their dedication to work, especially after having a child’’ [also see Kitching and Jackson 2002, p. 149; Berik, Dong, and Summerfield 2007, p. 5].22

OCCUPATIONAL SEGREGATION AND CREATIVITY PERCEPTIONS Although China has lower degrees of gender segregation compared to other developing countries, the large occupational segregation in S&T is a reason for concern.23 The most striking discovery in our ethnographic study was the view, shared by both genders, that women should not work in R&D because they lack creativity. We explored the subject further in our surveys of Beijing and Wuhan firms. Research on creativity differences among men and women concentrates on the western hemisphere.24 Psychoanalysts have tied creativity to well-integrated primary process cognition, sometimes defined as ‘‘the surfacing of unconscious instinctual energy in the form of images and ideas’’ [Russ 2002, p. 54]. Although research does not find reliable evidence that men and women differ in their primary process cognition potentials, it consistently discovers actual gender differences that are attributed to socialization.25 Parents and teachers indoctrinate girls in values that discourage creative expression: impulse control, propriety, politeness, femininity, conformity, and dependence [Helson 1990, p. 49; Reis 2002; Russ 2002, pp. 73–74]. As adults, creative women are typically far less productive than men, because they bear children and have the primary responsibility for home, child and adult care [Pohlman 1996; Reis 2002]. These realities and the perceptions they contribute to affect practices in hiring and promotion, training and compensation.26 Studies of Chinese female professionals attest to their high levels of competency. Female business students are ‘‘at least as competent and hardworking as the men’’ [McKeen and Bu 1998]. Female managers are equal to their male counterparts in their ‘‘mastery and application of modern high-tech communications’’ [Yu and Zhu 2000]. And women show no less ‘‘motivation to manage’’ than their male colleagues Eastern Economic Journal 2011 37


190 Table 4 Respondents’ definitions of creativity in S&T firms in Beijing and Wuhan, 2006 Definition of creativity

Full sample (%) (Std. dev.)

Male respondents (%) (Std. dev.)

Female respondents (%) (Std. dev.)

New ways to manage workers or coordinate activity

31.7 (46.6)

28.8 (45.4)

36.4 (48.4)

Designing a new product that improves company operations

18.3 (38.8)

19.2 (39.5)

16.9 (37.7)

Designing a new product that would increase sales revenue

17.8 (38.4)

16.8 (37.5)

19.5 (39.9)

New ways to improve worker productivity

12.4 (33.0)

14.4 (35.3)

9.1 (28.9)

Good salesmanship

18.8 (39.1)

20.0 (40.2)

16.9 (37.7)

Other

1.0 (9.9)

0.8 (8.9)

1.3 (11.4)

No. of observations

202

125

77

Source: Authors’ survey. Note: None of the differences in men’s and women’s responses is statistically significant.

[Chen et al. 1997, p. 169]. However, the literature does not cover issues concerning creativity or its connections to occupational segregation in S&T. To partly fill this void, in our survey we explore perceptions of gender differences in creativity. Table 4 represents how our respondents define creativity.27 Particular weight is attached to new methods of workforce management and coordination. Good salesmanship and designing products that improve operations and sales are also deemed important, but fewer respondents (17.8 percent) define creativity as designing products that increase sales above what is expected in such a competitive environment. In contrast, the initial ethnographic interviews we conducted in Beijing found that the respondents expressed the importance of creativity in R&D and stressed women’s lack of creativity in developing new products as the main reason for not being hired in that occupation. Also surprising is that only 12.4 percent of respondents view improving worker productivity as creative. While there are some numerical differences in male and female respondents’ views regarding what feature best defines creativity, these differences are statistically insignificant. Table 5 captures respondents’ perceptions of gender differentials in creativity. Ninety percent of all respondents (men and women) agree with the statement that men are creative, while only 53 percent agree with the same statement about women. Relative to their male counterparts, female respondents are more enthusiastic about women’s creativity, and the perception difference between male and female respondents is statistically significant only for women’s creativity. Male creativity is primarily perceived to be innate; female creativity, however, is perceived to derive from aspiration and dedication. Interestingly, a higher proportion of female respondents attribute men’s creativity to innate ability compared to male respondents. Only 10 percent agree with the statement that men are not creative; but almost half (47.3 percent) state that women are not creative. The primary reason for deficiencies in creativity among men is lack of aspiration and dedication. For women, however, the main obstacle to creativity is domestic responsibilities. An interesting Eastern Economic Journal 2011 37


191 Table 5 Respondents’ perceptions of worker creativity in S&T firms in Beijing and Wuhan by gender, 2006 Men are creative

