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ASSET 2016: experiences surrounding gender equality in engineering, and their intersections with ethnicity and disability

The Royal Society, the Royal Academy of Engineering, the Royal Society of Biology and the Academy of Medical Sciences commissioned Equality Challenge Unit (ECU) to design and implement the 2016 version of the Athena Survey of Science, Engineering and Technology (ASSET).

This report was researched and written by Dr Amanda Aldercotte, Dr Kevin Guyan, Dr Jamie Lawson, Stephanie Neave and Szilvia Altorjai at ECU.

Additional gratitude is extended to Lenna Cumberbatch (previously of The Royal Society), Polly Williams (The Royal Society), Dr Rachel Macdonald (the Academy of Medical Sciences), Bola Fatimilehin (the Royal Academy of Engineering) and Dr Laura Bellingan (the Royal Society of Biology) for their ongoing support and invaluable input into the content, design and analyses of the ASSET 2016 survey.

The ECU team is grateful to the more than 5000 respondents who donated their time to complete the survey and the dedicated staff of the 43 institutions who engaged with the project, without whom this nationally representative sample would not have been possible.

Further information

Dr Amanda Aldercotte [email protected]

Acknowledgements

Contents

© Equality Challenge Unit, October 2017

ASSET 2016

Experiences surrounding gender equality in engineering, and their intersections with ethnicity and disability

Executive summary 1

1 Introduction 8

2 Methods 92.1 The survey 92.2 The sample 92.3 Sample weighting 102.4 Data reduction 112.5 Presentation of results 12

3 Perceptions of gender equality 153.1 Perceived gender equality in respondents’ departments 153.2 Perceived gender equality in the allocation of tasks and resources 173.3 Perceived gender equality in obtaining senior posts 193.4 The impact of the Athena SWAN Charter 213.5 Beyond the gender gap: how do gender differences in

perceptions of gender equality vary by ethnicity and disability status? 22

4 Recruitment 244.1 How post was obtained 244.2 Interview panels 254.3 Decision to take up current post 254.4 Beyond the gender gap: how do recruitment processes

differ for STEMM academics belonging to more than one underrepresented group? 27

5 Job and career 295.1 Current posts 295.2 Time distribution across different academic duties 315.3 Life in the department 325.4 Factors influencing the average academic career 335.5 Factors influencing respondents’ academic careers 365.6 Beyond the gender gap: how do ethnicity and disability

intersect with gender in relation to the jobs and careers of STEMM academics in engineering? 42

6 Caring responsibilities, leave and career breaks 456.1 Maternity, paternity, adoption, shared parental or other

parental leave 456.2 Career breaks 546.3 Beyond the gender gap: how do caring responsibilities and

career breaks differ for STEMM academics belonging to more than one underrepresented group? 55

7 Training and leadership 577.1 Training opportunities 577.2 Training barriers 597.3 Beyond the gender gap: how do differences in training

opportunities and barriers differ across other characteristics? 63

8 Promotion and development 668.1 Explicit encouragement or invitation for promotion 668.2 Department’s encouragement of career development 678.3 Plans for future career 718.4 Beyond the gender gap: do individuals belonging to more

than one underrepresented group experience a unique path through the promotion and development process? 72

9 Conclusion 769.1 Key gender differences in engineering compared with STEMM

sciences in general 769.2 Summary of intersectional results 789.3 Recommendations 81

10 References 83

Appendix: sample characteristics 841.1 Gender 841.2 Ethnicity 851.3 Disability 86

Index 87

1October 2017

2 Perceptions of gender equality in engineering

1 Background to the Athena Survey of Science, Engineering and Technology 2016

Executive summary

The Athena Survey of Science, Engineering and Technology (ASSET) is a national survey of academics working in science, technology, engineering, mathematics and medicine (STEMM). ASSET 2016 was funded by The Royal Society, the Royal Academy of Engineering, the Royal Society of Biology and the Academy of Medical Sciences and was managed by Equality Challenge Unit (ECU).

The ASSET 2016 survey covered six aspects related to STEMM academics’ working life: perceptions of gender equality; recruitment; job and career; caring responsibilities, leave and career breaks; training and leadership; promotion and development.

By focusing on a subsample of respondents from the ASSET 2016 survey, the current report seeks to examine the experiences, expectations and perceptions of gender equality of academics in engineering. The current report also includes a novel discussion of how gender differences in these aspects of working life intersect with other protected characteristics, including ethnicity/race and disability.

The final weighted sample size was 868 respondents in engineering (602 men, 266 women) of which 173 identified as black or minority ethnic (BME) and 148 reported having disclosed as disabled.

Male respondents rated their department as more committed to gender equality than female respondents, although both genders were generally positive.

Female respondents felt that men in their department have an advantage in the allocation of tasks and resources related to professional development (eg receipt of mentoring, positive feedback from management, involvement in promotion decisions) and markers of esteem (eg invitations to conferences, recognition of intellectual contributions). In contrast, male respondents reported a perceived advantage for women in the allocation of tasks and resources related to professional development, but did not perceive an advantage for either gender with regard to the allocation of markers of esteem. Regarding the allocation of additional academic duties (eg teaching, administrative tasks), male respondents perceived an advantage for women while female respondents did not perceive an advantage for either gender.

2 ASSET report 2016: engineering

Executive summary

3.1 Intersectional results

3 Recruitment


Despite both genders reporting that it was slightly easier for a man to obtain a senior post in their department on average, female respondents reported a significantly stronger advantage for men than male respondents.

Gender and ethnicity: Female respondents were more likely to perceive an advantage for men in the allocation of tasks and resources related to professional development and markers of esteem than male respondents, regardless of their ethnicity. BME women and white women were both less positive about their department’s commitment to equality than BME men and white men.

Gender and disability: Compared with female respondents who had not disclosed as disabled, female respondents who disclosed as disabled not only reported a stronger advantage for men in the allocation of tasks and resources related to markers of esteem.

Although the majority of male and female respondents obtained their current post through an external advertisement (70.4% and 75.9%, respectively), proportionally more male respondents (15.6%) obtained their current post through a formal promotion than female respondents (7.5%).

Of those who were interviewed for their current post, 83.9% had more men than women on their interview panel. However, the difference between the proportions of male (7.3%) and female respondents (8.1%) who reported having more women than men on their interview panels was not significant.

Compared with male respondents, female respondents reported that the quality of life in the department were more influential in their decision to take their current post.

Gender and ethnicity: Proportionally more BME women than BME men had obtained their current post through an application for an advertised post (91.5% and 70.6%, respectively). On average, BME respondents rated their department’s commitment to equality as being more influential in their decision-making process than white respondents; however, BME women rated these indicators as more influential than BME men, white women and white men.

3October 2017

Executive summary

4 Job and career

Gender and disability: The proportion of men who disclosed as disabled (21.3%) who had obtained their current post by nomination or invitation was significantly larger than the proportion of men who had not disclosed as disabled (6.8%).

Female respondents were underrepresented in senior positions (eg head of school/division/department and professor) and overrepresented in early career positions (eg research fellow, researcher, research assistant and post-docs), even when age and contract type were taken into account.

Male and female respondents reported spending similar amounts of time on teaching, research, public engagement and clinical duties.

Both genders were relatively positive in their ratings of life in their department; however, male respondents viewed their departments as (i) more supportive, (ii) transparent and fair, and (iii) placing greater value on teaching, than female respondents.

Male and female respondents felt that the most beneficial factors for academic career progression were (i) being involved in well-regarded projects, (ii) successfully applying for grants, and (iii) having substantive research output. Both genders felt a heavy teaching load, a heavy administrative workload and taking a career break impeded academic career progression.

Female respondents rated the impact of having a family/children, protected characteristics and administrative duties on the average academic career more negatively than male respondents. In contrast, female respondents were more positive than male respondents about the impact of having sources of support. With regard to their own career progression, female respondents rated the impact of their sex, sexual orientation, marital or civil partnership status, gender identity, age and caring responsibilities more negatively than male respondents.

4.1 Intersectional results Gender and ethnicity: BME men rated their departments as more demanding of their time and effort than white men, but this difference was not present among BME and white women. BME men were also more positive about the impact of teaching experience on the average academic career than BME women, white women and white men.


Executive summary


5 Caring responsibilities, leave and career breaks

Overall, a significantly larger proportion of women (37.4%) had taken parental leave (ie maternity, paternity, additional paternity, adoptive, shared parental or unpaid parental leave) compared with the proportion of men who had taken such leave (22.8 %).

Regardless of whether they had previously taken parental leave, male respondents were more likely than female respondents to say that they (i) could relocate if necessary, (ii) could count on support from their family/partner, or (iii) feel involved in the social life of their department.

Both male and female respondents who had taken parental leave found that flexible working hours and keeping-in-touch (KIT) days were the most helpful options available in their department in preparing them to return to work. However, in general, female respondents felt less prepared to return from parental leave compared with male respondents.

Proportionally more female respondents (10.5%) had taken career breaks than male respondents (5.6%). Despite women being more likely to have taken a career break, the duration of men and women’s career breaks were similar. However, women who had taken both parental leave and a career break found it more difficult to return to work than men who had taken both forms of leave.

Gender and ethnicity: Although similar proportions of white female and BME female respondents had taken parental leave (37.2% and 38.2%, respectively), the proportions of BME female respondents with access to initial low research supervision, support networks and

Gender and disability: Investigating the intersection between gender and disability status revealed that there were a number of ways in which the opinions and experiences of female academics who disclosed as disabled were unique. For instance, women who disclosed as disabled rated the impact of having a family or children more negatively than female respondents who had not disclosed as disabled. Regarding their own career progression, female respondents who disclosed as disabled were significantly more negative about the impact of sex and having a disability on their own career progression than all other groups.

5October 2017

Executive summary


6 Training and leadership Of the ten training areas listed, it was only in administrative tasks related to management and professional development that men had more experience in than women.

Compared with men, larger proportions of women reported that time constraints, costs, ineligibility and caring responsibilities had blocked their access to training that they had needed or wanted in the last 12 months.

Gender and ethnicity: Compared with white male respondents, significantly larger proportions of BME male respondents had obtained training in postgraduate supervision, grant application skills and project planning/financial management skills. Conversely, the proportions of white male respondents who had obtained training in administrative tasks related to management and unconscious bias were significantly larger than the proportion of BME male respondents.

Gender and disability: Compared with female respondents who had not disclosed as disabled, significantly fewer female respondents who disclosed as disabled had obtained leadership training. The proportions of women who disclosed as disabled who had been unable to access training that they needed or wanted because they were ineligible or because it was not offered at their institution were significantly larger than all other groups.

shared parental leave were significantly larger than the proportions of white female respondents with access to these options.

