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CENTRE FOR ETHICAL LEADERSHIP

Resilience: Women’s Fit, Functioning and Growth at Work:

Indicators and Predictors

Centre for Ethical Leadership, Melbourne Business School

RESILIENCE:WOMEN’S FIT, FUNCTIONING AND GROWTH AT WORK: INDICATORS AND PREDICTORS

JULY 2012

Victor Sojo

Research Associate, Centre for Ethical LeadershipMelbourne Business School

Professor Robert Wood

Director, Centre for Ethical LeadershipMelbourne Business School

With particular thanks to Francisco Obreque and Anna GenatMelbourne Business School

©2012, Centre for Ethical Leadership.Additional owners of copy are acknowledged on page credit. Every effort has been made to trace and acknowledge copyrighted material and MBS apologises should any infringement have occurred.

This research is supported by

Resilience: Women’s Fit, Functioning and Growth at Work: Indicators and Predictors

The Gender Equality Project (GEP) is a networked organisation of industry partners, research partners and associates collaborating in pursuit of the common mission: ‘To produce a significant and sustainable improvement in the gender balance in leadership roles of participating organisations’ The underlying assumption is that a more balanced representation of men and women in leadership and decision making roles will mean that organisations are making better use of the full range of available talent and better meeting the needs of both men and women at work. Improving gender balance is both smart economics and good human rights. The GEP aims to develop new, validated and tailored solutions to address gender inequality in leadership roles of industry partner organisations. The research is focused on the mission and aligns the activities of the GEP to the needs and goals of industry partners. The GEP is an initiative of the Centre for Ethical Leadership (CEL) at Melbourne Business School, which is responsible for the management of the research and development program. All GEP members are invited to participate in six monthly workshops for the sharing and discussion of latest research findings, global best practices, case examples and other relevant information. The GEP commenced with a Planning Workshop held in April 2011, attended by industry partners, researchers and associate partners, as well as a keynote address by Sex Discrimination Commissioner, Liz Broderick, with the purpose of identifying the core research projects to be undertaken by the GEP. There are four initial core programs of relevance to all industry partners: • Unconscious Bias

• Resilience

• Targets and Quotas

• Flexible work practices These core research programs will be supplemented by projects targeted at specific issues and needs within each industry partner organisation. The Centre’s Diversity Leadership Skills Training Programs (DLSTP) is the primary training vehicle into understanding unconscious bias, how it impacts from an individual and organisational perspective, and what behaviours support or detract from gender equality in the workplace.

GENDER EQUALITY PROJECT

Resilience: Women’s Fit, Functioning and Growth at Work: Indicators and Predictors 5

CONTENTS

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Women’s Fit, Functioning and Growth at Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Predictors of Women’s Fit, Functioning and Growth at Work . . . . . . . . . . . . . . . . . . . . 7 Male-Dominated Work Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Indicators of Women’s Fit, Functioning and Growth at Work . . . . . . . . . . . . . . . . . . 10 Potential Predictors of Women’s Fit, Functioning and Growth at Work . . . . . . . . . . 11 Evaluation of the Relationships between the Potential Predictors and the Indices of Fit, Functioning and Growth for Women at Work . . . . . . . . . . . . 13

Consistent predictors of women’s fit, functioning and growth at work 13 Risk and protective factors for each of the 8 indicators for women’s fit, functioning and growth at work 14

i. Predictors of women’s fit as indexed by work attitudes, experiences of sexism and experiences 15 of sexual harassment at work ii. Predictors of women’s functioning as indexed by hiring and retention, health and performance 16 at work iii. Predictors of women’s growth as indexed by the managerial and compensation levels they achieve 17 within organisations.

Differences between Male-dominated and General Work Environment . . . . . . . . . 18 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Appendix A: Studies Used in the Meta-analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Appendix B: Categories, Variables, Description and Examples of Measures Used in Studies Meta-analysed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Centre for Ethical Leadership, Melbourne Business School6

Considering the many reported benefits of greater gender diversity, the persistent under-representation of women in leadership roles represents a significant set of lost opportunities for companies and nations. Existing strategies for increasing the numbers of women in leadership roles appear to have peaked in their impacts. In the current report we analyse indicators that are typically considered when assessing gender diversity strategies and then analyse the personal and organisational factors that predict these different outcomes. The use of these indicators and the related predictors provides an evidence-based approach, supported by results from multiple studies, for improving the effectiveness of gender diversity strategies.

A meta-analysis of 103 studies, including 46 studies conducted in male-dominated work environments and 57 in general work environments, identified eight indicators across three levels of fit (work attitudes, sexism and sexual harassment), functioning (hiring and retention, health and performance) and growth (managerial level and compensation level). The analysis also identified the strongest and most robust predictors of each indicator, which formed the evidence base for the following recommendations for organisations:

1. Conduct periodic audits of the fit, functioning and growth indicators shown in Figure 1 of this report.

2. Target the protective and risk factors that are the strongest and most robust predictors of the specific fit, functioning and growth indicators with the most significant shortfalls.

3. Ensure clear and consistent expectations for equality of treatment and opportunity are communicated through formal systems and processes and cultural activities and provide feedback on how actual work practices match expectations.

4. Target low-level sexism through a range of strategies, such as a “no just joking” policy.

5. Introduce a range of strategies for improving the performance of women through reduced sexism, and increasing the control women have over their work lives, particularly women in middle management roles, through delegation, project based tasks and flexible work.

EXECUTIVE SUMMARY


INTRODUCTION

Women remain highly under-represented in many areas of the workforce worldwide, particularly in senior leadership roles. In the USA, women make up just 15% of executive committee members in the top 101 companies (20-First, 2010) and less than 4% of the "C-level" roles of CEO, CFO, and COO in Fortune 500 companies (Jandeska & Kraimer, 2005). In the top 101 companies in Europe, only 7% of executive committee members are women, a number that drops to 3% in Asia (20-First, 2010). In Australia, women represent 15% of executive committee members in companies on the Fortune International 500 list (20-First/Egon Zehnder International, 2011) and 11% of directorship positions in ASX200 companies. 87 of the ASX200 companies still do not have a woman on their board (WomenOnBoards, 2011).

When juxtaposed against the many reported benefits of greater gender diversity (Francoeur, Labelle, & Sinclair-Desgagne, 2008; Terjesen, Sealy, & Singh, 2009), the under-representation of women in senior leadership roles represents a significant set of lost opportunities for companies and nations. Even where the benefits of gender diversity are recognised, existing strategies appear to have peaked in their impacts on the numbers of women being promoted into senior leadership roles across most organisations. However, the least progress has been made in those organisations and work environments where traditional male roles are dominant (Beckman & Philips, 2005; de Ruijter & Huffman, 2003).

In order to make a difference to the numbers of women in senior leadership roles, companies need the women recruited to fit in, perform successfully, stay with the company and progress through the ranks. One possible reason that this has not been happening at the desired rate, particularly in organisations that are more male-dominated, is that there are other factors, personal and contextual, that are influencing the effectiveness of gender diversity strategies. In achieving the desired supply of future female leaders, companies need to focus on those factors that enable women to remain healthy, satisfied and involved with their work, committed to the organisation, performing well, and able to advance in their careers. At the same time, companies’ attention needs to be given to risk factors that can undermine female fit, functioning and growth.

In the current report we present a meta-analysis of studies that have examined the characteristics of male-dominated work environments and the predictors of women’s effective fit, functioning and growth in both male-dominated work environments and work environments where women have equal or greater representation and influence (hereafter referred to as general work environments).

Human beings are resilient when they have sufficient resources available to effectively manage threatening situations. Resilient individuals are able to remain healthy and productive whilst under threat or recover relatively quickly from adversities. In the current study, women are considered resilient when they are able to fit in, function and grow in a work environment that poses risks to their well-being and performance. Fit is defined in terms of women’s acceptance by and of the workplace. It includes women’s attitudes towards work and the attitudes and behaviours of others towards them. Functioning is defined in terms of their hiring and permanence, general physical health, mental health and satisfaction with life, and their performance at work. Growth is defined in terms of women’s managerial and compensation level within organisations.

PREDICTORS OF WOMEN’S FIT, FUNCTIONING AND GROWTH AT WORK

The predictors of women’s fit, functioning and growth at work can be classified into risk and protective factors. For example, work environments that are numerically and normatively male-dominated seem to operate as risk factors for women at work. In these kinds of work contexts women show a number of negative outcomes; there is less hiring and retention of women (Fitzgerald, Drasgow, Hulin, Gelfand, & Magley, 1997; Konrad & Pfeffer, 1991) and there is a higher wage and career advancement gap between men and women (Beckman & Philips, 2005; de Ruijter & Huffman, 2003). Women’s work attitudes, such as the level of job involvement, organisational commitment and job satisfaction may be impaired (van der Velde, Bossink, & Jansen, 2003; Vinokur, Pierce, & Buck, 1999). Also, in male-dominated environments women’s performance (Sekaquaptewa & Thompson, 2003) and mental and physical health (Buchanan, Settles, & Woods, 2008; Weatherill, Vogt, Taft, King, King, & Shipherd, 2011) could be negatively affected.

On the other hand, protective factors are variables that modify or ameliorate responses to a context that would otherwise predispose individuals to a maladaptive outcome (Rutter, 1985). These factors also promote better functioning and growth in adverse contexts. The protective factors that promote women’s fit, functioning and growth are those factors that help women remain healthy, satisfied and involved with their work, committed to the organisation, performing well, and able to advance in their careers and salaries. In the current meta-analytic study those protective factors are considered variables that build resilience.

WOMEN’S FIT, FUNCTIONING AND GROWTH AT WORK


MALE-DOMINATED WORK ENVIRONMENTS

Many, but not all, of the risk factors for women’s functioning and growth at work have been identified through the study of male-dominated work environments. The risk factors of sexism, sexual harassment and stereotype threat, for example, are key characteristics of what has been described as a work environment with normative male dominance (de Haas & Timmerman, 2010; Rivardo, Rhodes, Camaione, & Legg, 2011; Settles, Cortina, Stewart, & Malley, 2007). Male-dominated work environments have been studied in a wide range of roles and contexts, including management, information technology (Wentling & Thomas, 2009), natural sciences and engineering (Fitzgerald et al., 1997; Settles et al., 2007), armed forces (Fitzgerald, Drasgow, & Magley, 1999; Newell, Rosenfeld, & Culbertson, 1995), law firms (Beckman & Philips, 2005; Guthrie & Roth, 1999) and medicine (Gerdes, 1995; Settles et al., 2007), among others.

The characterisation of a work environment as male-dominated includes not only the numerical dominance of men but also considerations of differential power. The sources of differential power may be positional, such as when men are more strongly represented in the higher levels of the organisation (Beckman & Philips, 2005), or more structural and cultural, such as when formal and informal practices are discriminatory or derogatory towards women (Fitzgerald et al., 1999). For instance, in a law firm there might be similar numbers of men and women working as lawyers, but females are more highly represented at the entry level while men make up a larger proportion of partners and therefore have greater positional power than women (Kay & Hagan, 1998).

The lack of representation of women in senior leadership positions in most companies means that decision rights are exercised through a male perspective. This could hinder women’s hiring and promotion without that being the intention (Gorman, 2005). Power imbalances between men and women have also been found to influence a range of negative outcomes for women, including inequality of opportunities for advancement (Heilman, Wallen, Fuchs, & Tamkins, 2004), over-performance demands (Rosin & Korabik, 1991), stereotype threat (Stangor, Carr, & Kiang, 1998), a general permissiveness for sexual bravado, sexual posturing and denigration of feminine behaviour (de Haas & Timmerman, 2010), sexual harassment (Buchanan et al., 2008) and a general lack of social support (Lyness & Thompson, 1997).

It is possible to compare the impact of male-dominated environments on women’s fit, functioning and growth with the impact of general environments. Studies conducted with women working in industries that are considered to be both numerically and normatively dominated by men (e.g., women working in natural sciences, engineering, medicine, police forces, military forces, information technology, law firms or financial services) have been compared with studies conducted on women working in contexts where there is no perceived disparity in numbers and dominant culture between men and women, or where there is a dominance of women (e.g., social sciences, teachers, nurses or general samples). This comparison will help us to understand whether occupational context has a differential impact on any of the identified predictors of women’s fit, functioning and growth.