Women are creative

Full Male Female Full Male Female sample respondents respondents sample respondents respondents % agree Reasons for creativity Fewer domestic responsibilities Innate ability Aspiration and dedication No. of observations

90.1

91.2

88.3

53.0

48.0

61.0a

21.9

18.4

27.9

0.9

0.0

2.1

41.0 37.5 182

37.7 43.8 114

47.1 25.0 68

29.9 68.2 107

31.7 68.3 60

27.7 68.2 47

Men are not creative % agree Reasons for lack of creativity More domestic responsibilities Lack of innate ability Lack of aspiration and dedication No. of observations

Women are not creative

9.9

8.8

11.7

47.0

52.0

39.0

19.3

27.3

11.1

53.3

44.6

66.7

17.5 57.9 20

18.2 54.5 11

22.2 66.7 9

32.2 14.4 95

36.9 18.5 65

30.0 3.7 30

a

The perception difference between male and female respondents is statistically insignificant with respect to men’s creativity but significant at the 1% level with respect to women’s creativity. A few respondents gave more than one reason for men’s or women’s creativity. For clarity of exposition, we present only the choice that the respondent thought most important. Source: Authors’ survey.

narrative emerges from these results. Men are endowed with a natural ability to create; if they do not tap their potential, they must lack aspiration and dedication. Women are not well endowed innately, but they can compensate with ambition and hard work. If they are not creative, the cause must be an excessive burden of domestic responsibilities. To explore the relationship between creativity perception and women’s entry to S&T enterprises in general and R&D and engineering occupation in particular, we estimate the determinants of female share in total employment and in R&D and engineers using OLS.28 As expected, Table 6 shows that the female share in both equations is negatively correlated with the perception that men are creative and positively with the perception that women are creative, and all the estimates on perception are statistically significant. Quantitatively, the shares of female employees in total employment and in R&D and engineering are, respectively, 9.9 and 14.5 percentage points lower for firms whose managers think men are creative. Compared to those for males perceived creative, the estimates of females perceived creative are markedly smaller. As Table 5 shows, this is perhaps because relatively few respondents think women are creative. We find that the distribution of S&T workforce by gender and occupation mirrors occupations in which respondents think men and women are creative. This suggests that creativity perceptions affect enterprise recruitment, while existing occupational segregation enforces prevailing gendered creativity perceptions. Due to data limitations, we are unable to identify the direction of causality between the two sets of variables. Eastern Economic Journal 2011 37


192 Table 6 Determinants of the share of female employees in S&T firms in Beijing and Wuhan, 2006a Dependent variable

Independent variables Males perceived creative Females perceived creative Share of exports Assets per employee Firm age Share of R&D and engineers Share of managerial personnel Share of HR and accountants Share of sales personnel Share of customer services Share of production workers 3-year university degree 4-year university degree Master degree required Ph.D. degree required Software Hardware Other IT and high tech. Same educ. req. Female CEO Solely private owned Partnership Solely state owned Partially state owned Solely foreign owned Joint venture Have union or women committee Test required Provide training 8–5 regular hours Monday–Friday workday 2005 2006 Beijing Constant F test for 0 slope P value R2 No. of observations

Female share of total employment

Female share of R&D and engineers

Coefficient

Standard error

Coefficient

Standard error

0.099 0.020 0.039 0.003 0.005 0.191 0.165 0.114 0.031 0.212 0.072 0.025 0.040 0.025 0.052 0.020 0.035 0.045 0.021 0.001 0.033 0.009 0.006 0.027 0.003 0.029 0.008 0.026 0.035 0.015 0.001 0.009 0.006 0.006 0.406 10.02 0.00 0.235 574

0.023*** 0.012* 0.028 0.004 0.001*** 0.125 0.172 0.138 0.125 0.140 0.126 0.030 0.031 0.037 0.031* 0.018 0.020 0.022** 0.013 0.021 0.016** 0.016 0.028 0.027 0.041 0.044 0.013 0.019 0.020* 0.014 0.014 0.013 0.013 0.015 0.124

0.145 0.042 0.217 0.011 0.007 0.108 0.517 0.041 0.112 0.359 0.116 0.009 0.002 0.009 0.010 0.023 0.029 0.036 0.013 0.044 0.004 0.027 0.060 0.041 0.042 0.115 0.001 0.051 0.014 0.011 0.003 0.006 0.025 0.034 0.443 4.99 0.00 0.211 506

0.039*** 0.019** 0.051*** 0.006* 0.003** 0.192 0.221** 0.223 0.216 0.194* 0.190 0.068 0.070 0.078 0.073 0.027 0.030 0.036 0.019 0.037 0.021 0.019 0.042 0.036 0.059 0.042*** 0.018 0.034 0.032 0.019 0.019 0.018 0.017 0.019* 0.197

a The table presents OLS estimates with heteroscedasticity-robust standard errors reported in parentheses. ***, **, and *: Significance levels of 1, 5, and 10 percent, respectively. Source: Authors’ survey.