Gender and disability: The difference between the proportions of men and women who disclosed as disabled who had taken parental leave (16.7% and 28.3%, respectively) or a career break (8.5% and 7.4%, respectively) was not significant. In contrast, among respondents who had not disclosed as disabled, proportionally more women had previously taken parental leave (24.1% and 39.8%, respectively) or a career break (11.3% and 5.1%, respectively) than men.


Executive summary


7 Promotion and development

The proportion of male respondents (60.0%) who reported that they were encouraged or invited to apply for a promotion or post at a higher grade did not significantly differ from the proportion of female respondents (55.1%) who reported this experience.

Compared with their female colleagues, male respondents in engineering were more likely to feel that their department encourages their career development and enjoy having a formally assigned mentor, the opportunity to serve on important departmental committees and feeling that their department values their research and external professional activities.

There were no significant differences in the proportions of male and female respondents who did not want to continue their careers in STEMM (5.4% and 2.7%, respectively) or who did want to continue their careers in STEMM but outside of higher education (8.2% and 6.1%, respectively).

Gender and ethnicity: There were no significant differences between the proportions of BME female respondents (45.3%), BME male respondents (56.9%), white female respondents (57.6%) and white male respondents (60.8%) who had been directly encouraged or invited to apply for promotion. However, the proportion of white male respondents (6.3%) who said that they did not want to continue their career in STEMM was significantly larger than the proportions of white female respondents (1.9%) and BME male respondents (1.7%) reporting this intention, but not BME female respondents (5.7%).

Gender and disability: There were no significant differences in the proportions of respondents who had previously been encouraged or invited to apply for promotion: 48.1% of women who disclosed as disabled, 55.3% of men who disclosed as disabled, 56.9% of women who had not disclosed as disabled and 60.9% of men who had not disclosed as disabled. However, regardless of gender, respondents who disclosed as disabled were less likely than respondents who had not disclosed as disabled to enjoy being encouraged to develop their career feeling that their department values their research and external professional activities, having access to senior staff, having a supportive line manager and feeling that their appraisal was useful and valuable.

7October 2017

Executive summary

8 Recommendations The following recommendations are driven by respondents’ reported experiences of gender equality and reinforced by their description of these experiences in the open-ended questions of the ASSET 2016 survey. While these recommendations are phrased in terms of alleviating discrepancies between men and women’s experiences in general, many could be adapted or used as a starting point for addressing the imbalances specific to the physical sciences or other imbalances, such as those related to the intersections between gender and ethnicity and gender and disability status.

= Develop mentoring or sponsorship programmes to increase the visibility of staff in early career posts (eg by increasing exposure to senior staff, clarifying promotion processes and providing opportunities to serve on departmental committees) (ECU 2012).

= Ensure academic contracts accommodate flexible working policies.

= Establish a set budget (time and money) for training programmes.

= Establish transparent workload allocation models that promote balance in the distribution of research, teaching and administrative duties among staff.

= Promote the development of supportive and career progressing networks (examples of good practice available in an ECU 2017 report for HEFCE).

= Ensure all staff have opportunities to engage with senior departmental staff.

= Explore options to offer analogous leave to staff caring for another adult to that offered to staff caring for children.

= Provide staff returning from parental or carer leave with additional options such as a low initial teaching or administrative workloads.

= Expand promotion criteria to include performance in other professional skills such as teaching and administrative experience.

= Reduce variability in the amount and type of support provided by line managers by ensuring that (i) line management duties are evenly distributed, (ii) line managers have the opportunity to develop their management skills (eg through management training programmes or unconscious bias training), and (iii) motivating line managers to prioritise these duties by increasing their accountability and adding incentives for being a good line manager.


1 Introduction

The most recent iteration of the national Athena Survey of Science, Engineering and Technology (ASSET) sought to examine the experiences, expectations and perceptions of gender equality of academics working in science, technology, engineering, mathematics and medicine (STEMM). ASSET 2016 was funded by The Royal Society, the Royal Academy of Engineering, the Royal Society of Biology and the Academy of Medical Sciences and was managed by Equality Challenge Unit (ECU).

Published in April 2017, the full ASSET 2016 report showed that from recruitment to promotion, female STEMM academics were more likely to perceive, experience or be exposed to some form of disadvantage compared with their male colleagues (ECU 2017).

The current report explores the experiences and perceptions of gender equality of academics working in engineering across six aspects of working life:

= perceptions of gender equality = recruitment = job and career = caring responsibilities, leave and career breaks = training and leadership = promotion and development

To provide additional insight into the gender experiences of academics in engineering, the current report also examines how gender differences in the above aspects of working life vary across individual sub-disciplines, including:

= electrical, electronic and computer engineering = general engineering = IT, systems sciences and computer software engineering = mechanical, aero and production engineering

This approach and the addition of qualitative data allows ASSET 2016 to paint a more detailed picture of current perceptions of gender equality in the physical sciences.

Finally, while the main focus of the current report is to identify and describe gender differences in the perceptions and experiences of academics in engineering, ASSET 2016 incorporates a novel exploration of the intersections between (i) gender and ethnicity/race, and (ii) gender and disability status.

9October 2017

2.2 The sample

2.1 The survey

2 Methods

Details on the development of the ASSET 2016 survey and the sampling method employed are available in the full report (ECU 2017). In sum, the survey underwent extensive piloting prior to being distributed to a cluster sample of 52 eligible higher education institutions (HEIs) that took into account the different locations (Scotland, Wales, Northern Ireland, England and London) and mission groups (University Alliance, Million+, GuildHE and Russell Group) of UK institutions. Over the course of four recruitment waves, 43 HEIs agreed to take part. Response rates were monitored and participating institutions were updated at regular intervals to encourage further engagement. The survey ran from March 2016 to June 2016.

ASSET 2016 contained six distinct sections relating to various aspects of experience within UK STEMM departments and a final monitoring section, which gathered equality and personal data on respondents.

The sections were:

= perceptions of gender equality = recruitment = job and career = caring responsibilities, leave and career breaks = training and leadership = promotion and development

The survey contained 89 questions in total, but the number of questions answered varied from respondent to respondent, since individuals were routed through the survey according to their own characteristics. For example, a respondent who had never taken maternity, paternity, adoption, shared parental or other parental leave did not complete the section on the options and resources surrounding parental leave.

Full details on the ASSET 2016 sample and the data cleaning processes employed to remove empty cases are available in the full report (ECU 2017).

The final unweighted subsample of academics in engineering contained 732 respondents from 43 institutions, of which 454 were male and 278 were female. The following analyses are


2 Methods

2.3 Sample weighting

limited to respondents who identified as ‘male’ or ‘female’. Gender differences are discussed in terms of ‘male respondents’ and ‘female respondents’ as well as ‘men’ and ‘women’, which ECU appreciates are not necessarily synonymous with the labels of male and female disclosed in the survey.

In order to ensure sample representativeness (UK STEMM academics), non-response weights were calculated using the Higher Education Statistics Agency (HESA) 2013/14 staff record (ECU 2015). Weights were based on gender (male or female), ethnicity (black or minority ethnic [BME] or white) and field of study (HESA cost centres). The full ASSET 2016 report describes how non-response weights were calculated and applied (ECU 2017).

The final weighted engineering subsample consisted of 868 respondents (602 men, 266 women). These numbers differ from those reported for the unweighted sample in the previous section because the weights applied were designed to obtain a more balanced gender distribution. However, as the weighting procedure also included ethnicity and field of study, applying the sample weights had a similar impact on the apparent size of these subsamples. This has been taken into account in the analysis which follows. Table 2.3.1 presents the distribution of male and female respondents across the individual academic fields belonging to the engineering discipline.

11October 2017

2 Methods

2.4 Data reduction

Table 2.3.1 Individual sub-disciplines by gender

All statistics reported from this point forward have been obtained from the weighted engineering subsample (see Appendix 1 of the full ASSET 2016 report for characteristics of the full ASSET 2016 weighted sample) (ECU 2017).

Engineering sub-discipline Female Male Total

No. % % No. % % No. %

Electrical, electronic and computer 20 7.5 15.6 108 17.9 84.4 128 14.7

General 46 17.3 33.3 92 15.3 66.7 138 15.9

IT, systems sciences and computer software

98 36.8 33.6 194 32.2 66.4 292 33.6

Mechanical, aero and production 45 16.9 31.5 98 16.3 68.5 143 16.5

Chemical, process and energy 21 7.9 40.4 31 5.1 59.6 52 6.0

Civil 26 9.8 31.3 57 9.5 68.7 83 9.6

Mineral, metallurgy and materials 10 3.8 31.3 22 3.7 68.8 32 3.7

Total 266 100.0 30.6 602 100.0 69.4 868 100.0

In consideration of the large number of survey questions in ASSET 2016, items relating to a similar topic were averaged into summary scores. Details regarding the principal components analyses used to determine whether closely related items captured a common concept are available in Appendix 2 of the full ASSET 2016 report (ECU 2017).

Average ratings on individual items and summary scores ranged from 1.00 to 7.00, with higher scores typically reflecting a more positive view (unless otherwise specified). For example, if respondents were asked to rate the impact of being a woman on the average academic career, a rating of 1.00 would reflect an extremely negative effect while 7.00 would indicate an extremely positive effect. Average ratings on individual items and summary scores ranging from 3.95 to 4.05 were considered ‘neutral’, or in this example, as having no effect.


2 Methods

2.5.3 Results related to individual sub-disciplines

2.5.2 Qualitative analyses

2.5 Presentation of results 2.5.1 Quantitative analyses

The quantitative results are presented in six separate sections. Use of the term ‘significant’ herein refers only to statistically significant differences (at the p < .05 level).

Except for analyses in which proportions of total men and women were compared, all analyses controlled for respondents’ current age (and where applicable, also respondents’ current posts) in order to determine whether gender differences were specifically related to respondents’ declared gender.

Visual representations of gender differences presented in this report are based on average ratings, summary scores or the proportion of respondents within each gender. Where possible, visual representations are accompanied by 95% confidence intervals around average ratings and summary scores, to facilitate identifying which differences are statistically significant. If two statistics have non-overlapping 95% confidence intervals, they are necessarily significantly different. However, there are instances where two statistics may have overlapping 95% confidence intervals but are still significantly different so interpretation of these confidence intervals should be completed alongside the results reported in the text.

Within each section of the ASSET 2016 survey, respondents were given the opportunity to expand and reflect upon the content of that section in a free text response. The qualitative data were coded inductively and emerging themes were used to inform the case studies included in vignettes throughout this report. Relevant quotations from these open responses were selected to provide additional insight into the mechanisms underlying respondents’ perceptions and experiences.