METHOD

The studies used in this meta-analysis were required to satisfy several criteria. They were required to include an empirical study of relevant criteria for women’s fit, functioning or growth at work that was published in a peer-reviewed journal. The studies also were required to report results for women such as correlations or other statistics (e.g., t, Cohen’s d) that could be converted into an effect size for inclusion in the meta-analysis, separately from results for men.

Electronic and manual searches according to the above criteria found a total of 356 journal articles. Those 356 journal articles were further evaluated to exclude those that did not report the required statistics. This process produced 88 studies with 103 independent samples. Of these 103 independent samples, 46 came from studies conducted in typical male-dominated environments (e.g., women working in engineering, medicine, police forces, military forces, natural sciences, information technology, law firms or financial services), and 57 came from samples of women in general work environments (e.g., women working as school teachers, social workers, nurses, social sciences, and general samples of workers from different areas).

Table 1 shows a disaggregation of the studies included in the meta-analysis. The references for all the studies meta-analysed are provided in Appendix A. Most of the studies from general environments (42 studies) were surveys that included a variety of occupational sectors (e.g., manufacturing, services, public and private sectors, education, health, etc.). Studies of male-dominated work environments included samples from the armed forces, financial services, law firms and physical and life sciences (e.g., mathematics, physics, chemistry, biology, etc.).


Table 1. Number of independent samples meta-analysed by occupational sector

Work context K

General Education, arts and social sciences graduates 2

Mix from university academics 1

Mix from different occupational sectors 42

Mix from female-dominated areas 1 (e.g., early childcare, hairdressing)

Newspaper employees 1

Nurses and health care support staff 3

Mix from public sector / government employees 3

School teachers and staff 1

Secretaries 1

Mix from university employees 2

Total General 57

Male-dominated Armed forces 9

Construction and utilities 2

Extraction industries 2

Farming 1

Financial services 6

Formal, physical and life sciences 13

IT 2

Law firms 6

Manufacturing 1

Mix from male-dominated areas (e.g., finances, manufacturing, engineering, medicine) 3

University staff (1978-1983) 1

Total Male-dominated 46

The 88 articles provided around 140 indicators of women’s fit, functioning and growth at work, and more than 500 potential predictors. These indicators and predictors were organised into higher-level categories based on their classifications in industrial and organisational psychology (Borman, Ilgen, Klimoski, & Weiner, 2003; Jex, 2002) and occupational health research (Antoniou & Cooper, 2005; Schabracq, Winnubst, & Cooper, 2003). In cases where it was not considered conceptually appropriate to categorise variables they were left independent (See Kinicki, McKee-Ryan, Schriesheim, & Carson, 2002; McKee-Ryan, Song, Wanberg, & Kinicki, 2005, for similar approaches). The categorisation process, which was conducted by two independent researchers, yielded 8 categories of variables for indicators and 11 categories of variables for predictors. The definitions and examples of measures for each of the categories of variables for the indicators of women’s fit, functioning and growth at work are provided in Table B1 in Appendix B. Definitions and example measures of the predictors of women’s fit, functioning and growth are presented in Table B2 in Appendix B.

Table 2. Number of independent samples meta-analysed by country Country K

Australia 7

Canada 14

Finland 2

Germany 1

Malaysia 2

Singapore 1

Norway 1

The Netherlands 5

United Kingdom 7

United States of America 63

Total independent samples 103

Table 2 shows the disaggregation of the 103 independent samples by country. More than half of the studies were conducted with participants from the United States of America, followed by Canadian samples and then by participants from Australia and the United Kingdom.


The final sample of independent effect sizes included 1112 data points. In the cases where there were multiple measures for a variable within a study or where effects from the same sample of participants were reported for different points in time, effect sizes were averaged and included as a single independent effect size in the final sample to prevent double counting. All the variables were coded so that a higher number reflected more of the variable as defined by a category, meaning that in some cases correlation signs were reversed to make them consistent with the other outcomes or predictors in the same category (e.g., correlations with measures of anxiety and depression were reversed so that they would be consistent with the other variables in the category of health).

The calculations converted all effect sizes into a common statistic r (see Borenstein, Hedges, Higgins, & Rothstein, 2009 pp.45-50 for a list of transformation formulas). Sample-size weighted mean effect sizes were computed using random models. 95% confidence intervals and Q were calculated for each mean effect size, with both used as indices of the variability of the effect sizes (Borenstein et al., 2009). The 95% confidence interval provides information about the significance of an association (when the interval crosses the zero point the association is not significant). Q is an index of variability of the effect sizes that could indicate the presence of a moderator of the studied association (all Q indices in these analyses were nonsignificant). The reported magnitudes of significant effects are based on Cohen’s (1988) categorisations: small effect sizes are r < .29, medium effect sizes are .30 < r < .49, and large effect sizes are r > .50.

Indicators of Women’s Fit, Functioning and Growth at Work

The eight categories of indicators identified in the analyses are presented in Figure 1. They are organised into three levels covering fit, functioning and growth. The top level includes factors that indicate whether women are growing and thriving in their work environment (i.e., women’s compensation level and managerial level). In the middle level are indices of everyday functioning at work (i.e., women’s performance, hiring and retention, and health). At the bottom level of the figure there are attitudinal factors that relate to women’s fit with the culture and work context (i.e., work attitudes and the attitudes and behaviours of other workers towards women, specifically sexist climate and sexual harassment). These three levels are hypothesised to be

RESULTS

intimately related, with reciprocal effects on each other.

Work attitudes, sexist climate and sexual harassment are included as both indicators and predictors in the analyses. They are included as indicators of fit because:

• sexist climate and sexual harassment are key elements in the definition of a male-dominated work environment

• women’s work attitudes have been shown to be related to the overall level of well-being experienced by women and their colleagues at work (Parasuraman, Greenhaus, & Granrose, 1992).

They are also included as predictors because they:

• have been studied as variables that could impact on women’s functioning and growth at work (Buchanan et al., 2008; Jandeska & Kraimer, 2005; Rosin & Korabik, 1991)

• are related to other important organisational variables such as work stress (Golderhar, Swanson, Hurell, Ruder, & Deddens, 1998; Morrow, McElory, & Phillips, 1994) and the formal and informal practices that take place every day in organisations (Heilman et al., 2004; Parker & Griffin, 2002).

They are also related to one another. For example, in organisations where sexist remarks are permitted it is more likely to also observe sexual harassment (de Haas & Timmerman, 2010; Fitzgerald et al., 1997). Thus, while work attitudes, sexist climate and sexual harassment are discussed as indicators of fit in this section, they are also discussed as predictors of the five indices of women’s functioning and growth at work (i.e., managerial level, compensation level, performance, hiring and retention and health).


Potential Predictors of Women’s Fit, Functioning and Growth at Work

The eleven categories of potential predictor variables indentified in the analyses are shown in Figure 2. They are organised along two axes that distinguish the categories by levels of analysis and type of variables. The horizontal axis, shown at the top, differentiates between categories for individual worker level variables on the left (e.g., human capital) and organisation level variables on the right (e.g., organisation formal practices). The vertical axis, shown on the right side of the figure, differentiates between demographic factors at the top (e.g. personal and organisational demographics) and behavioural and attitudinal factors in the middle and bottom sections (e.g., job demands and work attitudes). Macro-level societal factors are shown in the middle top section

(i.e., labour market characteristics) and psychosocial and informal factors are shown in the middle bottom section (e.g., sexism at work, organisation informal practices). These latter categories are presented in the middle section because they are a product of the relationship between the organisation and the workers.

Within the categories, sets of potential predictors that are surrounded by dotted rectangles belong to the same family and operate as predictors in the same way. For example, under 9. Personal supports and demands, General family stress, Family – work conflict, Marital stress, and Parental stress are all stressful events that are originated in the family sphere of the individuals studied. In this meta-analysis, results for each of those stressful events were analysed individually, and also as the summary variable Family stress.

Figure 1. Taxonomy of indices of women’s fit,functioning and growth at work

Indices of Growth

Indices of Functioning

Indices of Fit

•Managerial advancement •Women as managers1. Managerial Level

•Yearly salary •Hourly salary2. Compensation Level

•Implicit and explicit learning on expected task •Math performance •Transfer task learning •Work performance

3. Performance

•General health •Mental health: anxiety, depression, post traumatic stress disorder (-) •Physical health •Satisfaction with life

5. Health

•Hiring •Pursuing non-traditional occupations •Women in core job •Job tenure •Organisational tenure •Professional involvement •Absenteeism (-) •Intention to leave the organisation (-)

4. Hiring and Retention

•Career satisfaction •Job involvement •Job satisfaction •Organisational commitment

6. Work Attitudes

•Perceptions of achievement-related attributes (-) •Non-acceptance of women •Sexist organisational climate •Tolerance of sexualharassment

7. Sexist climate

•Sexual coercion •Unwanted sexual attention •Crude behaviour8. Sexual Harassment


1. Labour market characteristics

•Industry prosperity

•Regional prosperity

•Supply of prospective employees

•Occupation wage range

•Level of education for job

2. Organisation demographics

•Age of the organisation

•Business vs. other organisations

•Government vs. other organisations

•Industry type

•Organisational resources

•Size of organisation

•Number of managerial jobs

•% of professional or skilled employees

•Average salary for the job

•Job type

3. Organisation formal practices

•Formalisation of personnel practices

•Precision of information about performance

•Comfort with candidates for promotion

•Internal hire for promotions

•Opportunities for development

•Support for advancement

•Training and development

4. Work supports and demands

•Job networks and support

•Organisational support for parents

•Work balance

•Control over work life

•Hours of work per week

•Role reduction

•Work – family conflict

•General work stress

•Job insecurity

•Job monotony

•Overperformance

•Work overload

5. Organisation informal practices

•Collectivistic culture

•Competition and task- focused culture

•Perceived cultural fit

•Organisational climate

•Description of competence

•Description of likability

•Minorities as managers

•Minorities in the organisation

6. Sexism at work

•Sexist climate

•Sexual harassment

•Stereotype threat

7. Women at work

•Women as managers

•Women in core job

•Women working in the area

•Women as subordinates

8. Work attitudes

•Career satisfaction

•Job involvement

•Organisational commitment

•Job satisfaction

•Satisfaction with co-workers

•Satisfaction with supervisor

•Satisfaction with salary and ranking

9. Personal supports and demands

•Family balance & support

•Family interest for work & education

•Family centrality

•Family demands

•Family – work conflict

•General family stress

•Marital stress

•Parental stress

10. Human capital

•Education

•Prestige of attended university

•Work experience

•Employer change

•Job Change

•Agency

•Task orientation and analytical skills

•Gender-role egalitarianism

•Importance of having a career

•Dispositional resilience

•Interpersonal oriontation

11. Personal demographics

•Age

•Age dependent children

•Having children

•Marital status

•Martial tenure

•Dual career relationship

•Race

•Socio-economic status

Potential predictors of women’s resilience at work

Figure 2. Taxonomy of potential predictors of women’s fit, functioning and growth at work

Dem

ographic factors B

ehavioural / A

ttitudinal factors

Worker factors Organisation factors


Evaluation of the Relationships between the Potential Predictors and the Indices of Fit, Functioning and Growth for Women at Work Identification of the predictors with the most consistent positive or negative effects on women’s fit, functioning and growth assists organisations with:

• addressing the most significant determinants of effective gender diversity strategies

• considering effective strategies for the promotion of women into leadership roles

• tackling more specific problems related to a particular indicator.

For example, in some organisations, problems relating to the fit and functioning of women may have been successfully addressed, but problems regarding women’s growth persist. In such organisations the predictors of the two growth indicators would be of most interest when seeking to understand why particular strategies for solving this problem have not been effective.