CONCLUSION Science and technology initiatives, especially the creation of science parks, have played an important strategic role in China’s recent economic development. Our interviews and surveys show women to be very satisfied with their jobs in this sector due to relatively high salaries and better work environments. Although we find evidence of gender wage differentials, there is very little perception of gender Eastern Economic Journal 2011 37


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discrimination among our interviewees or survey respondents. We do discover a significant degree of occupational segregation, which is explained by a number of factors, including perceptions of gender differentials in creativity. Understanding and addressing the factors that contribute to actual or perceived creativity differences among men and women may have significant productivity consequences. Our study demonstrates that the perception that women are relatively less creative, contributes to their underrepresentation in R&D work in S&T firms in China. More research is needed to understand whether women are in fact less creative in this work, and, if so, to identify the causes and possible remedies. Two areas of study need particular attention. First, research in the United States demonstrates that extrinsic motivation — the promise of evaluating creative work and rewarding it — reduces intrinsic motivation — the desire to be creative — among girls but not boys [Baer 1997]. Do these results hold for adults and other cultures? The answer to this question is important for China, which emphasizes performance evaluation. The second area concerns tokenism in the workplace. Our interviewees believed that exclusively male or female work environments reduce productivity. All-male groups have a tendency to ‘‘tell dirty jokes,’’ while all-female groups talk about ‘‘shopping and children.’’ To improve productivity, several managers reported diluting the (100 percent) share of the male gender by 10 percent. An important study shows that tokenism may actually reduce innovation by damaging factors crucial to creativity: psychological safety of team members and the willingness to experiment and take risks [Gratton et al. 2007].29 Our study has demonstrated that gendered perceptions of creativity — shared by men and women alike — lead to occupational segregation in the S&T sector with negative income consequences for women. A policy directed at eliminating occupational segregation must therefore address these perceptions through awareness campaigns in schools and the workplace. Actual differences in creativity can be addressed through family friendly policies that allow men and women to share the burdens of housework and child/elder care more equally. Mentoring, competitive awards, and professional conferences focused on increasing creativity could be useful. Government funding of such programs is critical to their success. Otherwise, businesses might consider them as yet another increase in costs, which in a highly competitive context, could aggravate the unfair treatment of women in the S&T sector.

Acknowledgements The University of Illinois at Urbana-Champaign provided financial support for this study. The authors are grateful to Huaiyu Wang for assistance in data collection, Andre Renaudo and Mary-Ann Guyler for research, and Guy Oakes and three anonymous referees for helpful comments and insights on earlier drafts of this paper. The usual disclaimer applies.

Notes 1 For an account of these initiatives, see Consulate General of the People’s Republic of China in San Francisco [n.d.]. 2 There is a bourgeoning literature on Z-Park, its origins, evolution, institutions, and problems. See, for example, Cao [2004]; Tan [2006]; Zhou [2005, 2008]; and Zhu and Tann [2005]. Eastern Economic Journal 2011 37