Within each section, comparisons of how respondents’ perceptions and experiences differ across four main sub-disciplines are presented:

= electrical, electronic and computer engineering = general engineering = IT, systems sciences and computer software engineering = mechanical, aero and production engineering

13October 2017

2 Methods

Table 2.5.4.1 Sample sizes by gender and protected characteristic of interest

2.5.4 Intersectionality This report explored the intersection between gender and two protected characteristics (ethnicity/race and disability status), which are presented at the end of each section. To summarise these intersections succinctly, these subsections only describe statistically significant findings; areas in which no difference between groups was found are not discussed.

Ethnicity/race and disability status were selected because the number of respondents possessing such characteristics in the subsample of respondents in engineering was sufficient for quantitative analyses (see Table 2.5.4.1).

Protected characteristic Female Male Total

No. % No. % No.

Ethnicity

BME 54 31.2 119 68.8 173

White 211 30.4 484 69.6 695

Disability status

Had not disclosed as disabled 213 29.5 509 70.5 722

Had disclosed as disabled 54 36.5 94 63.5 148

To explore the intersection between gender and ethnicity, the following minority groups were aggregated into a single BME group (based on the 2011 census classification system):

= Asian – Asian Indian, Asian Pakistani, Asian Bangladeshi, Asian British and Asian other

= black – black Caribbean, black African, black British and black other = Chinese = mixed = other ethnic background

While this definition of BME status is widely recognised and used to identify patterns of marginalisation and segregation caused by attitudes towards an individual’s ethnicity, ECU recognises its limitations, particularly the erroneous assumption that minority ethnic individuals are a homogeneous group.


2 Methods

The phrase ‘respondents who disclosed as disabled’, or equivalent, is used throughout the report to refer to those who indicated that they had: a specific learning disability; a general learning disability; a social/communication impairment; a long-standing illness or long-term health condition; a mental health condition; a physical impairment or mobility issues; deafness or serious hearing impairment; blindness or a serious visual impairment. The phrase ‘respondents who had not disclosed as disabled’ was used for respondents who did not report a disability and did not specify that they did not wish to disclose this information (ie individuals who indicated that they would ‘prefer not to say’ were excluded from these analyses).

10.1%

1.7%

88.2%

More women than men

Roughly equal numbers of women and men

More men than women

15October 2017

Figure 3.1.1 Ratings of department gender distribution by gender

Table 3.1.1 Ratings of department’s commitment to gender equality

3.1 Perceived gender equality in respondents’ departments

3 Perceptions of gender equality

On average, male respondents were more positive about their department’s commitment to gender equality than female respondents (see Table 3.1.1). Specifically, men agreed more strongly with items relating to their department’s commitment to gender equality.

Female Male

Department’s commitment to gender equality summary score 4.52 5.16

In general, men and women are equally well represented (in numbers) in my department 2.76 3.08

In general, men and women are treated equally in my department 4.81 5.74

My department is committed to promoting gender equality in STEMM 5.14 5.82

If I had concerns about gender equality in my dept, I would know who to approach 4.90 5.38

My department is (or would be) responsive to concerns about gender equality 5.05 5.69

The first section of the ASSET 2016 survey explored respondents’ perceptions of gender equality, focusing on (i) their department’s commitment to gender equality, (ii) how resources are allocated in their department, and (iii) the ease with which senior posts are obtained. This section also included questions regarding the perceived impact of Athena SWAN initiatives.

However, it is worth noting that while male respondents’ ratings were higher than female respondents’ on average, both genders were positive about their department’s commitment to gender equality in general. Lastly, the majority of both male and female respondents estimated that there are more men than women in their department (see Figure 3.1.1).

4.34

4.84

5.08

5.04

4.32

5.19

4.75

5.27

Electrical Female

Male

GeneralFemale

Male

IT Female

Male

Mechanical Female

Male

NeutralSlightlypositive

4.00 4.40 4.80 5.20



Case study: departmental commitment to gender equality dependent on sub-discipline

On average, respondents in mechanical, aero and production engineering tended to view their department’s commitment to gender equality more positively than respondents in electrical, electronic and computer engineering. However, gender differences between men and women’s perceptions of their department’s commitment to gender equality varied within the individual sub-disciplines: for instance, both male and female respondents rated their department’s commitment in a similar manner in the sub-disciplines of electrical, electronic and computer engineering and general engineering (see Figure 3.1.2). Conversely, male respondents in IT, systems sciences and computer software engineering and mechanical, aero and production engineering were significantly more positive than female respondents in these sub-disciplines.

Figure 3.1.2 Department commitment to gender equality by gender and sub-discipline

Note. Error bars are based on 95% confidence intervals.

3.94

4.48

4.01

4.36

3.94

4.03

NeutralAdvantage

for men

4.00 4.20 4.40Professional developmentFemale

Male

Markers of esteemFemale

Male

Additional academic dutiesFemale

Male

17October 2017


3.2 Perceived gender equality in the allocation of tasks and resources

Respondents were asked to rate whether they perceived an advantage towards women or an advantage towards men across 18 items describing the allocation of tasks and resources in their department. These items were averaged into three summary scores reflecting the allocation of tasks and resources related to: (i) professional development (eg receipt of mentoring, attention from senior management); (ii) markers of esteem (eg distribution of laboratory space or equipment, invitations to conferences); (iii) additional academic duties (eg allocation of teaching, administrative or pastoral tasks) (ECU 2017).

Regarding the allocation of tasks and resources related to professional development, female respondents were more likely to perceive an advantage towards men than male respondents, who tended to perceive a slight advantage for women in this area (see Figure 3.2.1). Female respondents were also more likely to perceive an advantage for men in the allocation of markers of esteem, whereas male respondents rated these items more neutrally (ie perceiving no advantage for either gender). In contrast, while female respondents perceived no advantage for either gender in the allocation of additional academic duties, male respondents perceived an advantage for women in this area.

It is worth noting however that while these differences are statistically significant, they are relatively small in size (eg average summary scores were out of 7.00 and these were 3.92 for men and 4.03 for women regarding the allocation of additional academic duties).

Figure 3.2.1 Perceived allocation of tasks and resources by gender


4.24

3.92

4.00

3.97

3.98

3.92

4.12

3.97

Electrical Female

Male

GeneralFemale

Male

IT Female

Male

Mechanical Female

Male


4.00 4.203.80 4.40



Case study: teaching and other academic duties across sub-disciplines

Respondents’ perceptions surrounding the allocation of additional academic duties (eg teaching, administrative tasks) varied considerably across the individual sub-disciplines. For instance, in the overall engineering sample male respondents reported a perceived advantage for women in the allocation of these tasks while female respondents did not perceive an advantage for either gender. However, within the sub-discipline of electrical, electronic and computer engineering, these perceptions were partially reversed: female respondents reported a perceived advantage for men in the allocation of additional academic duties while male respondents felt that women had a slight advantage in this area (see Figure 3.2.2). In contrast, the gaps between male and female respondents’ perceptions within the other sub-disciplines were not significant and, in the case of general engineering and IT, systems sciences and computer software engineering, tended to be neutral.

Figure 3.2.2 Perceived allocation of additional academic duties by gender and sub-discipline


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3.3 Perceived gender equality in obtaining senior posts

Closer look: allocation of tasks

Female academics commented on the distribution of tasks between men and women:

‘Women are passed over for prestigious tasks, whilst less able men are given them, and the women are made to do the degrading and unintellectual tasks (pastoral care, general admin, etc).’

Female, electrical, electronic and computer engineering

In some instances, where women were given the opportunity to undertake similar tasks as men, senior management could still have a negative impact by wrongly taking credit for their work:

‘Being a woman allows by default that senior management can take credit for the outcomes of the hard work carried out by women. This is more the case with minority ethnicity. Gender/ethnicity plays a key role in taking people for granted in that there is an assumption that key matters need not be discussed with the individuals.’

Female, electrical, electronic and computer engineering

Despite both genders reporting that it was slightly easier for a man to obtain a senior post in their department on average, female respondents reported a significantly stronger advantage for men than male respondents. As seen in Figure 3.3.1, the proportion of female respondents reporting that it was ‘much easier for a man’ to obtain a senior post was almost six times the proportion of male respondents endorsing this option; the majority of male respondents rated this item neutrally.

0.8

0.0

2.9

0.4

5.9

0.0

52.7

26.5

20.3

24.2

13.7

27.8

3.8

21.1

Much easier for a womanFemale

Male

Easier for a womanFemale

Male

Slightly easier for a womanFemale

Male

The same for women and menFemale

Male

Slightly easier for a manFemale

Male

Easier for a manFemale

Male

Much easier for a manFemale

Male

10% 20% 30% 40% 50%



Figure 3.3.1 Proportion of respondents’ ratings of ease in obtaining senior post by gender

21October 2017


3.4 The impact of the Athena SWAN Charter

Overall, 14.7% of respondents had not heard of the Athena SWAN Charter in their department and an additional 1.7% of respondents reported that Athena SWAN initiatives were not run in their departments. Proportionally more male respondents (18.4%) had not heard of Athena SWAN in their departments than female respondents (5.4%).

Among respondents who were aware of Athena SWAN, both genders tended to agree that these initiatives had a positive impact on the work environment in their department and institution as whole. There were no differences in how men and women rated the impact of Athena SWAN in their department or institution.

Closer look: men’s attitudes to gender equality initiatives

Male engineers perceived initiatives to improve gender equality, such as Athena SWAN, in different ways. Some understood these initiatives as a necessary tool to correct historical imbalances, whereas others shared the view that they felt disadvantaged as white and male:

‘It is clearly the case that female staff seem to be significantly advantaged as this represents a corporate goal. I am also aware that although this may be ‘unfair’ to male staff it is not necessarily unlawful and may simply be a readjustment of the historical position. Nonetheless from a male perspective paths to career advancement and the development of a healthy work life balance remain as complex and partisan as ever. It seems we are developing a dual or twin-track culture of academic expectation and at some point in the future this will have to be addressed. This also will also demand a readjustment of the historical position.’

Male, electrical, electronic and computer engineering

‘It was easier for men in the past because the previous generation tended to have wives who would make sacrifices for their careers; this is (quite rightly) not the case for either gender now, but some old stagers got further, faster than we can as a result.’

Male, civil engineering

‘It is certainly an advantage to be non-male and non-white at the moment. Given two equal candidates one would strongly prefer the non-white male and even given unequal candidates I would prefer the non-white male.’

Male, IT, systems sciences and computer software engineering

4.55

4.47

3.86

3.97

4.35

4.36

3.97

4.02

NeutralAdvantage

for menAdvantagefor women

3.80 4.00 4.20 4.40 4.60Professional developmentBME female

White female

BME male

White male

Markers of esteemBME female

White female

BME male

White male



Figure 3.5.1.1 Perceived allocation of tasks and resources by gender and ethnicity

3.5 Beyond the gender gap: how do gender differences in perceptions of gender equality vary by ethnicity and disability status?