In this section we focus specifically on the significant, strongest and most robust predictors of the 8 indicators of fit (three indicators), functioning (three indicators) and growth (two indicators). The robustness of a relationship between indicator and predictor was based on the:

• number of studies reporting the relationship

• number of indices of fit, functioning and growth that were significantly related to a predictor

• strength of the mean effect size for the relationship The full set of relationships between all predictors and indicators of fit, functioning and growth of women at work are available in the longer technical report of this study.

We first report the summary results for all the most robust and strongest predictors across all 8 indicators of fit, functioning and growth and then report the top 5 predictors for each of the 8 indicators separately.

In the two sections that follow, the predictors are identified as either protective or risk factors. Protective factors are those that have a positive relationship with the indicators and, therefore, can be interpreted as enhancing the fit, functioning or growth of women at work. Risk factors are those that have a negative relationship with the indicators and, therefore, can be interpreted as reducing or undermining the fit, functioning or growth of women at work. Effective gender diversity strategies will be those that increase the protective factors and reduce the risk factors either as the main focus or as part of a strategy that targets other areas of change.

Consistent predictors of women’s fit, functioning and growth at work

The list of predictors is organised into four categories, with predictors either being protective factors or risk factors and corresponding either to organisational factors or to personal factors (see Figure 2 for this categorisation of predictors). That way the predictors could be arranged in a 2 x 2 matrix, as illustrated in Table 3, deriving the following four categories:

1. Organisational risk factors – OR

2. Personal risk factors – PR

3. Organisational protective factors – OP

4. Personal protective factors – PP.

Table 3. Matrix of factors predicting women’s fit, functioning and growth at work

Figure 3 provides a summary of the strongest predictors of women’s resilience at work. Only those predictors that were related to three or more indicators of women’s fit, functioning and growth at work have been included. In each section in Figure 3, factors are organised based on:

(i) their correspondence to personal or organisational factors

(ii) the number of studies supporting the association (minimum of 10)

(iii) the number of different indices of women’s fit, functioning and growth at work with which the factor was associated (minimum of three).

Factors at the top of each one of the four sections were supported by more studies and were related to more indices of women’s fit, functioning and growth at work.

Four variables operated as organisational risk factors for three or more indices of women’s resilience at work. In order of relevance and based on the consistency of the evidence, being a victim of sexual harassment and working in a sexist environment were clear risk factors for women at work. These factors were negatively related to at least five of the other six indices of women’s growth, functioning and work attitudes. Also, general work stress (e.g., ambiguity, lack of control and responsibility, work overload) and feeling that their job interferes with their personal activities operated as risk factors for four and three different indices of women’s resilience, respectively.

Family - work conflict (i.e., the perception that family responsibilities interfere with performance at work) was the only personal risk factor with consistent results, being associated with three indices of women’s resilience at work.

Factors Organisational Personal

Risk 1. OR 2. PR

Protective 3. OP 4. PP


More opportunities for development (e.g., assigning tasks that will foster the career of the employee) and control over work life (e.g., voice and latitude of decisions around how to organise their work) were the main organisational protective factors for women’s resilience at work, each being associated with five indices of women’s resilience. A rich job network and social support and a positive organisational climate were each associated with four indices of women’s resilience. Finally, having women working in the organisation or sector in general, and working in an organisation with formalised, fair and transparent personnel management practices were

Risk and protective factors for each of the 8 indicators of women’s fit, functioning and growth at work In this section, the first summary corresponds specifically to the predictors of women’s fit at work (i.e., women’s work attitude, sexist climate and sexual harassment). The second summary relates to the predictors of women’s functioning at work (i.e., hiring and retention, performance, and health). Finally, the third summary covers the indices of women’s growth at work (i.e., managerial level and compensation level).

The summary correlations (i.e., summary effect sizes) between specific predictors and the indices of fit, functioning and growth are presented in bar-graphs.

Protective Factors Risk Factors

Women’s Fit,Functioningand Growth

•Opportunities for development

•Control over worklife

•Job network and support

•Organisational climate

•Women working in the area

•Formalisation of personnel practices

•Age

•Dispositional resilience

•Job satisfaction

•Work experience

•Organisational commitment

•Sexual harassment

•Sexist climate

•General workstress

•Work - family conflict

•Family - work conflict

OP

PP

OR

PR

Figure 3. Organisational and Personal Protective and Risk Factors for Women’s Fit, Functioning and Growth at Work.

factors positively associated with three indices of women’s resilience. In terms of personal protective factors, the age of the participants and their personal resilience were both positively associated with five indices of women’s resilience at work. The level of job satisfaction was associated with four indices of functioning and growth of women at work. Finally, women’s work experience and their organisational commitment were each positively associated with three indices of women’s resilience.

These summary correlations were transformed from their original form in a scale from 0 to ± 1 to a scale from 0 to ± 10. Green bars toward the right side of the figure (i.e., above zero) show predictors that operate as protective factors. Red bars to the left of the centre show the predictors that act as risk factors. The interpretation of the strength of the correlations was based on Cohen’s (1988) classification: bars from 0 to 2.9 units in length (r < .29) represent small effects, bars from 3 to 4.9 units in length (.30 < r < .49) indicate medium effects, and bars equal or larger than 5 units in length (r > .05) indicate a large effect size.


i. Predictors of women’s fit as indexed by work attitudes, experiences of sexism and experiences of sexual harassment at work

Figures 4, 5 and 6 show the five strongest and most robust predictors of women’s positive attitudes towards work, their experiences of sexism and their experiences of sexual harassment respectively, all of which can influence their overall feelings of acceptance by and satisfaction with their colleagues, supervisor, staff and others in the organisation. Across the three sets of indicators of fit, measures of organisational climate provided the strongest and most consistent protective factor. Women fit better in organisations where there are common, positive understandings of norms and expected behaviours and shared perceptions that these norms and behaviours are enacted in line with expectations. The importance of the clarity and consistent promotion of expectations is illustrated in the finding that women had more positive attitudes and experienced less sexism in teams and organisations with greater formalisation of personnel practices (Heilman et al., 2004; Wallace, 2001). As with the shared understanding and perceptions of organisation climate, formalisation of personnel practices should produce greater clarity and consistency of expectations than informal practices which allow for greater discretion and subjectivity in decisions that can impact on women’s opportunities and achievement at work.

Further support for the importance of the clarity of expectations as a general determinant of fit is the finding that the robust predictors of women’s positive work attitudes, shown in Figure 4, included two seemingly contradictory dimensions of culture; the degree of competition and task focus (Fitzgerald et al., 1999) and the level of collectivism (Jandeska & Kraimer, 2005). The fact that two different, even opposing measures of culture both relate to positive work attitudes suggests that it is the clarity of expectations and not the actual dimension that determines women’s work attitudes. Women can fit well in either competitive, task-focused cultures or more collaborative environments as long as there are strong and clear expectations about the relevant norms and behaviours.

The finding that job monotony undermines positive work attitudes such as job satisfaction and job involvement is not expected to be unique to women (Grandey, Cordeiro, & Crouter, 2005).

Of note, women are much more likely to experience sexism and sexual harassment than men (Australian Human Rights Commission, 2008), and the effects can be quite debilitating for women’s performance and well-being (Miner-Rubino, Settles, & Stewart, 2009; Schmader & Johns, 2003). Sexism and sexual harassment are also much stronger determinants of women’s fit than general work attitudes, which can themselves be affected by experiences of sexism and sexual harassment.

-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6

Risk Protective

Competitive & task focused culture

Organisational climate

Formalisation of personnel practices

Collectivistic culture

Job monotony

Work Attitudes

Figure 4. Protective and Risk Factors for Women’s Work Attitudes

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Risk Protective



Control over work life

Women working in the area

Sexism

Figure 5. Protective and Risk Factors for Women’s Experience of Sexism

In addition to the clarity of expectations, which influences all measures of fit, the number of women working in a given area and the degree of control that women have over their work life are both important and robust predictors of the fit indicators that assessed women’s experiences of sexism and sexual harassment (de Haas & Timmerman, 2010; Settles et al., 2007). Sexism and sexual harassment are often power plays by one person over another; the results reported here specifically relate to the power of men over women. Women who lack control over the decisions, resources, allocations of their time, and other factors that make up their daily work life are necessarily more dependent on the people who control those factors. The fact that older women are less likely to experience sexual harassment (Figure 6) is consistent with this argument in that age


-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6

Risk Protective




Age

General work stress

Sexual Harassment

Figure 6. Protective and Risk Factors for Women’s Experience of Sexual Harassment

and seniority are highly correlated in most organisations (Rosin & Korabik, 2001). While a 50-year-old female board member may not be fully protected against sexism and harassment, she is much less likely to experience them than a 25-year-old junior member of a work team in a male-dominated work environment.

The other protective factor against both sexism and sexual harassment is having more women working in an area (de Haas & Timmerman, 2010). The presence of more women working in an area, particularly in senior leadership roles, can counter the imbalance of power between men and women in different ways. Firstly, if the senior manager with the greatest power is a woman, then the male-female dimension of the power imbalance that can lead to sexism and sexual harassment is removed. Also, as the number of women working in an area increases, the dominant culture shifts and male cultural traits that are associated with sexism and sexual harassment are diluted in their effects.

ii.Predictors of women’s functioning as indexed by hiring and retention, health and performance at work

The predictors of the indicators of women’s functioning at work are shown in Figures 7, 8 and 9 for hiring and retention, health, and performance respectively. Across the three figures some common protective and risk factors are indicated for both hiring and retention and health, which suggests that common considerations influence women’s health and their decisions to stay in a particular role or organisation. These include conflicts between work and family demands, general levels of stress at work and a woman’s personal resilience in coping with these factors (Demerouti, Bakker, & Schaufeli, 2005; Noor, 2004; Wallace, 2001). Family – work conflict and stress encourage women to leave their organisations and have a negative impact on their health if they stay. Women with stronger personal resilience are both more likely to stay and are less likely to suffer ill health if they do.

Performance is influenced by a different set of factors from the other two measures of functioning. The lack of studies that have included measures of performance meant that there were only two factors, one risk factor and one protective factor, which satisfied the criteria for inclusion as strong and robust predictors.

Women successfully seek employment and stay in organisations for a combination of personal and organisational reasons. Two of the personal factors that influence commitment to the organisation are the importance of a career to the woman and her personal resilience in dealing with the challenges and setbacks of working life (Smart, 1998; Wallace, 2001), which may extend to coping with the challenges of sexism and sexual harassment. These two factors represent the motivation and capability factors that are often used as explanations for women’s lack of success in organisations, such as “she lacks the fire or ambition” and “women have to be able to cope with the demands of leadership if they want to be successful”.

Additionally, women are more attracted to and more likely to stay with organisations that offer more developmental opportunities.

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Risk Protective

Importance of having a career

Opportunities for development

Dispositional resilience

General work stress

Family - work conflict

Hiring and Retention

Figure 7. Protective and Risk Factors for Women’s Hiring and Retention

Stress arising from family and work conflicts and work demands are risk factors for both women’s hiring and retention and their health at work (Parker & Griffin, 2002). Health is also better when women are able to achieve balance between their work and family commitments. The greatest risk for women’s health is general family stress due to issues such as strains in family relationships, children’s schooling, relationship problems, illness and disabilities of family members and ageing parents (Hammer, Cullen, Neal, Sinclair, & Shafiro, 2005). However, it is possible to observe that the negative associations of occupational stress with women’s retention and health are similar in strength to those of personal stress.


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Risk Protective

General family stress

Work - family conflict


Work Balance

General work stress

Health

Figure 8. Protective and Risk Factors for Women’s Health

Fewer studies have included a performance measure than other measures of fit, functioning and growth. In the studies that did include a measure of performance, only two factors, stereotype threat and control over work life, satisfied the requirements to be included as a strong and robust predictor. These predictors are detailed in Figure 9. Figure 9 also shows three protective factors in light grey that had significant relationships with performance but were only included in one or two studies. These were organisational climate, number of women in core jobs and the effort the organisation places on formal training and development.