194 3 In 2005, China claimed the second highest share of high technology exports in the world, having raised its ranking from 99th in 1980 [Gallagher and Porzecanski 2008, p. 11]. 4 The literature addresses women in both academia and industry. See, for example, Bauer and Baltes [2002], National Academy of Sciences [2006] and Jacobsen et al. [2006]. 5 Rules on conducting interviews in China have been relaxed in recent years, but gender issues continue to raise flags. Although our research was focused on business, we still faced substantial challenges in obtaining interviews. Several firms that had agreed to interviews before our arrival in China withdrew because they did not want exposure to external criticism. 6 According to field interviews conducted by Ho et al. [2003], Chinese enterprises widely adopted this labor discipline scheme (muoweitaotaizhi) following property rights reforms launched in the 1990s. 7 The ACFTU was formed in 1925, crushed by the Guomintang nationalist government in 1927, revived in 1949 with the founding of the Communist China, disbanded in 1966 during the Cultural Revolution, and reinstated in the beginning of the reform period in 1976 [Economist 2008]. 8 Before the market reforms, the ACWF had representation at the firm level. Today, the ACWF is affiliated only with various levels of government without mandatory firm representation. Its main function is to promote gender equality and bring gender issues to the attention of government. 9 A Peking University study of IT firms, for example, shows that women are typically situated in HR and administration (73 percent) and marketing and finance (60 percent). They make up a small share of R&D staff (12 percent) and production workers (16 percent) [Shen and Ge 2005, p. 6]. 10 On this point, see McKeen and Bu [1998] and Kitching and Jackson [2002]. 11 A study of women IT workers captures these sentiments for women who approach the age of 40, a ‘‘turning point’’ in their careers. ‘‘The age of 40 should be the prime of one’s career with the best abilities, experience and determination. But women may find themselves lost in middle age as they fail to obtain social recognition and begin to decrease their personal commitment’’ [Shen and Ge 2005, p. 10]. Anecdotal evidence indicates that as opportunities are reduced for older women, some open their own firms. One firm in our ethnographic sample had a female CEO, office director, human resource manager, and marketing director. The average age in this firm of 15 employees (eight of whom were women) was 40. The CEO had served as a soldier in the army, a civil servant in the government, and an official in a non-governmental association, where she had networked with many experts. The marketing director was also middle-aged, having worked as a medical doctor and later marketer of pharmaceuticals before joining the firm. The company was established in 2005 and quickly obtained intellectual property rights in the area of environmental protection. It boasted of more than $120,000 of profits in its first year of operation. 12 In 2008, the Chinese government passed a law requiring union membership of all workers in China, including those working in foreign-owned firms. 13 See Drouin and Thompson [2006] for a comprehensive account of the Chinese social insurance system and its subsequent reforms. 14 Because statistics in this table are weighted by firm size, occupational shares of men and women differ somewhat from those presented in Table 1. 15 To streamline the exposition, we present only the distribution in 2006. Occupational distributions in 2004 and 2005 are similar to that for 2006. The share of female employees varied somewhat over the 3 years; it decreased moderately but steadily in Beijing from 24.1 percent in 2004 to 22.5 percent in 2006 and in Wuhan from 27.9 percent to 26.1 percent. 16 The Duncan index is equal to 0 when there is no difference in gender distributions; it is equal to 1 when women and men are completely separated. A number between 0 and 1 indicates the percentage of female (or male) workers who would have to change jobs in order to equalize the occupational distribution of men and women. 17 Some respondents provided more than one reason. 18 Relying on the estimated gender wage gap instead of the actual gap is a major disadvantage of the studies based on firm-level data. The growing availability of matched employee-employer data opens an avenue for overcoming the difficulty of collecting reliable sex-disaggregate wage information at the firm level [see Hellerstein et al. 2000]. 19 For studies that estimate the gender wage gap using similar methodology and firm-level data, see Svejnar [1984], Hellerstein and Neumark [1999], Dong and Zhang [2009]. 20 Among the explanatory variables, female share, workforce composition by occupation, assets, export share, and firm age are a panel of three observations for each firm while firm characteristics such as products, ownership, education requirements are cross-sectional information. It is plausible to assume that the products, ownership structure, recruitment policy, and union or women representation Eastern Economic Journal 2011 37


195

21

22

23

24 25 26

27 28

29

remain unchanged during the short period of investigation. As can be seen from Table 3, excluding these time-invariant variables does not substantively change the main finding of the paper. In Table 3, we present heteroscedasticity-robust standard errors. The reference group includes firms that are publicly traded, produce other products, have no minimum education requirements, have no union or women’s committee representation, do not provide training, and are located in Wuhan. The temporal reference is 2004. On the basis of data from Chinese manufacturing enterprises, Dong and Zhang [2009] find that enterprises with a larger share of female workers have lower productivity; they attribute this result to gender inequality in domestic responsibility. In the present study, we are unable to estimate the effect of female share on productivity due to data limitations. For international comparisons, see Eisler and Montuori [2007]; Helson [1990]; Pohlman [1996]; Reis [2002]; and Russ [2002]. For an examination of employment in information and communications in China, see Shen and Ge [2005]. See Eisler and Montuori [2007] and Russ [2002] for literature surveys. See, for example, Eisler and Montuori [2007]; Helson [1990]; Pohlman [1996]; Reis [2002]; and Russ [2002]. Literature suggests that under favorable circumstances, gender differences in variables crucial to creative work — mathematical and spatial skills, motivation, attitudes and aspirations, and applications of information and communication technology — can disappear altogether [Chen et al. 1997; Yu and Zhu 2000; Eisler and Montuori 2007; Gratton et al. 2007]. The statistics presented in Tables 4 and 5 are obtained from a cross-section of the respondents with one observation from each enterprise in the sample. We assume that the impacts of creativity perception on female share variables are the same for Wuhan and Beijing to streamline the exposition. In a different specification, we introduced the interactive terms between creativity perception and location dummy variables and found they were statistically insignificant. The study covered 21 companies, 100 teams (with a total membership of 1400), and 17 countries. Innovative teams came from leadership, R&D, finance and accounting, law, IT, HR, and marketing. It recommended a relatively equal gender mix in teams for achieving maximum productivity.

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