3.5.1 Gender and BME

Investigating the intersection between gender and ethnicity revealed that many of the gender differences reported for the sample of respondents in engineering remained regardless of respondents’ ethnicity. For instance, female respondents were more likely to report a perceived advantage for men in the allocation of tasks and resources related to professional development and markers of esteem, regardless of their ethnicity (see Figure 3.5.1.1). Similarly, BME women and white women were both less positive about their department’s commitment to equality than BME men and white men.


Finally, although female respondents felt that it was easier for a man to obtain a senior post than male respondents overall, on average BME respondents tended to be slightly more neutral in their rating of this item than white respondents (on a scale of 1 through 7, BME respondents’ average rating was 4.51 compared with the 4.81 average rating of white respondents).

4.63

4.45

3.97

3.94

4.63

4.29

4.09

3.99

4.20

3.98

3.97

3.93

Professional developmentDisabled female

Non-disabled female

Disabled male

Non-disabled male

Markers of esteemDisabled female

Non-disabled female

Disabled male

Non-disabled male

Additional academic dutiesDisabled female

Non-disabled female

Disabled male

Non-disabled male

NeutralAdvantage

for menAdvantagefor women

4.00 4.20 4.40 4.60

23October 2017


Figure 3.5.2.1 Perceived allocation of tasks and resources by gender and disability status

3.5.2 Gender and disability status


In general, compared with male respondents, female respondents reported a perceived advantage for men in the allocation of tasks and resources in all three areas (see Figure 3.5.2.1). However, female respondents who disclosed as disabled reported a stronger advantage for men in the allocation of tasks and resources related to markers of esteem than female respondents who had not disclosed as disabled.

1.5

2.5

15.6

7.5

9.2

9.5

70.4

75.9

3.3

4.6

10% 20% 30% 40% 50% 60% 70%Ad hoc promotionFemale

Male

Formal promotion roundFemale

Male

Invitation/nominationFemale

Male

Application for advertised postFemale

Male

Other (eg fellowship/grant)Female

Male


Figure 4.1.1 Recruitment method by gender

4.1 How post was obtained

4 Recruitment

The majority of men and women had obtained their current post through an external advertisement (see Figure 4.1.1). However, proportionally more men (15.6%) had obtained their current post through a formal promotion compared with women (7.5%).

Respondents were asked how they had obtained their current post and the factors that influenced their decision to take the position. If respondents had been interviewed for their post, they were asked to provide details about the number of men and women on their interview panel(s).

25October 2017

4 Recruitment

Table 4.3.1 Breakdown of summary scores and average ratings across items related to respondents’ decision to take their current post

4.3 Decision to take up current post

4.2 Interview panels To calculate the average proportion of women on respondents’ interview panels, the total number of women on the interview panel was divided by the total number of panellists. These scores ranged from 0 (ie no women on the interview panel) to 1 (ie only women on the interview panel).

Overall, only 9.2% of respondents’ recalled having an equal number of men and women on their interview panels with an additional 6.9% indicating that there had been more women than men on their interview panel. This means that 83.9% of respondents recalled having more men than women on their interview panel. However, the difference between the proportions of male (7.3%) and female respondents (8.1%) who recalled having more women than men on their interview panels was not significant.

The ASSET 2016 survey included seven items regarding why respondents decided to accept their post. These were averaged into two summary scores reflecting (i) the quality of working life in that department and (ii) the department’s commitment to equality (see Table 4.3.1).

Summary scores Female Male

Quality of working life 2.86 2.54

Flexibility of working hoursWork/life balance offeredDiverse and inclusive working environmentReputation for training or career development

3.242.692.762.74

2.752.492.472.42

Commitment to equality 1.48 1.33

Childcare facilities availableAn Athena SWAN awarded to the departmentStaff networks (eg LGBTQ group)

1.451.511.45

1.341.321.30

On average, female respondents reported that the quality of life in the department was more influential in their decision than male respondents. In contrast both men and women rated their department’s commitment to equality as being only slightly influential in their decision-making process.

3.44

3.20

2.60

2.36

2.61

2.87

2.47

2.87

Electrical Female

Male

GeneralFemale

Male

IT Female

Male

Mechanical Female

Male

Neutral In�uential

2.00 2.40 2.80 3.20 3.60


4 Recruitment

Case study: deciding to take a post in the individual sub-disciplines

Men and women in IT, systems sciences and computer software engineering and mechanical, aero and production engineering rated the factors reflecting the quality of working life and a department’s commitment to equality in a similar manner (see Figures 4.3.1 and 4.3.2). This was not the case among respondents in electrical, electronic and computer engineering or general engineering: compared with men, women in these sub-disciplines rated their department’s commitment to equality as more influential in deciding to take their current post. Women in general engineering were also more likely to rate the factors reflecting working life as more influential than men in general engineering (although this gender difference was not present among men and women in electrical, electronic and computer engineering).

Figure 4.3.1 Influence of quality of working life in taking up current post by gender and sub-discipline


2.06

1.78

1.37

1.33

1.19

1.65

1.21

1.53

Electrical Female

Male

GeneralFemale

Male

IT Female

Male

Mechanical Female

Male

NeutralNot in�uential

1.00 1.20 1.40 1.60 1.80 2.00 2.20 2.40

27October 2017

4 Recruitment

4.4 Beyond the gender gap: how do recruitment processes differ for STEMM academics belonging to more than one underrepresented group?


Beyond the gender difference in formal promotions reported for the overall engineering sample, an exploration of the intersection between gender and ethnicity revealed an additional gap between BME men and BME women: proportionally more BME women than BME men had obtained their current post through an application for an advertised post (91.5% and 70.6%, respectively).

Figure 4.3.2 Influence of commitment to equality in taking up current post by gender and sub-discipline


It is worth noting however that while respondents in IT, systems sciences and computer software engineering rated their department’s commitment to equality as less influential in their decision to take up their current post than respondents in any other sub-discipline (regardless of their gender), this difference between sub-disciplines was not present for the items reflecting the quality of working life.

2.15

1.31

1.69

1.23

Department’s equality commitment BME female

White female

BME male

White male

Neutral In�uentialNot at allin�uential

2.00 2.201.801.601.401.20


4 Recruitment


Figure 4.4.1.1 Influence of commitment to equality in taking up post by gender and ethnicity

On average, BME respondents rated their department’s commitment to equality as being more influential in their decision-making process than white respondents; however, BME women rated these indicators as more influential than BME men, white women and white men (see Figure 4.4.1.1).


Proportionally more men were formally promoted to their current post than women, regardless of their disability status. However, an additional contrast in the recruitment methods reported by respondents in engineering was uncovered when the intersection between gender and disability status was explored: the proportion of men who disclosed as disabled (21.3%) who had obtained their current post by nomination or invitation was significantly larger than the proportion of men who had not disclosed as disabled (6.8%).

29October 2017

Table 5.1.1 Current posts by gender

5.1 Current posts

5 Job and career

To compare whether there were gender differences in the current posts held by respondents, we looked at the overall proportions of men and women within each position and whether these proportions were significantly different from one another.

As seen in Table 5.1.1, women were underrepresented in senior positions (eg head of school/division/department and professor) and overrepresented in early career positions related academic research (eg research fellow, researcher, research assistant and post-docs). This gender difference between male and female respondents’ current posts remained when respondents’ age and contract type (eg teaching only, combined research and teaching) were taken into account.

Current post Female Male TotalNo. % % No. % % No. %

Head/director of major academic area 9 3.4 34.6 17 2.8 65.4 26 3.0

Head of school/division/department 8 3.0 19.5 33 5.5 80.5 41 4.8

Centre director 4 1.5 44.4 5 0.8 55.6 9 1.0

Senior function head 1 0.4 7.7 12 2.0 92.3 13 1.5

Professor 22 8.3 20.8 84 14.0 79.2 106 12.3

Associate professor 3 1.1 9.7 28 4.7 90.3 31 3.6

Function head 3 1.1 42.9 4 0.7 57.1 7 0.8

Senior/principal lecturer (pre-1992 university) 35 13.3 27.6 92 15.4 72.4 127 14.7

Reader, principal research fellow 7 2.7 21.2 26 4.3 78.8 33 3.8

Senior lecturer (post-1992 university) 43 16.3 36.1 76 12.7 63.9 119 13.8

Lecturer 52 19.7 31.5 113 18.9 68.5 165 19.1

Teaching fellow 10 3.8 35.7 18 3.0 64.3 28 3.2

Researcher, research fellow, senior research assistant

29 11.0 42.6 39 6.5 57.4 68 7.9

Post-doc, post-doc research assistant 19 7.2 51.4 18 3.0 48.6 37 4.3

Research assistant 3 1.1 27.3 8 1.3 72.7 11 1.3

Teaching assistant 1 0.4 33.3 2 0.3 66.7 3 0.3

Technical staff 1 0.4 9.1 10 1.7 90.9 11 1.3

Other 14 5.3 51.9 13 2.2 48.1 27 3.1

Total 264 100.0 30.6 598 100.0 69.4 862 100.0

40.0

30.0

36.4

21.4

38.8

45.5

30.2

28.5

22.3

26.4

60.0

70.0

63.6

78.6

61.2

54.5

69.8

71.5

77.7

73.6

20% 40% 60% 80%

Less than £17,500

£17,500–£22,439

£22,440–£27,374

£27,375–£32,314

£32,315–£37,249

£37,250–£42,189

£42,190–£47,124

£47,125–£52,064

£52,064–£57,000

More than £57,000

Female Male


5 Job and career

Figure 5.1.1 Salary band by gender

Similarly, a larger proportion of female respondents were in part-time positions (15.6%) or on fixed-term contracts (31.3%), compared with male respondents (6.6% and 17.9%, respectively). In contrast, the proportions of male and female respondents on teaching-only contracts was not significant (35.5% and 36.3%, respectively). Despite differences in their current posts and contracts, the gap between male and female respondents’ reported salary bands was not significant. In other words, the proportion of female respondents within each salary band is not significantly different from what would be expected given the proportion of female respondents in engineering (30.6%) (see Figure 5.1.1).

Closer look: the lack of female academics in engineering

Respondents commented on what they saw as the lack of female academics in engineering and the problems this created throughout the career pipeline:

‘What concerns me is a lack of young, early career female academics applying for posts. I do not think that this is an institutional problem, but actually a sector and discipline wide concern.’

Male, mechanical, aero and production engineering

‘Engineering traditionally has low women numbers so expect that most senior positions proportionally are filled by men. This is not

31October 2017

5 Job and career

5.2 Time distribution across different academic duties

gender bias this is the reality of the current proportional status of male-female balance in Engineering.’