The biggest risk factor for women performing effectively in their roles is the level of stereotype threat that they experience in their daily work life (Schmader & Johns, 2003). Stereotype threat occurs when the gender of a woman is drawn to attention, typically in negative ways that lead her to question or doubt her suitability for a role or task or to ruminate on the intentions of the person who made the remark. Sexism, sexual harassment and work - family conflict all increase the incidence of stereotype threat for women at work. The number of women in the area reduces the threat.

The level of control that women have over the decisions and factors that shape their work life was identified as a strong and robust protective factor for women’s performance (Figure 9). The greater self-determination that women are able to exercise in relation to their daily work lives, either because of job design, less authoritarian leadership or their own seniority, the more effectively they perform at work (Brass, 1985; Settles, Cortina, Malley, & Stewart, 2006).

-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6

Risk Protective

Stereotype threat



Women in core job

Training and development

Performance

Figure 9. Protective and Risk Factors for Women’s Performance

iii. Predictors of women’s growth as indexed by the managerial and compensation levels they achieve within organisations.

Once women feel they fit and they are functioning effectively, organisations need to ensure that women’s progress into senior leadership roles is not impeded. Many organisations have made significant progress in increasing the numbers of women in the lower and middle ranks without achieving the same success in the progression of women into senior leadership ranks. Predictors for the two studied indicators of women’s progression or growth, compensation level and managerial level, are shown in Figures 10 and 11, respectively. The results show that both merit and non-merit based factors contribute to the successful progression of women in organisations. The results in Figures 10 and 11 also challenge some of the conventional beliefs about merit and why women often don’t make it to senior leadership positions, as outlined in Whelan and Wood (2012).

The two merit-based variables, level of education and work experience, were significant predictors of both sets of indicators of women’s growth. However, they were not always the strongest predictors as would be expected if promotion and compensation decisions were strictly merit based (Tharenou, 1999; Tharenou, Latimer, & Conroy, 1994). Further, education was a stronger predictor of both female compensation level and managerial level than work experience. Given that work experience is a more proximal predictor of merit, and a more commonly used criterion for all but entry-level positions, this suggests that women are either not getting the required experience to capture growth opportunities or that their work experience is not valued as heavily as an indicator of capability.


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Risk Protective

Education


Work experience

General stress

Size of the organisation

Compensation Level

Figure 10. Protective and Risk Factors for Women’s Compensation Level

Non-merit predictors of women’s compensation levels include dispositional resilience, general work stress (which is most likely a product rather than a cause of compensation) and the size of the organisation in which they are employed (Melamed, 1996; Tam, 1997; Wallace, 2001). The general rule that bigger organisations pay higher salaries also applies to women (although women might therefore claim that they would like more opportunity to earn the aforementioned higher salaries). Non-merit predictors of progress through managerial levels include the numbers of women working in the area, opportunities for development that can prepare them for more senior roles and racial status (Buchanan et al., 2008; Cohen & Huffman, 2003; Metz & Tharenou, 2001). Women who are members of a minority are less likely to progress to more senior levels than their white female counterparts (Buchanan et al., 2008; Lyness & Thompson, 1997; Settles et al., 2007).

As can be seen in Figure 11, the strongest predictor of progress to senior leadership roles was the number of women working in an area. This is likely to result from two factors. First, as an organisation starts to gain experience with women in more senior leadership roles and others observe them being successful, there is a greater willingness to promote women. The second possible pathway is that as the number of women increases, the male stereotypical view of leadership becomes less dominant and exerts less influence through conscious or unconscious bias against the selection of women into senior leadership roles. The large numbers of ASX200 companies with no women on their board and the small percentage of women on executive boards (WomenOnBoards, 2011), suggest that significant increases in the numbers of senior female leaders are still a long time away. Coupled with the number of non-merit based predictors of women’s compensation and managerial levels, this data could be used as an argument for gender quotas as a temporary measure for increasing the numbers of women in senior roles.

Differences between Male-dominated and General Work Environments

An analysis was conducted to establish if there were differences in the risk factors and protective predictors of women’s fit, functioning and growth between male - dominated and general work environments. Only one predictor differed in strength between the two contexts. Interest in a career, whilst positively related to fit in both types of work environments, was significantly more strongly related in male-dominated work environments than in general work environments. Thus, while career motivation is always related to fit, functioning and growth, it appears that to fit in a male-dominated work environment, a woman has to really want to succeed.

One other comparison between the two environments almost reached significance. The negative association between work - family conflict and women’s retention was stronger in male - dominated environments than in general work environments. The level of conflict women experience between their occupational role and their personal/family role seems to have a stronger negative impact on women’s retention in male-dominated work environments than in general work environments.

Interestingly, there were several predictors that were expected to but did not differ in their effects on fit, functioning or growth between male-dominated and general work environments. The number of women working in the area had a negative association with perceptions of a sexist work environment in both male-dominated and general work environments. Thus, it appears that increasing the number of women who work in relationships with one another has beneficial effects irrespective of the more general work environment in which they operate. Additionally, in both male-dominated and general work environments women who perceived their work context to be sexist and who had experienced sexual harassment also had more negative work attitudes. Finally, women in the less powerful, lower levels of the organisational hierarchy perceived a more sexist organisational climate irrespective of the broader context in which they worked.

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Risk Protective



Level of education for job

Race (1=minority)

Work experience

Managerial Level

Figure 11. Protective and Risk Factors for Women’s Managerial Level


The preceding reporting of results begs an important question for the practical manager who wants to know, “What should I do to help women stay happier and healthier, perform better and successfully progress within my team, unit or organisation?” This question can be answered at a few different levels from the results of this research.

The results of the meta-analysis point to several potential areas of focus for organisations seeking to promote greater gender diversity through the recruitment, retention and promotion of more women. Our focus has not been on specific gender diversity strategies such as recruitment processes, maternity leave policies, targets and quotas, networking or support groups. Instead, in response to the lack of satisfactory progress or decreasing returns from these strategies, we focused on personal and organisational factors that impact on the outcomes of those strategies, including the fit, functioning and growth of women in organisations. These protective and risk factors act as facilitators or inhibitors for the effectiveness of gender diversity strategies.

For example, increases in the numbers of women in the workforce may be achieved through targeted recruitment and selection processes. However, if the female recruits experience a poor fit because of attitudes and norms in the dominant culture, they may develop negative attitudes towards their work and the organisation, underperform and then leave. This commonly occurring cycle of events will often reinforce beliefs within the organisation that targeted recruitment and selection leads to selection of substandard (female) candidates or that women in general are not cut out for the available roles. When some women cope and stay, this can often reinforce a belief that the women who leave cannot handle the pressures of the job. Hopefully, the findings in this report will encourage organisations to look beyond the individuals and specific diversity strategies to consider the organisational and personal predictors of women’s fit, functioning and growth and how those might impact on the effectiveness of individuals and gender diversity strategies.

The point needs to be stressed that most protective and risk factors that can be influenced by the organisation are not specific to industry or organisation type. They will have the same effects in banks, mining companies and hospitals, even if the levels of those factors differ between those organisations. One standout exception is women’s commitment to a career. Mining companies, law firms, police departments and other male-dominated environments may gain greater benefit from investments in convincing women that a career in their organisation is a desirable goal to pursue. This is particularly important during the recruiting phase and in the early stages of their careers, prior to major career or family decisions being made (e.g., promotional considerations or maternity leave).

DISCUSSION

We present and discuss five recommendations. Recommendations 1 and 2 provide guidance on how organisations could use the evidence from the meta- analysis to address the problems of recruiting, retaining and promoting more women. Undertaking the recommended actions will provide organisations with their own generative capacity to deal with gender inequality as a dynamic process and to adapt to the changing circumstances of their experiences with different strategies. Recommendations 3, 4 and 5 provide specific guidance on how to influence what we, the authors, believe are critical indicators of fit, functioning and growth.

1. Organisations should conduct periodic audits of the eight fit, functioning and growth indicators shown in Figure 1 of this report. One of the important products of the meta-analytic review is the categorisation of indicators for fit, functioning and growth, which are also the outcomes that are sought through gender diversity strategies. Audits and integrated reviews of the full set of eight indicators, many of which will already be assessed through existing data collection methods such as surveys, staffing reports, compensation audits and the like, can help provide a more complete picture of the impacts and shortfalls of existing strategies plus problem areas to be targeted. In many companies, discussions tend to focus on one or a limited set of indicators and, therefore may only uncover one part of the problem. Evaluation of the full set of indicators will provide a more comprehensive and deeper understanding of the issues and uncover ideas about how they might be addressed. Furthermore, whilst organisations often pursue solutions through the identification of what has worked elsewhere or what is considered best practice, an investment in understanding the problems specific to their own organisation is a better starting point. 2. Organisations should target the strongest and most robust predictors of the specific fit, functioning and growth indicators found to have the most significant shortfalls in the audits. Organisations should take an evidence-based approach when attempting to improve the fit, functioning and growth of women in their organisations. Single studies and recommendations of specific programs without supporting evidence are less likely to produce the desired changes than predictors that have been shown to be related to the required outcomes across multiple studies, as reported here. There are a few particular indicators and their strongest predictors that we believe organisations should target. These are the focus of recommendations 3, 4 and 5.


3. Organisations should clearly and consistently communicate expectations for equality of treatment and opportunity through their formal systems and processes, cultural activities and climate surveys. Organisations should also ensure that work practices are consistent with those expectations, (e.g., including evaluating work practices and providing feedback on how they match expectations).

One of the few axioms in modern management is that clarity of expectations and feedback on performance against those expectations leads to improved performance and effective behaviour change (Wood, Whelan, Sojo & Wong, 2012). In organisations, expectations and feedback are communicated in many different ways, including through processes such as recruitment, selection, performance management and rewards, through frameworks such as leadership competencies and values statements, and through the daily actions of leaders and peers. These various modes of communication of expectations and feedback define the context for organisational change initiatives such as a gender diversity strategy. However, organisations rarely consider how a particular strategy is related to or impacted by these contexts. Gender diversity strategies need to be aligned with the expectations communicated by existing organisational systems, processes and practices which may themselves need to be changed to achieve alignment.

4. Organisations should improve fit for women by targeting low level sexism through a range of strategies such as a “no just joking” policy. The most pervasive and pronounced fit indicator that was a predictor of the levels of functioning and growth for women in organisations was sexism, in its different manifestations.

Sexism refers to low-level sexual humour, sexual slang and comments targeted at gender. Examples, respectively, might include, “Jill will make the tea”, “Mary has a great body (or other references to the specifics of the female anatomy)” and “Congratulations on your promotion, Jenny, it is great that our gender diversity strategy is working, even if some qualified men have to miss out.” Remarks such as these are often not recognised as sexism, even though in some jurisdictions they are legally defined as sexual harassment. Studies by VicHealth (2012) show that these types of sexist remarks are much more wide-spread than more overt, physical or aggressive acts of sexual harassment, which have been targeted and significantly reduced in most organisations.

If women do not feel that they fit and are accepted as equals by their colleagues, they are less likely to stay in the role or organisation. If they do stay, both their

performance and their health suffers. Women who are not performing as well as they might and who are unhealthy are less likely to be promoted to senior levels or to grow in other ways.

The impacts of low-level sexism are insidious but as the results of our meta-analysis show, very real. The perpetrators may not believe or accept that they are being sexist, and will often respond when challenged that they are “just joking”. The effects for women are insidious because they create a reaction refered to as “stereotype threat” in which the individuals targeted by sexist remarks will often ruminate on the implications and be distracted from the task at hand. The fact that stereotype threat is such a strong negative predictor for female performance highlights how distractive ruminations created by sexism undermine women’s functioning at work.

In addition to its effects on performance, sexism also undermines women’s health and their retention by organisations. Furthermore, the effects are not limited to the women who are specifically targeted by sexist remarks. Other women who hear the remarks can also experience stereotype threat as a member of the group whose status is challenged. When a sexist remark is challenged and the perpetrator responds that they are “just joking” it presents two challenges for the women to ruminate about. First they are challenged about their gender, and second, about their sense of humour and social competence in not understanding social norms.

Under our proposed “no just joking” policy, anyone who hears a sexist remark would be expected to point it out and the person who made the remark would be required to say “I am sorry that my comments were offensive.” The situation should end there. We believe that this simple intervention can do much to surface and deal with the incidence of sexism. First, it would legitimise a woman’s and other’s right to challenge sexist remarks without being criticised or accused of a lack of humour. Second, it can ensure that if a person who makes a sexist remark starts to say “I was just joking”, they should stop and say “I am sorry”. This locates the responsibility with the perpetrator and not the target. Third, apologies are a non-defensive response in which the person apologising accepts responsibility for their actions and makes an implicit promise to try not to repeat the behaviour in the future (Wood & Mitchell, 1981). The implicit promise can be made explicit through statements such as “I won’t make comments like that again”. If promoted by the senior leadership of the organisation as an expected response to sexism, a “no just joking” policy will lead to awareness and hopefully change without women having to bear the double burden of stereotype threat for their lack of a sense of


Gender inequality at work is still one of the core problems that most organisations around the world need to address. Dealing with the problem requires an understanding of the gaps and the key factors driving those gaps. The results of this meta-analysis show how the effectiveness of gender diversity strategies aimed at the recruitment and promotion of women can be understood in a broader context in two ways: First, we have disaggregated the understanding of the effectiveness of women at work into the three levels of fit, functioning and growth, with a total of eight categories of indicators. These categorisations will enable organisations to use data collected through employee surveys and company records to develop a more finely-tuned understanding of the gender issues or gaps that they might address.

Second, the use of the fit, functioning and growth indicators to target understanding of the problems to be addressed is supplemented by the identification of the strongest and most robust predictors of those indicators. Once problems are identified, organisations can target solutions at the relevant predictors with the knowledge that they are using an evidence-based approach, supported by results from multiple studies.

CONCLUSIONS

humour. Those who use sexist humour can be corrected in a way that doesn’t say that they are sexist, just that they have said something which hurt or offended the person to whom it was directed.

There is a broader reality that needs to be acknowledged in the crafting and promotion of a “no just joking” policy. Many men and women have grown up in a world in which sexist jokes were part of their daily social lives and were considered just jokes, even if people were sometimes offended by them. But back then, the evidence that stereotype threats and sexist jokes would significantly impede the progress of women in organisations was not widely acknowledged the way it is today. Also, the point needs to be made that the loss of one source of humour is not the death of humour. It merely indicates that it is time to learn a few new jokes.

5. Organisations should target factors that influence the performance of women including sexism that creates stereotype threat and leadership and job design factors that limit the control women have over their work lives, particularly for women in middle management roles. Performance is the major currency of success in most organisations. Women’s movement from middle management to senior leadership roles will be influenced by their performance even when systems are biased. The reduction and removal of stereotype threat due to low-level sexism will provide a subtle but cumulative benefit to the performance of women in organisations. Increasing the control that women in middle management exercise over their work, work hours, resources and availability needs to be approached from multiple perspectives. One approach should be through leadership and the delegation of tasks. Many leaders are poor delegators and need to learn to do so more effectively. This requires trust, attention to the confidence of the delegate and skills to balance the self-determination of the delegate and the control and accountability needs of the delegator.

A second approach for increasing women’s control over their work is the design of work. Where possible, project based assignments should be used to provide women in mid-level roles with opportunities for the development and demonstration of leadership skills for more senior positions. Projects involve a discrete structuring of tasks that allows greater discretion and, therefore, control over the timing, resourcing and execution of tasks, with external control through milestones and outcomes.

A third approach to increasing the control that women have over their work lives is greater acceptance and use of flexible work practices. While there are many factors that contribute to organisational resistance to flexible work practices, a perceived lack of control over the

flexible worker is a key one. Managers and colleagues of flexible workers need to be educated to understand that physical proximity is only one method of control and that other methods should be in place when a person works flexibly.


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Heilman, M. E., Wallen, A. S., Fuchs, D., & Tamkins, M. M. (2004). Penalties for success: Reactions to women who succeed at male gender-typed tasks. Journal of Applied Psychology, 89, 416-427.

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Health: from an environmental point of view health denotes the level of an organism’s resources to operate successfully in its environment and to be able to function and grow (Larson, 1999).

Male-dominated work environment: a working environment where there is a numerical male dominance and where the policies, formal and informal practices are dictated by men and are detrimental to women’s personal and organisational wellbeing.

Meta-analysis: a systematic review of research where the results of the association between variables obtained from different studies are statistically synthetised (Borenstein, Hedges, Higgins & Rothstein, 2009).

Protective factor: a variable that modifies, ameliorates, or alters an individual’s response to a specific hazard that would otherwise predispose to a maladaptive outcome (Rutter, 1985).

p-value: a measure of the magnitude of the summary effect size (measure of the association between two variables) and also the volume of information on which the estimation of the effect size was based. p-values range from 1 to 0. If a p-value is below .05 it means that the summary effect size is significantly different from zero and worthy of interpretation (Borenstein, Hedges, Higgins & Rothstein, 2009).

Q: the overall index of variability of the individual effect sizes used to estimate a summary effect size. A significant Q could indicate a systematic variability of the effect sizes and the need to evaluate moderators of the relationship between the two variables studied (Borenstein, Hedges, Higgins & Rothstein, 2009).

Resilience: the set of processes through which the properties of an organism allow it to remain healthy and functional when it is confronted with adversities.

Risk factor: a variable that, when present, predisposes the individual to a maladaptive outcome (Rutter, 1985).

Summary effect size: the overall measure of the association between two variables in a meta-analysis. It is a weighted mean of the individual effects obtained from different studies (Borenstein, Hedges, Higgins & Rothstein, 2009). In this meta-analysis Pearson correlations (r) were the effect size indicator used.

Taxonomy: a classification of organisms or events in an ordered system that indicates their relationships.

Well-being: the level of progress toward better individual functioning, an optimistic view of the future and one’s potential, and the integration of the person (body, mind, and spirit) in a functioning process (Larson, 1999).

GLOSSARY


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APPENDIX A:STUDIES USED IN THE META-ANALYSIS


Fredrickson, B., Roberts, T., Noll, S., Quinn, D. & Twenge, J. (1998). That swimsuit becomes you: Sex differences in self objectification, restrained eating, and math performance. Journal of Personality and Social Psychology, 75, 269-284.

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Gerdes, E. (1995). Women preparing for traditionally male professions: Physical and psychological symptoms associated with work and home stress. Sex Roles, 32, 787-807.

Gignac, M. A. M., Kelloway, E. K., & Gottlieb, B. H. (1996). The impact of caregiving on employment: A mediational model of work-family conflict. Canadian Journal on Aging, 15 (4), 525-542.

Goldenhar, L., Swanson, N., Hurrell, J., Ruder, A., & Deddens, J. (1998). Stressors and adverse outcomes for female construction workers. Journal of Occupational Health Psychology, 3 (1) 19-32.

Grandey, A., Cordeiro, B. L., & Crouter, A. C. (2005). A longitudinal and multi-source test of the work–family conflict and job satisfaction relationship. Journal of Occupational and Organisational Psychology, 78, 1-20.

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Greenberger, E., & O’Neil, R. (1993). Spouse, parent, worker: Role commitments and role-related experiences in the construction of adults’ well-being. Developmental Psychology, 29, 181-197.

Guelzow, M. G., & Bird, G. W. (1991). An exploratory path analysis of the stress process for dual-career men and women. Journal of Marriage and the Family, 53, 151-164

Hammer, L. B., Cullen, J. C., Neal, M. B., Sinclair, R. R., & Shafiro, M. V. (2005). The longitudinal effects of work-family conflict and positive spillover on depressive symptoms among dual-earner couples. Journal of Occupational Health Psychology, 10 (2), 138-154.

Heilman, M. & Haynes, M. (2005). No credit where credit is due: Attributional rationalization of women’s success in male–female teams. Journal of Applied Psychology, 90 (5), 905-916.

Heilman, M. E., Wallen, A. S., Fuchs, D. & Tamkins, M. M. (2004). Penalties for success: Reactions to women who succeed at male gender-typed tasks. Journal of Applied Psychology, 89, 416-427.

Higgins, C., Duxbury, L., & Johnson, K. L. (2000). Part-time work for women: Does it really help balance work and family? Human Resource Management, 39, 17-32.

Inzlicht, M. & Ben-Zeev, T. (2000). A threatening intellectual environment: Why females are susceptible to experiencing problem-solving deficits in the presence of males. Psychological Science, 11, 365-371.

Jandeska, K. & Kraimer, M. (2005). Women’s perceptions of organisational culture, work attitudes, and role-modeling behaviors. Journal of Managerial Issues, 17 (4), 461-478.

Javidan, M., Bemmels, B., Devine, K. S., & Dastmalchian (1995). Superior and subordinate gender and the acceptance of superiors as role models. Human Relations, 48, 1271-1284.

Jawahar, I. & Hemmasi, P. (2006). Perceived organisational support for women’s advancement and turnover intentions: The mediating role of job and employer satisfaction. Women in Management Review, 21 (8), 643-661.

Jones, F., & Fletcher, B. (1993). An empirical study of occupational stress transmission in working couples. Human Relations, 46, 881-903.

Keller, J. & Dauenheimer, D. (2003). Stereotype Threat in the Classroom: Dejection Mediates the Disrupting Threat Effect on Women’s Math Performance. Personality and Social Psychology Bulletin, 29, 371-381.

Kinnunen, U., & Mauno, S. (1998). Antecedents and outcomes of work-family conflict among employed women and men in Finland. Human Relations, 51 (2), 157-177.

Kirchmeyer, C., & Cohen, A. (1999). Different strategies for managing the work/non-work interface: a test for unique pathways to work outcomes. Work & Stress, 13, 59-73.


Konrad, A. & Pfeffer, J. (1991). Understanding the hiring of women and minorities in educational institutions. Sociology of Education, 64, 141-157.

Leiter, M. P., & Durup, M. J. (1996). Work, home and in-between: a longitudinal study of spillover. Journal of Applied Behavioral Science, 32, 29-47.

Luchetta, T. (1995). Parental and work role salience, everyday problems, and distress: A prospective analysis of specific vulnerability among multiple-role women. Women & Health, 22(4), 21-50.

Lyness, K. S., & Thompson, D. E. (1997). Above the glass ceiling? A comparison of matched samples of female and male executives. Journal of Applied Psychology, 82, 359-375.

Martire, L. M., Stephens, M. A. P., & Atienza, A. A. (1997). The interplay of work and caregiving: Relationships between role satisfaction, role involvement, and caregivers’ well-being. Journal of Gerontology, 52B, S279-S289.

Martire, L., Stephens, M. A. P., & Townsend, A. L. (2000). Centrality of women’s multiple roles: Beneficial and detrimental consequences for psychological well-being. Psychology and Aging, 15 (1), 148-156.

Melamed, T. (1995). Career success: The moderating effect of gender. Journal of Vocational Behavior, 47 (1), 35-60.

Melamed, T. (1996). Career success: An assessment of a gender-specific model. Journal of Occupational and Organisational Psychology, 69 (3), 217-242.

Metz, I. & Tharenou, P. (2001). Women’s career advancement: The relative contribution of human and social capital. Group & Organisation Management, 26 (3), 312-340.

Miner-Rubino, K., Settles, I., & Stewart, A. (2009). More than numbers: Individual and contextual factors in how gender diversity affects women’s well-being. Psychology of Women Quarterly, 33, 463-474.

Moore, S., Grunberg, L., & Greenberg, E. (2004). Are female supervisors good for employee job experiences, health, and wellbeing? Women in Management Review, 20 (2), 86-95.

Morrow, P. C., McElory, J. C., & Phillips, C. M. (1994). Sexual harassment behaviors and work related perceptions and attitudes. Journal of Vocational Behavior, 45, 295-309.