Male, electrical, electronic and computer engineering

Even though there was less women than men in engineering, this respondent noted that more could be done to tackle this issue:

‘I do not believe there is any form of active discrimination against women, but nor any positive discrimination to address the gender imbalance in general. However, there are more men in the department which could be down to indirect discrimination through poor advertising of positions or ease of women to re-enter the work place after having a family.’

Male, chemical, process and energy engineering

The ASSET 2016 survey included 19 items regarding how respondents distributed their time across their various tasks. These items were grouped to reflect how much time respondents spent on:

= teaching (eg course development, undergraduate lectures, academic advising)

= research (eg running research projects, writing papers, applying for grants)

= public engagement = clinical duties

The summary scores on these four duties ranged from 1 (‘none of my time’) to 5 (‘all or almost all of my time’).

Notably, male and female respondents rated each of these areas similarly (see Figure 5.2.1). Specifically, men and women reported spending similar amounts of their time on teaching, research, public engagement and clinical duties.

2.52

2.56

1.88

1.94

1.87

1.84

1.06

1.10

TeachingFemale

Male

ResearchFemale

Male

Public engagement Female

Male

Clinical dutiesFemale

Male

Signi�cant portion

of my timeNone ofmy time

1.401.20 1.60 1.80 2.00 2.20 2.40 2.60


5 Job and career

5.3 Life in the department

Figure 5.2.1 Time spent on academic duties by gender


The ASSET 2016 survey included 14 items that described respondents’ academic environment which were subsequently grouped into four categories describing whether respondents felt that their department was:

= a supportive environment = characterised by fairness and transparency in its allocation of overall

workload and resources (eg office space, budget) = likely to place value on teaching = demanding of their time and effort

Although both genders were relatively positive in their ratings of life in their department, men viewed their departments as (i) more supportive, (ii) transparent and fair, and (iii) placing greater value on teaching than women (see Figure 5.3.1).

In contrast, men and women had similar ratings of how demanding their department was of their time and effort, with both genders expressing a relatively positive view regarding these demands.

4.97

5.18

4.03

4.38

4.77

5.09

3.70

3.63

Supportive environmentFemale

Male

Fairness and transparencyFemale

Male

Value teachingFemale

Male

Demands on time and e�ortFemale

Male

NeutralSlightlyagree

3.803.60 4.00 4.20 4.40 4.60 4.80 5.00 5.20

33October 2017

5 Job and career

5.4.1 Top factors of influence in the average academic career

5.4 Factors influencing the average academic career

Figure 5.3.1 Ratings of life in their department by gender


Respondents were asked to rate the impact of a number of protected characteristics and academic qualities on the average academic career. Scores ranged from 1 (indicating a strong negative impact) to 7 (indicating a strong positive impact), with a rating of 4 being considered neutral.

Both men and women agreed that (i) having substantive research output, (ii) successfully applying for grants, and (iii) being involved in well-regarded projects were the three most positive factors in progressing the average academic career (see Table 5.4.1.1).


5 Job and career

Table 5.4.1.1 Average ratings of all factors impacting the average academic career by gender

* A significant difference between average ratings from male and female respondents

† Three factors with the most positive ratings

‡ Three factors with the most negative ratings

Factors Female Male

Being a woman* 3.29 4.04

Being married, civil-partnered or cohabiting 4.15 4.15

Having a supportive family and/or partner* 5.93 5.62

Being older than average in the field 3.63 3.69

Being younger than average 4.16 4.19

Having a non-heterosexual sexual orientation* 3.88 3.95

Having a non-white ethnic identity 3.77 3.85

Having a particular set of religious beliefs (including atheism)

3.91 3.94

Having a transgender identity* 3.56 3.76

Having disclosed a disability to an employer* 3.73 3.93

Requiring reasonable adjustments to be made to the working environment*

3.77 4.11

Not having children or other caring responsibilities*

5.26 4.61

Taking maternity, paternity, shared parental, adoption or any other form of parental leave*

3.17 3.57

Extensive administrative experience* 4.12 4.45

Extensive experience of public engagement 5.16 5.07

Extensive teaching experience* 4.56 4.79

Having good references from a previous post 5.36 5.30

Having teacher training (eg the Postgraduate Certificate in Academic Practice)

4.75 4.78

Possessing an award in recognition of teaching skill

4.96 4.93

Being able to easily move geographic location* 5.69 5.27

Being able to work long hours* 5.58 5.25

Recruiting multiple PhD students 5.44 5.45

Involved in well regarded projects† 6.24 6.14

35October 2017

5 Job and career

5.4.2 Gender differences in perceived areas of impact

Successfully applying for grants† 6.43 6.36

Having substantive research output† 6.45 6.37

Flexible working hours 4.83 4.81

Receiving formal and regular mentoring* 5.42 5.10

Receiving support or encouragement from senior colleagues*

5.98 5.51

Receiving support/encouragement* 5.76 5.41

Having visible role models* 5.55 5.02

Having a heavy administrative load*‡ 2.37 2.67

Having a heavy teaching load‡ 2.58 2.74

Taking a career break*‡ 2.73 3.25

Being lucky 5.18 5.17

Male and female respondents also agreed that (i) having a heavy administrative load, (ii) having a heavy teaching load, and (iii) taking a career break would have the most negative impact on the average academic career. However, female respondents saw administrative workload and career breaks as more detrimental to the average academic career than men.

These individual items were combined into categories to explore gender differences across six areas of impact:

= an esteemed reputation = family/children = sources of support = protected characteristics = teaching experience = administrative duties

On average, women rated the impact of having a family/children, protected characteristics and administrative duties on the average academic career more negatively than men. In contrast, women were more positive than men about the impact of having sources of support (see Figure 5.4.2.1). However, it is worth noting that, while statistically significant, these gender differences were relatively small. Finally, although men and women did not differ in how they rated

2.78

5.69

6.36

3.71

4.73

3.41

2.98

5.32

6.29

3.92

4.85

3.66

Family/childrenFemale

Male

Sources of supportFemale

Male

Esteemed reputationFemale

Male

Protected characteristicsFemale

Male

Teaching experienceFemale

Male

Administrative dutiesFemale

Male


Slightlynegative

3.00 4.00 5.00

Positive

6.00


5 Job and career

5.5 Factors influencing respondents’ academic careers

Figure 5.4.2.1 Areas of perceived impact on the average academic career by gender

the impact of having an esteemed reputation, men were more positive than women regarding the impact of teaching experience on the average academic career.


Respondents were also asked to rate how they felt possessing certain protected characteristics had impacted their own careers.

On average, women reported that their sex, sexual orientation, marital or civil partnership status and gender identity had had a negative impact on their own academic career progression while men rated these items in a neutral manner. Female respondents were also more negative than male respondents in their ratings of age and

3.74

3.93

4.00

3.93

3.94

3.96

3.62

3.62

3.74

4.02

3.99

3.94

4.04

3.99

3.98

3.92

3.86

4.01

SexFemale

Male

Sexual orientationFemale

Male

EthnicityFemale

Male

Marital/civil statusFemale

Male

Disability statusFemale

Male

Religious beliefsFemale

Male

Caring responsibilitiesFemale

Male

AgeFemale

Male

Gender identityFemale

Male

NeutralSlightly

negative

3.60 3.80 4.00

37October 2017

5 Job and career

Figure 5.5.1 Areas of perceived impact on respondents’ academic careers by gender

caring responsibilities (although both genders felt that these had negatively impacted their own careers) (see Figure 5.5.1).


3.31

4.04

3.90

4.02

3.74

4.01

3.68

4.02

Electrical Female

Male

GeneralFemale

Male

IT Female

Male

Mechanical Female

Male

3.603.20

Neutral4.00

Slightlynegative


5 Job and career

Notably, there were no significant differences in how men and women rated the impact of ethnicity, disability status and religious beliefs.

Case study: respondents’ career progression in electrical, electronic and computer engineering compared with other sub-disciplines

Exploring how respondents’ opinions of their own career progression differed between the individual sub-disciplines revealed an important distinction; female respondents in electrical, electronic and computer engineering were significantly more negative about the impact of sex on their own career progression than female respondents in any other sub-discipline (see Figure 5.5.2). Notably, male respondents rated the impact of sex in a neutral manner, regardless of their sub-discipline, and these ratings were consistently more positive than those reported by female respondents.

Figure 5.5.2 Perceived impact of sex on respondents’ own career progression by gender and sub-discipline


3.81

3.99

3.97

4.00

3.97

3.94

3.79

4.02

Electrical Female

Male

GeneralFemale

Male

IT Female

Male

Mechanical Female

Male

3.80

Neutral4.00

Slightlynegative

39October 2017

5 Job and career

Female respondents in electrical, electronic and computer engineering were also more negative about the impact of their sexual orientation than female respondents in general engineering and IT, systems sciences and computer software engineering (see Figure 5.5.3). However, female respondents in mechanical, aero and production engineering were also considerably more negative about the impact of sexual orientation than female respondents in general engineering and IT, systems sciences and computer software engineering. In contrast to respondents’ perceptions of sex, gender differences in how respondents’ rated the impact of sexual orientation were not consistent across sub-disciplines: specifically, male and female respondents in general engineering and IT, systems sciences and computer software engineering both rated this item in a relatively neutral manner.

Figure 5.5.3 Perceived impact of sexual orientation on respondents’ own career progression by gender and sub-discipline



5 Job and career

Table 5.5.1.1 Perceived impact of protected characteristics on own versus average academic career by gender

5.5.1 Impact of protected characteristics on the average academic career versus respondents’ own

Finally, we looked at whether there were differences in how respondents rated the impact of the nine protected characteristics on their own versus the average academic career. There were discrepancies between ratings on respondents’ own and the average academic career for both genders (see Table 5.5.1.1).

Protected characteristic

Female Male Overall

Aver-age

Own career

Aver-age

Own career

Aver-age

Own career

Sex 3.29 3.75 4.04 4.04 3.81 3.95

Sexual orientation 3.88 3.95 3.95 3.99 3.93 3.98

Ethnicity 3.77 3.99 3.85 3.97 3.83 3.98

Marital/civil status 4.15 3.94 4.15 4.04 4.15 4.01

Disability status 3.73 3.98 3.93 3.99 3.87 3.99

Religious beliefs 3.91 3.97 3.94 3.97 3.93 3.97

Caring responsibilities 3.17 3.64 3.57 3.91 3.45 3.83

Age 3.90 3.61 3.94 3.85 3.93 3.78

Gender identity 3.56 3.73 3.76 4.01 3.7 3.93

In general, both male and female respondents rated the impact of these characteristics more negatively when judging the average academic career versus their own (Figure 5.5.1.1). For example, both groups felt that the impact of ethnicity on the average academic career was more negative than the impact ethnicity has had on their own career. Notably, male respondents’ ratings of the impact of sex did not differ across their own versus the average academic career, whereas women were more negative about the impact of sex on the average academic career than they were on their own. In contrast, both genders were more positive about the impact of marital/civil status and age when rating the average academic career compared with how they rated their own careers.