Newell, C. E., Rosenfeld, P., & Culbertson, A. L. (1995). Sexual harassment experiences and equal opportunity perceptions of Navy women. Sex Roles, 32, 159-168.

Noor, N. M. (1999). Roles and women’s well-being: Some preliminary findings from Malaysia. Sex Roles, 41 (3/4), 123- 145.

Noor, N. M. (2002). Work-family conflict, locus of control, and women’s well-being: Tests of alternative pathways. The Journal of Social Psychology, 142 (5), 645-662.

Noor, N. M. (2004). Work-family conflict, work - and family - role salience, and women’s well being. The Journal of Social Psychology, 144 (4), 389-405.

O’Connell, L., Betz, M., & Kurth, S. (1989). Plans for balancing work and family life: Do women pursuing nontraditional and traditional occupations Differ? Sex Roles, 20 (1/2), 35-45.

Parasuraman, S., Greenhaus, J. & Granrose, C. (1992). Role stressors, social support, and well-being among two-career couples. Journal of Organisational Behavior, 13, 339-356.

Parker, S. & Griffin, M. (2002). What is so bad about a little name-calling? Negative consequences of gender harassment for overperformance demands and distress. Journal of Occupational Health Psychology, 7 (3), 195-210.

Pearson, Q. (2008). Role overload, job satisfaction, leisure satisfaction, and psychological health among employed women. Journal of Counseling & Development, 86, 57-63.

Pretty, G. M., McCarthy, M. E., & Catano, V. M. (1992). Psychological environments and burnout: Gender considerations within the corporation. Journal of Organisational Behavior, 13, 701-711.

Reskin, B. & McBrier, D. (2000). Why not ascription? Organisations’ employment of male and female managers. American Sociological Review, 65, 210-33.


Richardsen, A., Burke, R., & Mikkelsen, A. (1999). Job pressures, organisational support, and health among Norwegian women managers. International Journal of Stress Management, 6 (3), 167-177.

Riipinen, M. (1994). Occupational needs as moderators between locus of control and job involvement. Psychological Reports, 74, 371-379.

Riley, S., & Wrench, D. (1985). Mentoring among women lawyers. Journal of Applied Social Psychology, 15, 374-386.

Rivardo, M. G., Rhodes, M. E., Camaione, T. C., & Legg, J. M. (2011). Stereotype threat leads to reduction in number of math problems women attempt. North American Journal of Psychology, 13 (1), 5-16.

Rosin, H. & Korabik, K. (1991). Workplace variables, affective responses, and intention to leave among women managers. Journal of Occupational Psychology, 64, 317-330.

Ruderman, M., Ohlott, P., Panzer, K., & King, S. (2002). Benefits of multiple roles for managerial women. Academy of Management Journal, 45, 369-386.

Ryan, M., & Haslam, A. (2005). The Glass Cliff: Evidence that women are over-represented in precarious leadership positions. British Journal of Management, 16, 81-90.

Rydell, R., Rydell, M. & Boucher, K. (2010). The effect of negative performance stereotypes on learning. Journal of Personality and Social Psychology, 99 (6), 883-896.

Schmader, T. & Johns, M. (2003). Converging evidence that stereotype threat reduces working memory capacity. Journal of Personality and Social Psychology, 85 (3), 440-452.

Sekaquaptewa, D. & Thompson, M. (2003). Solo status, stereotype threat, and performance expectancies: Their effects on women’s performance. Journal of Experimental Social Psychology, 39, 68-74.

Settles, I. H., Cortina, L. M., Malley, J., & Stewart, A. J. (2006). The climate for women in academic science: the good, the bad, and the changeable. Psychology of Women Quarterly, 30, 47-58.

Settles, I., Cortina, L., Stewart, A. & Malley, J. (2007). Voice matters: Buffering the impact of a negative climate for women in science. Psychology of Women Quarterly, 31, 270-281.

Smart, R. M. (1998). Career stages in Australian professional women: A test of Super’s model. Journal of Vocational Behavior, 52, 379-395.

Stangor, C., Carr, C. & Kiang, L. (1998). Activating Stereotypes Undermines Task Performance Expectations. Journal of Personality and Social Psychology, 75 (5), 1191-1197.

Tam, T. (1997). Sex segregation and occupational gender inequality in the United States: Devaluation or specialized training? American Journal of Sociology, 102, 1652–1692.

Taniguchi, H. (1999). The timing of childbearing and women’s wages. Journal of Marriage and the Family, 61, 1008- 1019.

Tharenou, P. (1999). Is there a link between family structures and women’s and men’s managerial career advancement? Journal of Organisational Behavior, 20, 837-863.

Tharenou, P., Latimer, S. & Conroy, D. (1994). How do you make it to the top? An examination of influences on women’s and men’s managerial advancement. Academy of Management Journal, 37, 899-931.

Thomas, L. T., & Ganster, D. C. (1995). Impact of family-supportive work variables on work–family conflict and strain: A control perspective. Journal of Applied Psychology, 80 (1), 6-15.

van der Velde, M., Bossink, C., & Jansen, P. (2003). Gender differences in the influence of professional tenure on work attitudes. Sex Roles, 49, 153-162.

Vinokur, A., Pierce, P. & Buck, C. (1999). Work-family conflicts of women in the air force: The influence on mental health and functioning. Journal of Organisational Behaviour, 20, 865-878.

von Vianen, A., & Fischer, A. (2002). Illuminating the glass ceiling: The role of organisational culture preferences. Journal of Occupational & Organisational Psychology, 75, 315-337.


Wallace, J. E. (2001). The benefits of mentoring for female lawyers. Journal of Vocational Behaviour, 58, 366-391.

Wallace, J. E., & Young, M. (2008). Parenthood and productivity: A study of demands, resources and family-friendly firms. Journal of Vocational Behavior, 72, 110-122.

Weatherill, R., Vogt, D., Taft, C., King, L., King, D. & Shipherd, J. (2011). Training experiences as mediators of the association between gender-role egalitarianism and women’s adjustment to marine recruit training. Sex Roles, 64, 348-359.


APPENDIX B:CATEGORIES, VARIABLES, DESCRIPTION AND EXAMPLES OF MEASURES USED IN STUDIES META-ANALYSED

1. Managerial level

Managerial advancement (managerial level, N of subordinates, managerial positions filled by women)

Outcomes

Table B1. Categories, variables, descriptions and examples of measures used for the indices/outcomes of women’s fit, functioning and growth at work

Variable Description Examples of measures used

Combination of managerial level, salary level and number of supervised people at the individual level

Women working as managers at the organisational level

3 items: 1. What is your level in the managerial hierarchy? (1 = First line supervisor; 6 = Chief executive). 2. What is your salary range? (1 = Under $22,000; 8 = Over $100,000). 3. How many subordinates do you have? (i.e. how many people do you delegate work to directly or indirectly) (1 = None; 8 = Over 30) (Tharenou, Latimer, & Conroy, 1994)

Number of women hired as managers in the organisation (Konrad & Pfeffer, 1991)

2. Compensation level

Compensation Hourly wage: Pay per working hour

Direct question (Rosin, & Korabik, 1991)

3. Performance

Implicit and explicit learning on experimental task

Math performance

Transfer Task Learning

Work performance

Recognition task manipulated through prime stimuli

Participants’ score in a math test

Knowledge transference

Work performance evaluated by supervisor

Recognition-task where participants were to identify if the symbols were old (those that had been used in the focal or transfer tasks) or new. Implicit learning was measured by presenting prime stimulus for 200 ms before participants made each recognition decision. (Rydell, Rydell & Boucher, 2010)

20 items taken from the GRE test guide (ETS, 1994 in Inzlicht & Ben-Zeev, 2000)

Number of correct answers in a second task that involved using the same set of rules that were used for a Focal Task, this time applied to different symbols (Rydell, Rydell, & Boucher, 2010)

Mean of two,7-point items,6 = Outstanding to 1 = Unsatisfactory (Metz & Tharenou, 2001)

4. Hiring and Retention

Absenteeism

Hiring women

Number of days in the past year that the individual missed work, excluding vacations and other excused reasons

Being granted a job for which the individual applied

Direct report of number of days (Moore, Grunberg, & Greenberg, 2004)

Total number of job offers received after applying for them (Belliveau, 2005)


Intention to Leave the Organisation

Organisational Tenure

Professional Tenure

Pursuing non-traditional occupation

Women in core job

OutcomesVariable Description Examples of measures used

Participants’ intention to leave their job, intent to remain or job withdrawal (reversed)

Years with current employer/spent in job

Number or years working in the present profession

Enrolment in vet science or engineering, or other non-traditional subject area

Number of women working in a job of the line of production or core business of the organisation

4 items: 1. At this time of your career, would you want to quit this job if it were possible? (1 = Yes; 2 = No; 0 = Not sure). 2. Are you actually planning to leave your job within the next six months? (1 = Yes; 2= No; 0 = Not sure). 3. Are you actively searching for another job right now? (1 = Yes; 0 = No). 4. Please indicate whether you have ever had thoughts of leaving your job (1 = Never; 3 = Frequently) (Rosin & Korabik, 1991)

Direct question (Tam, 1997)

Direct question (van der Velde, Bossink, & Jansen, 2003)

Direct question (O’Connell, Betz & Kurth, 1989)

Organisational level indicator of the number of women associates working for a law firm (Beckman & Philips, 2005)

5. Health

General Health Problems and Symptoms

Mental Health Problems and Symptoms

Physical Health Problems and Symptoms

Satisfaction with life

Presence or absence of specific health symptoms or diagnosed conditions

Self-rated symptoms of anxiety, depression, distress, irritation, PTSD

Self-rated physical health

Overall evaluation of own life

Health Conditions Index (Brodman, Erdman, Lorge, & Wolff, 1949)

8 items, 4-point scale from the RandCorporation’s 36-item Short Form Health Survey (Ware & Sherbourne, 1992 in Buchanan, Settles & Woods, 2008)

A modified version of the Seriousness of Illness Rating Scale. Accidents and illnesses that were unlikely to be caused by stress (e.g. colour-blindness) were omitted. (Wyler, Masuda & Holmes, 1968 in Gerdes, 1995)

Satisfaction with Life Scale - SWLS (Diener, 1984 in Fitzgerald, Drasgow, Hulin, Gelfand & Magley, 1997)

6. Work Attitudes

Career Satisfaction

Job Involvement

Satisfaction with progress toward achieving career goals

Importance placed on a particular job and the extent to which everything else in life centres around it

5 items, 5-point scale (1 = Very dissatisfied to 5 = Very satisfied,” Example item: The progress I’ve made toward meeting my goals for advancement (Greenhaus, Parasuiaman, & Wormley, 1990)

Short (6 items) form of Lodahl & Kejner’s (1965 in Lyness & Thompson, 1997) Job Involvement Scale. Response format from “Strongly disagree” to “Strongly agree”


OutcomesVariable Description Examples of measures used

Job Satisfaction

Organisational Commitment

Overall evaluation of the job (satisfaction with tasks, employer, co-workers, career opportunities)

Overall attachment individuals have with the organisation

13 items, 5-point scale (1= Very dissatisfied). Satisfaction with dimensions such as faculty interaction, resources and salary, being valued for scholarship and instruction, level of intellectual stimulation (Settles, Cortina, Stewart & Malley, 2007)

8 items, 5-point Likert scale. Example item: This organisation has a great deal of personal meaning to me (Casper, Martin, Buffardi, & Erdwins, 2002)

7. Sexist climate

Perception of achievement-related attributes

Nonacceptance of women

Sexist organisational climate

Tolerance for sexual harassment

Regarding stimulus person as achievement-oriented

Perception of acceptance of police women as competent workers

Organisation that supports heterosexual norms, devaluation of women, sexual bravado and aggression Extent to which the participants think their organisation tolerates behaviours associated with sexual harassment

9-point bipolar adjective scale, ratings describing the stimulus individual (unambitious-ambitious; passive-active; indecisive-decisive; weak-strong; gentle-tough; timid-bold) (Heilman, Wallen, Fuchs, & Tamkins, 2004)

2 items 5-point scale (1 = Strongly disagree; 5 = Strongly agree). Example item: Men police officers find it difficult to accept women officers performing the same duties as they do (Parker & Griffin, 2002)

9 proposition, 5-point scale, taken from an organisational culture scale. Example item: In my work unit people make indecent remarks about women (de Haqs & Timmerman, 2010) Organisational Tolerance for Sexual Harassment Inventory (OTSHI): Participants are asked to report their perceptions of the likelihood of organisational reactions when superiors and co-workers engage in various forms of harassment (Fitzgerald, Drasgow, Hulin, Gelfand, & Magley, 1997)

8. Sexual harassment Sexual coercion Unwanted sexual attention / Crude behaviour

Behaviours in which resistance, promises, or retaliation are into play Offensive verbal and non-verbal sexual behaviours such as making sexual gestures or jokes

6 items, 5-point scale (1 = Never; 5 = Many times). Example item: Subtly bribed into sexual intimacy with promise or reward (de Haas & Timmerman, 2010)

12 items, 5-point scale (1 = Never; 5 = Many times). Example items: Unwanted attempts to draw you into a discussion of personal or sexual matters; Staring, leering, or ogling you in a way that made you feel uncomfortable (de Haas & Timmerman, 2010)


1. Labour market characteristics

Industry prosperity

Regional prosperity

Supply of prospective employees

Occupation wage range

Level of education required for job

Predictors

Table B2. Categories, variables, descriptions and examples of measures/interventions used for the potential predictors of women’s fit, functioning and growth at work


Current economic success of a specific industry sector

Current economic success of a specific geographic region Relationship between supply and demand of professionals in a specific sector

Number of levels of salary in an occupational sector

The typical requirement of the occupation for schooling and vocational training

Average of three standardised figures from government publications: average wage in each industry, a wage range in each industry excluding the top and bottom 10% of earners, and the size of the work force in each industry (Melamed, 1995)

Standardised and averaged three figures for the economic state in each region of the UK: unemployment rate in each region, the ratio of job centre vacancies to the number of unemployed in the region, and the average regional wage (Melamed, 1995) Whether at least 30 people applied for a managerial job (0 = No, 1 = Yes) (Reskin & McBrier, 2000)

Range of managerial pay (range 0 to 950, in US$1000s) (Reskin & McBrier, 2000)

0-6 point scale with high values denoting those occupations requiring relatively high levels of general educational development (Cohen, & Huffman, 2003)

2. Organisation demographics

Age of the organisation

Business vs. other organisations

Government vs. other organisations Industry type

Number of years the organisation has been operative

Organisational Sector

Organisational Sector

Main business of the organisation

Natural logarithm of establishment age (Cohen & Huffman, 2003)

1 = Private sector, 0 = Public sector (Melamed, 1996 1 = Government establishment, 0 = Non-government establishment (Cohen & Huffman, 2003)

1 = Manufacturing (durable and nondurable manufacturing, mining, forestry, agriculture, and construction), 0 = Non-manufacturing (services, transportation and communication) (Blum, Fields, & Goodman, 1994)


PredictorsVariable Description Examples of measures used

Organisational resources

Size of the organisation Number of managerial job positions % professional or skilled employees Average salary of the job

Job type

Economic and human resources available for the regular operation of the organisation

Number of people working in the organisation Number of employees in an organisation that have subordinates reporting to them Percentage of professional or skilled employees in each company Mean of the salaries for a specific job in an organisation

Core job: Job title of those employees most directly associated with the production or service line of the organisation

Factor score comprised of 3 variables: Full-time equivalent (FTE) faculty/FTE students; FTE Staff/FTE Students; total budget/FTE students (Konrad & Pfeffer, 1991)

Natural logarithm of the size of the labour force (Cohen & Huffman, 2003) Percentage of establishment’s workforce in management (Reskin & McBrier, 2000) Respondents classified employees as belonging to different occupational categories: professional, skilled, management, clerical, and unskilled. A square root transformation was used to reduce skewness of the distribution of this variable (Blum, Fields, & Goodman, 1994) Average salary reported for the job across 821 institutions (Konrad & Pfeffer, 1991)

1 = Line, 0 = Staff, (Melamed, 1995)

3. Organisation formal practices


Precision of information about performance

Clear policies and regulations for personnel management

Clarity of the information provided about the performance and contribution of employees in the achievement of organisational goals

8 dichotomous indicators of the presence of the following documents: rules and procedures manual, written job descriptions, written record of job performance, employment contracts, personnel evaluation documents, hire-fire procedure documents, safety-hygiene practices description, fringe benefits documents. Formalisation value equals the number of these documents that are present (Cohen & Huffman, 2003)

Experimental Manipulation Clear success: the target person is said to have already undergone performance review and has been designated as a top performer by the organisation. Ambiguous success: stating that the target subject was about to undergo their annual performance review, and their evaluation would be based on sales, volume, number of new client accounts, and actual dollars earned (Heilman et al., 2004)



Comfort with candidate for promotion

Internal hire for promotions


Support for advancement

Training and development

The extent to which decision makers promote candidates with whom they feel comfortable

Use of internal labour market to promote currently employed workers

Assigning tasks that will foster the career development of the employees

Personal mentoring from a superior and encouragement for career advancement

Investment by the organisation on training and development of the employees

7 items, 5-point scale (e.g., the person who promoted/recommended me for promotion knows me well) (Metz & Tharenou, 2001)

3 items, whether the establishment fills vacancies in the core job title with current employees, whether different levels of the core job title exist, and the final item taps the frequency of promotion above the core job title. (1 = Yes, 0 = No) (Cohen & Huffman, 2003)

Report of the number of different assignments held (Grant, Garrison, & McCormick, 1990)

3 items, 5-point scale (1 = Never; 5 = Six or more times), e.g., number of times encouragement was provided for career development by more senior employees in the organisation (Tharenou & Conroy, 1994)

4 items, 5-point scale: Example item: My organisation has provided formal training and education programs - inside or outside - to help me develop (Richardsen, Burke, & Mikkelsen, 1999)

4. Work supports and demands

Job network and support Organisational support for parents

Work balance

Number of relationships and degree of closeness to co-workers with whom they discussed important matters Organisation’s effort to support workers with family responsibilities

Experience of work in a positive way, providing more rewards than concerns

6 items, 5-point scale, assessing perceived support and cooperation from co-workers, degree of sociability and friendliness of colleagues (Crossfield, Kinman, & Jones, 2005) 1 item, 7 point scale, participants indicated the extent to which their work schedule was flexible enough to allow time off work to take care of family needs (Guelzow & Bird, 1991) Scale of 19 rewards and 19 concerns associated with the role of a paid employee, 4 point scale (1 = Not at all; 4 = Extremely). The subjects were to indicate to what extent each of the items was rewarding or distressing. The difference between the mean level of reward and the mean level of distress was the final indicator (Barnett & Baruch, 1985)


Predictors



Hours of work a week Role reduction General work stress Job insecurity Job monotony Overperformance Work overload Work – Family conflict

Latitude in decision-making and relative power at work

Number of working hours per week Partial withdrawal from work situations that are perceived as too demanding Whether employees need to deal with emotionally charged situations and whether they are confronted with events that touch them personally at work Concern about lack of job security and uncertainty about the future of one’s job Lack of challenging tasks and boredom with the routine of work An individual’s perception that they need to perform above the normal level expected for the job to gain acceptance and recognition within the workplace Conflict that occurs when the sheer volume of behaviour demanded in the position exceeds available time and energy The extent to which work responsibilities caused fatigue and distracted the employees while at home, or resulted in less attention given to family members

4 items, 5-point agree/disagree response scale. Example item: I have enough power in this organisation to control events that might affect my job. A modified version of Ashford, Lee, and Bobko’s (1989) scale (Kinnunen & Mauno, 1998)

9 category items, 1 = Less than 15 hours to 9 = More than 60 hours (Metz, & Tharenou, 2001) 13 items, 7-point scale, participants indicated the extent to which items described their way of managing the dual responsibilities of employment and family life. E.g., Limiting involvement on the job - saying no to some things I could be doing (Guelzow & Bird, 1999) 20 items taken from previously published measures (Frone et al., 1992), 4-point scale. Four subscales: work overload, lack of autonomy, role ambiguity, lack of responsibility (Vinokur, Pierce, & Buck, 1999) 5 items, 5-point agree/disagree scale. Example item: I am worried about the possibility of being fired (Kinnunen & Mauno, 1998) Please indicate the extent to which (this) factor might influence a decision to leave your job: “Boredom with the routine” (1 = Not at all a factor, 3 = Definitely a factor, 0 = Not applicable) (Rosin & Korabik, 1991) 4 items, 5 point scale (1 = Never to 5 = All of the time), of how often they needed to behave (or believed they ought to behave) in certain ways to be accepted or to advance within their workplace. Example item: How often do you feel you have to work twice as hard as your colleagues? (Parker & Griffin, 2002) 13 items, 5-point Likert scale. Example item: There are too many demands on my time (Pearson, 2008) 3 items, 5-point frequency scale. E.g., How often does your job or career interfere with your responsibilities at home, such as year work, cooking, cleaning, repairs, or childcare? (Kinnunen & Mauno, 1998)



5. Organisation informal practices

Collectivistic culture Competitive & task focused culture Perceived cultural fit Organisational climate Description of competence Description of likeability

Minorities as managers Minorities in the organisation

The extent to which the organisation is team-oriented and values the interdependence and contributions of all employees The extent to which the organisation is oriented to good planning, efficiency, and getting the job done, and values competition among employees Degree to which employees feel accepted as a member of their specific team and the organisation as a whole Perceptions of the work environment, organisational policies, practices and procedures Degree to which the target employee is presented as competent or non-competent compared to their reference group Degree to which the target employee is presented as liked or not liked compared to their reference group

Proportion of non-whites in management positions, i.e. those with regular supervisory responsibilities Proportion of non-whites in the organisation

7 items, 5 point scale (1 = Does not describe at all, to 5 = Describes completely) developed by Robert and Wasti (2002). E.g., How well each statement described their current organisations: Employees are taken care of like members of a family (Jandeska, & Kraimer, 2005) 4 items, 7-point scale (1 = Not at all applicable; 7 = Very applicable). E.g., Are the following statements applicable to the organisation where you work?: there are high standards of performance (von Vianen & Fischer, 2002) 6 items, 5-point scale. E.g., I feel completely accepted as a full-fledged member by the senior management in my organisation (Richardsen, Burke, & Mikkelsen, 1999) 6 items, 5-point scale of paired descriptors: E.g., friendly-hostile, disrespectful-respectful, collegial-contentious, collaborative-individualistic, cooperative-competitive, and Non supportive- supportive (Settles et al., 2007 Experimental Manipulation: information provided on the performance rating information sheet. Employees in the high-competence conditions were shown to have a competence rating of 9.1 and individuals in the low competence condition were shown to have a rating of 5.4 (the average rating was 6.8) (Heilman, Wallen, Fuchs & Tamkins, 2004) Experimental Manipulation: information provided on the performance rating information sheet. Employees in the high-likability conditions were shown to have a likability rating of 9.3 and individuals in the low likability condition were shown to have a rating of 4.9 (the average rating was 7.1) (Heilman, Wallen, Fuchs & Tamkins, 2004)

Direct question: percentage of whites and non-whites in management positions in the organisation(Blum, Fields & Goodman, 1994) Percentage of minority persons in administrative positions in the institution (Konrad & Pfeffer, 1991)



6. Sexism at work

Sexist climate

Sexual harassment Stereotype threat

The extent to which the organisation values men more than women and allows for discrimination and harassment of women Experiences of sexual coercion, unwanted sexual attention and crude behaviour at work Making salient the gender of female workers during the performance of a task that has been defined as stereotypically masculine