3.75

3.95

3.99

3.94

3.98

3.97

3.64

3.61

3.73

4.04

3.99

3.97

4.04

3.99

3.97

3.91

3.85

4.01

NeutralSlightly

negative

3.60 3.80 4.00

(own career average )

SexFemale

Male

Sexual orientationFemale

Male

EthnicityFemale

Male

Marital/civil statusFemale

Male

Disability statusFemale

Male

Religious beliefsFemale

Male

Caring responsibilitiesFemale

Male

AgeFemale

Male

Gender identityFemale

Male

3.29

3.88

3.77

4.15

3.73

3.91

3.17

3.90

3.56

4.04

3.95

3.85

4.15

3.93

3.94

3.57

3.94

3.76

41October 2017

5 Job and career

Figure 5.5.1.1 Perceived impact of protected characteristics on own and average academic career by gender


3.76

3.69

3.97

3.54

Demands on time and e�ortBME female

White female

BME male

White male

Neutral AgreeDisagree4.003.803.60

4.73

4.73

5.20

4.75

Impact of teaching experienceBME female

White female

BME male

White male

Neutral Agree

4.00 4.80 5.204.40


5 Job and career

Figure 5.6.1.2 Perceived impact of teaching experience on the average academic career by gender and ethnicity

Figure 5.6.1.1 Ratings of departmental demands on time and effort by gender and ethnicity

5.6 Beyond the gender gap: how do ethnicity and disability intersect with gender in relation to the jobs and careers of STEMM academics in engineering?


Examining the intersection between gender and ethnicity revealed two results specific to BME men: first, BME men rated their departments as more demanding of their time and effort than white men, while this difference was not present among BME and white women (see Figure 5.6.1.1). Second, BME men were also more positive about the impact of teaching experience on the average academic career than BME women, white women and white men (see Figure 5.6.1.2).



1.78

2.17

2.59

2.55

Family/childrenDisabled female

Non-disabled female

Disabled male

Non-disabled male

NeutralSlightly

positive impactSlightly

negative impact

2.00 2.40 2.801.60

43October 2017

5 Job and career

Figure 5.6.2.1 Perceived impact of family/children on the average academic career by gender and disability status


Respondents who disclosed as disabled and respondents who had not disclosed as disabled differed in how they distributed their time across tasks and their experience of life in their department. Specifically, respondents who disclosed as disabled spent more time on average on teaching and less time on research than respondents who had not disclosed as disabled. Additionally, respondents who disclosed as disabled were less positive about their departments’ commitment to equality and its transparency and fairness.

Investigating the intersection between gender and disability status revealed that there were a number of ways in which the opinions and experiences of female academics who disclosed as disabled were unique. For instance, on average, female respondents rated the impact of having a family or children on the average academic career more negatively than male respondents. However, as seen in Figure 5.6.2.1, women who disclosed as disabled rated the impact of having a family or children more negatively than female respondents who had not disclosed as disabled.


Regarding their own career progression, female respondents who disclosed as disabled were significantly more negative about the impact of sex than male respondents who disclosed as disabled (see Figure 5.6.2.2). In contrast, this gender difference was not present among respondents who had not disclosed as disabled. Finally, women who disclosed as disabled were more negative about the impact of having a disability on their own career progression than all other groups (see Figure 5.6.2.2).

3.58

3.78

4.14

4.00

3.64

4.02

3.83

4.02

SexDisabled female

Non-disabled female

Disabled male

Non-disabled male

Disability statusDisabled female

Non-disabled female

Disabled male

Non-disabled male

NeutralSlightly

positive impactSlightly

negative impact

4.00 4.203.803.60


5 Job and career

Figure 5.6.2.2 Perceived areas of impact on respondents’ own career by gender and disability status


45October 2017

Table 6.1.1 Proportions of respondents by type of parental leave and gender

6.1 Maternity, paternity, adoption, shared parental or other parental leave


The proportions of respondents in engineering who had taken the different types of parental leave, including maternity, paternity, additional paternity, adoptive, shared parental or unpaid parental leave, are presented in Table 6.1.1.1.

Type of leave Female Male Total

No. %* %† No. %* %† No. %†

Maternity 98 27.0 11.3 0 0.0 0.0 98 11.3

Paternity 0 0.0 0.0 132 93.6 15.2 132 15.2

Additional paternity 0 0.0 0.0 0 0.0 0.0 0 0.0

Adoption 0 0.0 0.0 0 0.0 0.0 0 0.0

Shared parental 0 0.0 0.0 3 2.1 0.3 3 0.3

Unpaid parental 265 73.0 30.5 6 4.3 0.7 271 31.2

Total 363 100.0 41.8 141 100.0 16.2 504 58.1

* Within each gender, the percentage of respondents who had taken that form of parental leave. † Within the sample of respondents in engineering (n = 868), the percentage of respondents who had taken that form of parental leave.

Respondents were also asked about other forms of caring responsibilities, including whether they care for another adult. The proportions of men (6.4%) and women (8.0%) who reported that they provide care for another adult were not significantly different.

Given that very few respondents reported taking additional paternity, adoption, shared parental or unpaid parental leave, these categories were combined with those respondents who reported taking maternity and paternity leave (which will be collectively referred to as ‘parental leave’ hereafter.

Although 39.4% of the overall sample (or 36.1% of female respondents and 38.2% of male respondents) indicated that they were a parent or legal guardian, only 27.3% of the total sample reported that they had previously taken some form of parental leave. Overall, a significantly larger proportion of women (37.4%) had taken parental leave compared with the proportion of men who had taken such leave (22.8 %).

2.15

3.36

2.80

3.65

5.71

5.64

6.16

5.90

3.75

4.11

4.28

4.27

4.21

4.29

4.34

4.34

Able to relocateFemale has taken parental leave

Female no parental leave

Male has taken parental leave

Male no parental leave

Support from family/partnerFemale has taken parental leave




Involved in department social lifeFemale has taken parental leave




Work success celebratedFemale has taken parental leave




NeutralStrongly

agreeStronglydisagree

4.00 6.002.40 3.20 5.204.402.80 3.60 5.604.80



Figure 6.1.1.1 Factors related to career progression by gender and parental leave status

6.1.1 Differences in the factors related to career progression

Regardless of whether respondents had previously taken parental leave, men were more likely than women to say that they:

= could relocate if needed = could count on support from their family/partner = feel involved in the social life of their department

In contrast, male and female respondents both felt that their work successes were celebrated in their department, even if they had previously taken parental leave (see Figure 6.1.1.1).


2.75

1.80

2.75

2.85

2.00

2.85

GeneralFemale

Male

IT Female

Male

Mechanical Female

Male

NeutralDisagree

1.40 1.80 2.20 2.60 3.00 3.40 3.80

47October 2017


Case study: factors related to career progression across sub-disciplines

In contrast to the results reported for the full engineering subsample, men and women in general engineering who had taken parental leave did not differ in how much they felt they were able to relocate or how supported they felt by their family or partner (see Figure 6.1.1.2 and Figure 6.1.1.3, respectively). Conversely, the ratings provided by male and female respondents in IT, systems sciences and computer software engineering and who had taken parental leave did significantly differ from one another, with women feeling less able to relocate and less supported than men. Notably, while female respondents in mechanical, aero and production engineering felt less able to relocate than male respondents in this sub-discipline, they did not significantly differ in their ratings of support. Unfortunately the number of female respondents in electrical, electronic and computer engineering who had taken parental leave (n = 5) was too small to include in the above comparisons.

Figure 6.1.1.2 Ability to relocate by gender and sub-discipline


6.25

5.54

6.13

6.12

5.29

6.35

GeneralFemale

Male

IT Female

Male

Mechanical Female

Male

Neutral Agree

4.00 4.40 4.80 5.20 5.60 6.00 6.40



6.1.2 Departmental preparation for parental leave

Figure 6.1.1.3 Feeling supported by family or partner by gender and sub-discipline


The following analyses on the options available to prepare respondents for parental leave are limited to the subsample of respondents who reported taking parental leave (rather than those who reported having a child or children).

For each of the 11 items listed, proportionally more women had received information from their department before going on parental leave than men, regardless of whether they had explicitly asked for information (see Table 6.1.2.1). Notably, roughly half of the male respondents who had previously taken parental leave did not receive or request information on six out of the 11 policies.

49October 2017


Table 6.1.2.1 Proportion of respondents who did and did not receive or request information regarding childcare-related policies and options prior to parental leave

Policies and options related to childcare and parental leave

Female Male

Did not receive/request information

Received/requested information

Did not receive/request information

Received/requested information

No. % No. % No. % No. %

Childcare-related policies on payments and benefits

22 10.7 61 29.6 66 32.0 57 27.7

Facilities for continued baby feeding on return to work

57 28.6 25 12.6 108 54.3 9 4.5

Contacts for supporting services (eg human resources, occupational health)

34 16.9 48 23.9 90 44.8 29 14.4

Time off for antenatal appointments 28 13.9 54 26.9 97 48.3 22 10.9

Health and safety assessment 38 19.0 45 22.5 101 50.5 16 8.0

How and when to notify your institution of your intention to return to work

9 4.4 74 36.5 76 37.4 44 21.7

Workplace childcare facilities 27 13.2 56 27.3 82 40.0 40 19.5

Leave cover and handover 43 21.5 39 19.5 89 44.5 29 14.5

Keeping-in-touch days 43 21.5 40 20.0 100 50.0 17 8.5

Options for phased return/workload adjustment

48 24.2 34 17.2 98 49.5 18 9.1

Rest facilities during pregnancy 61 30.7 23 11.6 104 52.3 11 5.5

73.4

60.3

29.1

26.8

24.4

30.3

26.0

17.0

28.4

21.3

26.6

39.7

70.9

73.2

75.6

69.7

74.0

83.0

71.6

46.8 53.2

78.7

20% 40% 60% 80%

KIT days

Flexible hours

Initial part-time build to full-time

Lower initial teaching load

Lower initial administrative load

Lower initial research supervision

Lower initial clinical work load

Parents' network/support group

Additional shared parental leave

Continued baby feeding

Childcare services at workplace

Available Unavailable



Figure 6.1.3.1 Reported availability of options/resources in the department to facilitate return from parental leave

6.1.3 Departmental preparation for return from parental leave

Respondents were also asked to rate how helpful the resources and options available in their department were in facilitating their return to work. Nine of the 11 resources and options listed were not available to more than half of the respondents who had taken some form of parental leave (see Figure 6.1.3.1).