9 items, 5-point scale (1= Strongly disagree, 5 = Strongly agree). Example item: Men receive preferential treatment in the areas of recruitment and promotions (Settles, Cortina, Stewart, & Malley, 2007) 12 items, 5-point scale (1 = Never; 5 = Many times). Example item: Unwanted attempts to draw you into a discussion of personal of sexual matters” (de Haas & Timmerman, 2010) Experimental Manipulation: Description of the characteristics of the mathematical task. Either as a set of mathematical problems or as a set of mathematical problems followed by the explanation that men perform better than women in that kind of task (Rivardo et al., 2011)

7. Women in the organisation

Women as managers Women in core job Women working in the area Women as subordinate

Proportion of managerial positions filled by women Proportion of women filling positions in the line of production/service of the organisation Proportion of women working in the organisation or industry in general Gender of the subordinate evaluating the female superior

Participants were asked to indicate the composition of men and women in the rank or position above them using a scale (1 = All or mostly men to 3 = All or mostly women) (Miner-Rubino, Settles, & Stewart, 2009 Number of women associates in the law firm (Beckman & Philips, 2005) Personnel and HR Managers were asked the percentage of non-management positions held by men. The percentage of women in non-management positions was obtained by subtracting the percentage held by men from 100 (Blum, Fields, & Goodman, 1994 Either female or male subordinate (Javidan et al., 1995)



8. Work attitudes

Career Satisfaction Job Involvement Organisational Commitment Job satisfaction Satisfaction with co-workers Satisfaction with salary and ranking Satisfaction with supervisor

Satisfaction with progress toward achieving career goals Importance placed on a particular job and the extent to which everything else in life centres around it Overall attachment individuals have with the organisation where they work Overall evaluation of the job (satisfaction with tasks, employer, co-workers, career opportunities) Overall evaluation of the quality of the relationship with co-workers Overall evaluation of payment and career progress or status in the organisation Participants’ perception of the leadership in their department

5 items, 5-point scale (1 = Very dissatisfied to 5 = Very satisfied). Example item: The progress I’ve made toward meeting my goals for advancement (Greenhaus. Parasuiaman, & Wormley, 1990) Short (6 item) form of Lodahl & Kejner’s (1965 in Lyness & Thompson, 1997) Job Involvement Scale. Response format from “Strongly disagree” to “Strongly agree” 8 items, 5-point Likert scale. Example item: This organisation has a great deal of personal meaning to me (Casper, Martin, Buffardi, & Erdwins, 2002) 13 items, 5-point scale (1= Very dissatisfied). Satisfaction with dimensions such as: faculty interaction, resources and salary, being valued for scholarship and instruction, level of intellectual stimulation (Settles, Cortina, Stewart & Malley, 2007) People in present job sub-scale of the Job Descriptive Index (JDI; Smith, Kendall, & Hulin, 1969). Response alternatives “Yes”, “No” or “Uncertain” were scored 3, 0, and 1 respectively (Smart, 1998) Pay sub-scale of the Job Descriptive Index (JDI; Smith, Kendall, & Hulin, 1969). Response alternatives “Yes”, “No” or “Uncertain” were scored 3, 0, and 1 respectively (Smart, 1998) Supervision sub-scale of the Job Descriptive Index (JDI; Smith, Kendall, & Hulin, 1969). Response alternatives “Yes”, “No” or “Uncertain” were scored 3, 0, and 1 respectively (Smart, 1998)

9. Personal supports and demands

Family balance and support Experiencing family in a way that provides more rewards than concerns and the emotional and instrumental support from relatives

9 items, 6-point scale measuring Support From Neighbours.Example item: I am part of a close-knit neighbourhood, where people are friendly and help each other out (Greenberger & O’Neil, 1993)


Predictors


Family interest for work and education Family centrality Family demands General family stress Marital stress Parental stress Family – Work conflict

Extent to which relatives encourage and support the career development of the employee Perception of personal investment in key life roles: marital, parental, community, and friendship (and occupational) Time and effort invested caring for relatives Whether employees have to deal with emotionally charged situations and whether they are confronted with events that touch them personally at home Pressure from partner and conflicts derived from the marital relationship

Pressure from children and conflicts derived from the parental care role The extent to which family responsibilities caused fatigue and distracted the employees while at work, or resulted in less attention given to work obligations

2 items, 7-point scale (1= Strongly discouraged; 7 = Strongly encouraged): 1. To what extent did your father encourage you to complete year 12? 2. To what extent did your mother encourage you to complete year 12? (Tharenou et al., 1994) 17 items scale. Commitment to marital and parental roles was assessed by items derived from the Life-Role Salience Scale (Amatea, Cross, Clark, & Bobby, 1986 in Ruderman et al., 2002). Total number of hours per week spent in care-giving responsibilities (Martire et al., 1997) 5-items scale assessing personal conflicts at home, modified version of Leiter’s (1988) instrument (Leiter & Durup, 1996) 1 item. Please indicate the extent to which (this) factor might influence a decision to leave your job: “Pressure from my husband” (1 = not at all a factor; 3 = Definitely a factor; 0 = Not applicable) (Rosin & Korabik, 1991)

Caregivers’ appraisals of 21 tasks often performed by adult child caregivers. For each task, the respondent was asked to indicate if she had performed that task in the past month and, if so, how stressful that had been, using a 4-point scale (1 = Not at all; 4 = Very). Tasks not performed were scored ‘0’ (Martire et al., 1997) 4 items, 5-point Likert scale: Example item: My personal life takes up time that I’d like to spend at work (Casper et al., 2002)

10. Human Capital

Education Highest level of education the employee has achieved

10-point scale (1 = Some secondary school to 10 = PhD) (Tharenou, 1999)


Predictors


Prestige of attended university Work experience Employer change Job change Agency Task orientation and analytical skills Gender-role egalitarianism Importance of having a career Dispositional resilience Interpersonal orientation

Social recognition of the university where the employee completed a university degree Number of years working in current professional area Number of times the worker has changed employers Number of different jobs an employee has had Self-confidence, independence and ambition Analysis and synthesis ability and orientation to approach tasks in an organised way oriented to their completion Degree to which non-traditional gender-role behaviours are viewed as appropriate for both women and men and recognition of sexism in society Extent to which one’s career is central to one’s sense of personal identity Tendency to adjust the individual’s own behaviour and mindset to the ever-changing characteristics of the environment while having a positive outlook and sense of control Social skills, relationality, and leadership style that is oriented to care for the individuals and relationships

Reputation ratings provided for each school in the U.S. News and World Report (1997). Institutional ratings were provided by a sample of university presidents, provosts, and deans of admission from 1400 four-year schools in the United States surveyed by U.S. News and World Report (1997). Final scores ranged from 1-4 (Belliveau, 2005) Single item that asked participants to indicate the number of years of active duty service in the army they had completed (Buchanan et al., 2008). Number of different employers the respondents had throughout their careers (Melamed, 1995) Number of job titles respondents had throughout their careers (Melamed, 1995) 4 items, 5-point scale (1 = Completely false to 5 = Completely true). Example item: When I decide to do something, I go right to work on it (Tharenou et al., 1994) Inference scale of Watson-Glaser Critical Thinking Appraisal (Melamed, 1996) 10 items, 5-point Likert scale from the Sex-Role Egalitarianism Scale (SRES). Example item: A female executive deserves the same respect as a male executive (Weatherill, Vogt, Taft, King, King & Shipherd, 2011) 4 items from Gould’s (1979) scale. Example item: I identify strongly with my chosen line of work (Smart, 1998) 20 items, 5-point Adaptability scale of the BENCHMARKS (McCauley & Lombardo,1990) Extraversion factor of the 16PF (form A) by Cattell (1970) (Melamed, 1995)


Predictors


11. Personal demographics

Age Age dependent children Having children Dual career relationship Marital status Marital tenure Race Socio economic status

Chronological age of the employee Age of dependent children Employee living with children Employees who are living with a spouse, partner or significant other who is employed full time Relationship status of employee Number of years married, living with a partner or a significant other Classification of humans into groups by heritable phenotypic characteristics, geographic ancestry, physical appearance, and ethnicity Level of well-being of the individual based on education, professional status, income and living arrangements

Direct question (Rosin & Korabik, 1991 Direct question coded into one of the following five categories: No children, Youngest child over 18 years of age, Youngest child 13-18, Youngest child 7-12 years of age, and Youngest child less than 7 years of age (Kinnunen, & Mauno, 1998) Direct question, 1 = Living with children, 0 = Not living with children (Lyness & Thompson, 1997) Dual career = 1, Not dual career = 0 (Lyness & Thompson, 1997) Direct question, 1 = Living with partner / married 0 = Never married, divorced, separated, or widowed (Parker & Griffin, 2002). Direct question of number of years in the current marriage (Greenberger & O’Neil, 1993) 0 = Caucasian, 1 = Other (Lyness & Thompson, 1997) Income adequacy was assessed using an item that asked participants to indicate which of four statements best described the family’s ability to get along on their income (1 = We cannot make ends meet to 4 = We always have money left over) (Hammer et al., 2005)


Victor Sojo

BSc (Central University of Venezuela), MSc (Simon Bolivar), PhD Candidate (Melbourne)

Victor has worked as project manager in organisational development consulting for mining and energy corporations in Venezuela, including CVG EDELCA, CVG ALCASA and CORPOELECT.

Prior appointments include Senior Lecturer in General Psychology, Experimental Psychology and Research Methods for Industrial / Organisational Psychology at the School of Psychology of the Central University of Venezuela, and visiting lecturer for research methods in the Master of Clinical Psychology and Master of Mental Health of the Central University of Venezuela. He also has tutored for the subjects of Personality and Social Psychology 2 and Industrial / Organisational Psychology in the School of Behavioural Science at the University of Melbourne.

He has submitted the thesis for his PhD in Psychology at the University of Melbourne, working in human resilience to stress, positive emotions and health. He completed his Master of Science in Health Psychology (thesis marked as outstanding) at the Simon Bolivar University, in Venezuela, and his Bachelor of Science in Organisational Psychology (Magna Cum Laude) at the Central University of Venezuela.

Professor Robert Wood

Bus (Curtin), PhD (Washington). FIAAP, FANZAM, FASSA, FAPA

Professor of Management (Organisational Behaviour), Director Centre for Ethical Leadership

Robert Wood is Professor of Management at Melbourne Business School. Prior appointments include Deputy Vice Chancellor at the University of Western Australia and visiting Professor at the Kellogg School, Northwestern University. He completed his PhD in organizational behaviour at the University of Washington (Seattle) and did post-doctoral studies at Stanford University Psychology Department. He is Editor of Applied Psychology an International Review. He was awarded the AGSM Alumni Outstanding Teacher Award (1998) and the inaugural AGSM Award for Excellence in Research (2002). He is a Fellow of the Academy of Social Sciences - Australia; the Australian and New Zealand Academy of Management; the American Psychological Association (Division 14) and the International Association of Applied Psychologists.

Robert has designed, developed and delivered programs for senior managers and provided advice in many Australian and overseas corporations, including Saudi Aramco, Dow Chemical, Telstra, P&O Ports, Dubai Ports World and the Hong Kong Government. He has delivered programs to managers in the USA, Australia, Malaysia, Thailand, Sri Lanka, UAE, the Philippines, and Hong Kong. He was Consultant to OECD (Paris) from 1990 to 1996. During that period he conducted several multi-national studies of pay schemes and performance appraisal practices for managers in Europe, the USA, Japan and Australia.

Robert has served on the Boards of Royal Perth Hospital, the Australian Graduate School of Management and the Australian and New Zealand Academy of Management and the University of Western Australia Senate. He currently sits on the Executive Boards of the Academy of Social Sciences Australia and the International Association of Applied Psychology.

Minerva Access is the Institutional Repository of The University of Melbourne

Author/s:

SOJO, V; Wood, R

Title:

Resilience: Women's Fit, Functioning and Growth at Work: Indicators and Predictors

Date:

2012

Citation:

SOJO, V. & Wood, R. (2012). Resilience: Women's Fit, Functioning and Growth at Work:

Indicators and Predictors. Melbourne Busine.

Persistent Link:

http://hdl.handle.net/11343/123773

File Description:

Published version

GENDER EQUALITY PROJECT - Minerva Access

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