This lack of availability across the different options and resources may be why many of the respondents were not offered and did not ask for information on these prior to their parental leave (noted in the previous section).

Among respondents who had the above options available in their department, both men and women rated flexible working hours as the most helpful option in facilitating their return from parental leave. However, women were more positive than men in their ratings of how helpful this option was in preparing them to return from parental leave (see Table 6.1.3.1), suggesting that being able to adjust working hours outside the standard nine to five format was particularly useful for women with children.

Female respondents also rated the following options as being more helpful than male respondents:

51October 2017


Table 6.1.3.1 Average ratings of helpfulness of options to facilitate return from parental leave by gender

= Keeping-in-touch (KIT) days = lower initial teaching load = lower initial administrative load = baby feeding facilities

Department options and resources Female Male

Keeping-in-touch days* 5.42 4.96

Flexible hours* 6.41 5.84

Initial part-time 5.05 4.48

Initial low teaching load* 5.46 4.40

Initial low admin load* 5.55 4.29

Initial low research supervision 4.30 4.06

Initial low clinical duties 3.65 3.95

Support networks 4.22 4.17

Additional shared parental leave 3.92 4.44

Baby feeding facilities* 5.02 3.95

Childcare facilities 5.47 4.83

* Denotes a significant gender difference in average rating.

Closer look: initiatives to support those with caring responsibilities

Respondents from engineering disciplines expressed discontent that although measures had been put in place for flexible working and ways to support staff with caring responsibilities, they were not always followed-through in reality:

‘I am encouraged to do things but then frequently not facilitated - meetings are held at times which I can’t get to because of childcare.’

Female, IT, systems sciences and computer software engineering

Both male and female respondents commented on the perception that taking parental leave or working part-time would negatively impact their future careers:



6.1.4 Overall, did respondents feel prepared to return from parental leave?

‘Although my department does try hard to support work life balance and family friendly policies, I anticipate that taking parental leave next year for my first child will have some impact on my career development. I don’t particularly resent this impact (especially given that this is something that women have had to deal with forever).’

Male, IT, systems sciences and computer software engineering

‘Taking time out to care for dependents often means that you are left out of decision making and other activities. My perception is that I have been overlooked a number of times and I feel that if I had been full time or not on maternity leave that this may have not happened as much.’

Female, general engineering

Despite female respondents’ positive ratings of the options and resources available, they were more likely than male respondents to report feeling less prepared to return to work (on a scale of 1 to 7, see Figure 6.1.4.1). This result can appear counterintuitive as female respondents tended to have more information before going on parental leave and rated departmental resources and options as more useful than male respondents. However, it is worth noting that the average maternity leave is considerably longer than the average paternity leave. Female respondents may therefore have had greater appreciation of the resources and options available in their department than male respondents because they felt less prepared to return to work after a longer period away.

1.0

4.1

3.1

8.8

0.0

14.7

26.9

9.6

14.1

30.5

34.7

27.8

20.1

4.5

10% 20% 30% 40% 50%Extremely underpreparedFemale

Male

UnderpreparedFemale

Male

Somewhat underpreparedFemale

Male

NeutralFemale

Male

Somewhat preparedFemale

Male

PreparedFemale

Male

Extremely preparedFemale

Male

53October 2017


Figure 6.1.4.1 Ratings of feeling prepared to return from parental leave by gender

3.30

3.94

5.6

4.08

Has taken parental leaveFemale

Male

Has not taken parental leaveFemale

Male

Neutral EasierMore di�cult

4.003.603.20 5.20 5.604.40 4.80



Figure 6.2.1 Difficulty returning to work by gender and parental leave status

6.2 Career breaks The ASSET 2016 survey included a section concerning whether respondents had previously taken a career break, defined as a period of leave following a resignation or unenforced departure at the end of a contract that does not include periods of maternity, paternity, adoption, shared parental, other parental or sick leave.

Overall, 7.1% of respondents in engineering reported having taken a career break; however, proportionally more women (10.5%) had taken career breaks than men (5.6%).

The majority of respondents’ career breaks lasted less than 12 months (62.3%), but there was a considerable number of respondents who reported breaks of one to two years (18.0%), three to five years (9.8%) or more than five years (9.8%). Notably, despite women being more likely to have taken a career break, the duration of men and women’s career breaks were similar.

However, an interesting contrast was revealed when respondents who had taken a career break were considered separately from respondents who had taken both a career break and some form of parental leave: women who had taken both parental leave and a career break found it more difficult to return to work than men who had taken both forms of leave (see Figure 6.2.1) This gender difference was not present between men and women who had taken a career break but not previously taken parental leave.


33.3

14.1

42.9

17.4

33.3

11.3

Initial low research supervisionBME female

White female

Support networksBME female

White female

Shared parental leaveBME female

White female

10% 20% 30% 40% 50%

55October 2017


Figure 6.3.1.1 Female respondents’ access to options/resources to facilitate return from parental leave by ethnicity

6.3 Beyond the gender gap: how do caring responsibilities and career breaks differ for STEMM academics belonging to more than one underrepresented group?

In contrast, male and female respondents rated the impact of taking a career break on career progression in a similar manner, regardless of whether they had previously taken parental leave and the duration of their career break.


Although similar proportions of white female and BME female respondents had taken parental leave (37.2% and 38.2%, respectively), the proportions of BME female respondents with access to initial low research supervision, support networks and shared parental leave were significantly larger than the proportions of white female respondents with access to these options (see Figure 6.3.1.1). With regards to the helpfulness of options to facilitate a return from parental leave, it was not possible to quantitatively explore whether gender differences varied by ethnicity as too few BME respondents in engineering who had previously taken parental leave (n = 35) had used these options.

Finally, the gender difference between the proportions of men and women who had taken a career break was present among both white (6.0% and 10.4%, respectively) and BME respondents (4.2% and 10.9%, respectively).




The proportion of respondents who had not disclosed as disabled (28.8%) who had taken parental leave was similar to the proportion of respondents who disclosed as disabled who had taken parental leave (21.0%). However, the gap between the proportions of men and women taking parental leave was only significant among respondents who had not disclosed as disabled (24.1% and 39.8%, respectively). In contrast the gap between the proportions of men and women who disclosed as disabled (16.7% and 28.3%, respectively) was not statistically significant. Beyond those reported for the engineering sample so far, there were no additional differences in how men and women who had and had not disclosed as disabled rated the availability and helpfulness of the options and resources intended to facilitate return from parental leave.

The proportion of respondents who disclosed as disabled (8.1%) who had taken a career break was not significantly different from the proportion of respondents who had not disclosed as disabled (6.9%). Again, the gender difference in the proportions of men and women who had taken a career break was limited to respondents who had not disclosed as disabled (11.3% and 5.1%, respectively), compared with considerably smaller gap between men and women who disclosed as disabled (8.5% and 7.4%, respectively).

57October 2017

7.1 Training opportunities

7 Training and leadership

The ASSET 2016 survey also sought to examine whether the nature of respondents’ previous training opportunities, as well as access to such training opportunities, differed by gender.

Respondents were asked whether or not they had received formal training in ten areas relevant for career development:

= administrative tasks related to management = postgraduate supervision = leadership = professional development = grant application skills = teaching = project/planning/financial management skills = equality and diversity training (student issues) = equality and diversity training (staff issues) = unconscious bias training

Out of these ten areas, proportionally more men than women reported having obtained training in administrative tasks related to management and professional development. In all other areas, the proportions of male and female respondents reporting that they had received this form of training were similar (see Figure 7.1.1).

28.8

38.7

59.5

58.9

36.4

34.2

43.2

51.3

37.1

42.3

62.1

56.8

25.0

29.9

51.1

52.3

57.2

58.0

39.8

37.7

10% 20% 30% 40% 50% 70%60%Admin related to managementFemale

Male

Postgraduate supervisionFemale

Male

LeadershipFemale

Male

Professional developmentFemale

Male

Grant application skillsFemale

Male

TeachingFemale

Male

Project/�nancial managementFemale

Male

Equality and diversity (students)Female

Male

Equality and diversity (sta�)Female

Male

Unconscious biasFemale

Male



Figure 7.1.1 Training opportunities by gender

56.4

45.2

18.4

12.0

4.8

1.8

12.9

11.6

11.6

9.8

11.2

4.9

7.7

5.2

10% 20% 30% 40% 50% 60%TimeFemale

Male

CostsFemale

Male

IneligibleFemale

Male

Not o�ered by institutionFemale

Male

Not relevant to positionFemale

Male

Caring responsibiltiesFemale

Male

Obstructive line managerFemale

Male

59October 2017


Figure 7.2.1 Training barriers by gender

7.2 Training barriers The ASSET 2016 survey also asked respondents to indicate whether they had experienced any of 18 possible barriers to training in the last 12 months. Compared with men, larger proportions of women reported that the following barriers had blocked their access to training that they had needed or wanted in the last 12 months: time, costs, ineligibility and caring responsibilities (see Figure 7.2.1).



Table 7.2.1 Training barriers related to protected characteristics by gender

For a number of the protected characteristics, the number of respondents who reported that a given characteristic had blocked their access to training was too small to allow for gender contrasts (see Table 7.2.1). The only exception to this was age, which was similarly reported by male and female respondents.

Training barrier Female Male

No. %† No. %†

Accent or language skills 6 2.4 6 1.1

Age 17 6.8 23 4.2

Disability 4 1.6 5 0.9

Dress or appearance 7 2.8 1 0.2

Ethnicity or race 4 1.6 6 1.1

Gender identity 5 2.0 0 0.0

Marital or civil partnership status 3 1.2 1 0.2

Religion or belief 0 0.0 2 0.4

Sex 3 1.2 0 0.0

Sexual orientation 0 0.0 0 0.0

† Within each gender, the proportion of respondents who experienced that training barrier

Case study: training experiences across individual sub-disciplines

To explore whether male and female respondents’ training experiences differed across sub-disciplines, the total number of opportunities and barriers reported by each respondent were summed into two separate scores, one representing their total training opportunities (range 0 to 10) and another representing their total training barriers (range 0 to 18). Averages of these summed scores were used to compare men and women’s training experiences within the individual sub-disciplines as well as across sub-disciplines.

In contrast to all other sub-disciplines, there was a significant difference in the total training opportunities reported by men

3.00

3.65

4.81

3.90

3.80

3.74

3.84

3.99

Electrical Female

Male

GeneralFemale

Male

IT Female

Male

Mechanical Female

Male

Average number of training opportunities

4.0 5.03.02.01.0

61October 2017


and women in general engineering. Specifically, women in general engineering had received more training than men in general engineering (see Figure 7.2.2). A similar incongruence between general engineering and the other sub-disciplines was also apparent in respondents’ total training barriers; female respondents reported more barriers than male respondents in all engineering sub-disciplines except general engineering (see Figure 7.2.3).

Figure 7.2.2 Training opportunities by gender and sub-discipline


1.88

1.13

1.14

0.99

1.58

0.93

1.49

0.98

Electrical Female

Male

GeneralFemale

Male

IT Female

Male

Mechanical Female

Male

Average total of training barriers

4.0 5.03.02.01.0



Figure 7.2.3 Training barriers by gender and sub-discipline


Taking a closer look at the individual training opportunities revealed that respondents in general engineering were more likely to have obtained training in administrative tasks related to management and leadership. However, there were no significant differences in the types of training barriers reported across the individual sub-disciplines.

Closer look: time, caring responsibilities and unsupportive line management

Respondents commented on their inability to undertake training due to a lack of time:

‘A lack of time is always a problems in my position, I have to prioritise my time, sometimes training does not fit into this. I would like to train in leadership, management and teaching even though these aspects are not present in my current role.’

Female, mechanical, aero and production engineering

63October 2017


7.3 Beyond the gender gap: how do differences in training opportunities and barriers differ across other characteristics?

This problem was further compounded by caring responsibilities and unsupportive line management, particularly in regards to training related to personal development:

‘Training is viewed very negatively in my group. My line manager makes it quite clear! At my position, training is seen as unnecessary and time wasting. I should have all the skills required to do the job. Training is viewed as skills required to do the job and not for personal developmental purposes and how it helps the job rather than how it is going to help develop your staff. My caring duties also meant that I work reduced hours which adds to the emphasis on time ‘wasted sitting in a room somewhere, when you should be doing work’.’

Female, general engineering

‘There is a presumption that academics will self-train - particularly those of us in senior roles. The University does rather take advantage of this, particularly whenever there is a change to a system or process. The biggest issue is time though - I just don’t have any to spare during core hours.’



Investigating the intersection between gender and ethnicity revealed an imbalance in the training opportunities and barriers experienced by BME and white men in particular. For instance, compared with white men, significantly larger proportions of BME men had obtained training in:

= postgraduate supervision = grant application skills = project planning/financial management skills

20.8

30.8

23.3

42.4

66.0

57.8

68.1

56.6

41.5

35.7

51.7

40.0

25.9

24.6

40.5

27.3

39.6

40.0

25.0

40.8

10% 20% 30% 40% 50% 60% 70%Admin related to managementBME female

White female

BME male

White male

Postgraduate supervisionBME female

White female

BME male

White male

Grant application skillsBME female

White female

BME male

White male

Project/�nancial managementBME female

White female

BME male

White male

Unconscious biasBME female

White female

BME male

White male



Figure 7.3.1.1 Training opportunities by gender and ethnicity

Conversely, the proportions of white male respondents who had obtained training in administrative tasks related to management and unconscious bias were significantly larger than the proportions of BME male respondents with experience in these training areas (see Figure 7.3.1.1). In contrast, the gaps between BME and white women’s training experiences in these areas were not significant.

11.3

3.1

3.5

1.5

22.6

10.2

12.8

11.4

10% 20% 30% 40% 50% 60% 70%IneligibleDisabled female

Non-disabled female

Disabled male

Non-disabled male

Not o�eredDisabled female

Non-disabled female

Disabled male

Non-disabled male

65October 2017


Figure 7.3.2.1 Training barriers by gender and disability status


In contrast to the intersection between gender and ethnicity, taking a look at how gender differences varied according to respondents’ disability status revealed significant differences in the training opportunities and barriers experienced by women who had and had not disclosed as disabled. For instance, the proportion of female respondents who disclosed as disabled (24.1%) who had obtained leadership training was significantly smaller than the proportion of female respondents who had not disclosed as disabled (39.5%).

Regarding respondents’ experience of training barriers, the proportions of women who disclosed as disabled who had been unable to access training that they needed or wanted because they were ineligible or because it was not offered at their institution were significantly larger than all other groups (see Figure 7.3.2.1).

25.0

62.5

65.9

62.0

53.6

56.5

51.1

62.5

Electrical Female

Male

GeneralFemale

Male

IT Female

Male

Mechanical Female

Male

40% 50% 60% 70%30%20%10%


8.1 Explicit encouragement or invitation for promotion


The final section of the ASSET 2016 survey asked respondents to describe how their current department encourages them to develop their careers and their intentions for the future of their careers.

In contrast to the results surrounding recruitment methods in section 4, the proportion of male respondents (60.0%) who reported that they were encouraged or invited to apply for a promotion or post at a higher grade did not significantly differ from the proportion of female respondents (55.1%) who reported this experience.

Case study: gender imbalance in explicit encouragement across sub-disciplines

In general, the proportions of male and female respondents who had previously been encouraged or invited to apply for promotion were similar across the four sub-disciplines. However, among respondents in electrical, electronic and computer engineering, proportionally more men than women were encouraged to apply for promotion (see Figure 8.1.1). This gender gap was not present among respondents in general engineering, IT, systems sciences and computer software engineering or mechanical, aero and production engineering.

Figure 8.1.1 Proportion of respondents encouraged or invited to apply for promotion by gender and sub-discipline

67October 2017


8.2 Department’s encouragement of career development

Closer look: applying for promotion requires more than just a helping hand

Respondents noted that men seemed more likely to possess characteristics associated with promotion, such as having the confidence to apply, as well as the ability to relocate for a new position:

‘Male academics are more mobile which helps with promotion and also they push more for it.’


Others explicitly commented on experiences of racial discrimination in the promotions process and the benefits of having a good relationship with senior management:

‘There is discrimination on the basis of colour. Promotion is easier in my experience if one is white and in favour of senior management.’

Male, mineral, metallurgy and materials engineering

Each of the analyses exploring gender differences in departmental encouragement for career development took into account whether respondents had previously been invited to apply for promotion.

In general, male respondents in engineering felt more encouraged by their department to undertake activities that contributed to their career development than female respondents (see Figure 8.2.1). Compared with their female colleagues, male respondents were also more likely to enjoy:

= having a formally assigned mentor = opportunities to serve on important departmental committees = feeling that their department values their research and external

professional activities

4.68

5.01

2.98

3.21

4.56

5.05

4.65

4.97

5.32

5.13

4.44

4.82

5.08

5.17

5.23

5.38

4.00

4.05

Encouraged to develop careerFemale

Male

Formally assigned mentorFemale

Male

Served on important committeesFemale

Male

Research is valuedFemale

Male

Su�cient adminstrative experienceFemale

Male

External activities are valuedFemale

Male

Accessible senior sta�Female

Male

Supportive line managerFemale

Male

Useful and valued appraisalFemale

Male

NeutralSomewhat

agreeSomewhat

disagree

4.003.202.80 5.20 5.604.403.60 4.80



Figure 8.2.1 Ratings of departmental support for career development by gender


4.18

3.18

4.13

2.69

2.38

3.34

3.09

3.53

Electrical Female

Male

GeneralFemale

Male

IT Female

Male

Mechanical Female

Male

3.603.202.802.40

Neutral4.00 4.40

Slightly negative

69October 2017


Conversely, female respondents in engineering were more likely to feel that they had sufficient administrative experience compared with male respondents. Notably, the differences between male and female respondents’ ratings of having a supportive line manager and a useful appraisal were not significant.

Case study: formal mentors and valuing of external activities across sub-disciplines

On average, in the full engineering subsample, male respondents were more likely than female respondents to report having a formally assigned mentor. However, the presence and direction of this gender difference depends on which sub-discipline is being examined. As seen in Figure 8.2.2, male respondents in IT, systems sciences and computer software engineering were more likely to have a formally assigned mentor than female respondents in this sub-discipline. The situation was reversed for respondents in general engineering, with female respondents being more likely than male respondents to have a formally assigned mentor. Neither of these differences were present among male and female respondents in electrical, electronic and computer engineering or mechanical, aero and production engineering.

Figure 8.2.2 Assignment of formal mentor by gender and sub-discipline


5.00

4.90

5.45

4.92

4.15

4.73

4.43

5.11

Electrical Female

Male

GeneralFemale

Male

IT Female

Male

Mechanical Female

Male

Neutral4.00 4.40 4.80 5.20 5.60

Slightly positive



The same pattern of results was present among respondents’ ratings of how much their department values their external professional activities (see Figure 8.2.3).

Figure 8.2.3 Value of external professional activities by gender and sub-discipline


Closer look: informal masculine networks

Respondents noted the perception that a ‘boys’ club’, or informal masculine network, had sway over decisions made within engineering departments and facilitated the ease by which certain staff members progressed in their career:

‘In terms of formal processes, I think we now have quite an equitable situation. I think the big issue here is the informal, or unconscious bias of networking to form alliances and preferences. I very much feel that there is a boys’ club in operation here and the girls aren’t allowed to play, at times.’


4.56

4.84

4.27

3.93

3.70

3.24

3.75

3.07

Desire to obtain management postFemale invited to apply

Female not invited

Male invited to apply

Male not invited

Expect to obtain management postFemale invited to apply

Female not invited

Male invited to apply

Male not invited

Neutral AgreeDisagree

4.00 4.40 4.803.603.20

71October 2017


Figure 8.3.1 Ratings of desire to obtain senior management post versus expectations by gender

8.3 Plans for future career

Although gender equality was discussed within engineering departments as an issue to address, this did not always translate into proactive practices:

‘My experience is that senior staff in leadership & management roles tend to talk about gender equality, and I am convinced that most care about it, but they do very little about it, especially proactively. Women are excluded and their views downplayed in very subtle ways. I feel that I am not in the right cliques which means that I am less likely to be appointed to formal leadership positions than male colleagues should I apply.’


Women reported a stronger desire to obtain a senior management post in their institutions than men did (see Figure 8.3.1), even when other factors were taken into account, including respondent’s age, current post and previous invitation to apply for a promotion.


In contrast to the gender difference in respondents’ desires, male and female respondents were similar in how much they expected to obtain a senior management post in their institutions (see Figure 8.3.1). Instead, whether respondents expected to obtain a senior post



8.4 Beyond the gender gap: do individuals belonging to more than one underrepresented group experience a unique path through the promotion and development process?

depended on whether they had or had not been explicitly invited or encouraged to apply for promotion in the past.

The final item in this section asked respondents whether they wanted to continue a career in STEMM (within or outside higher education) or continue in a field outside STEMM. Similar proportions of men and women endorsed each of the options listed. Specifically, 5.4% of male respondents and 2.7% of female respondents indicated that they did not want to continue a career in STEMM while another 8.2% of men and 6.1% of women said that they would like to continue their career in STEMM but outside of higher education. Still, the overwhelming majority of both male and female respondents reported that they wanted to remain in STEMM and within higher education (86.4% and 91.2%, respectively).


There were no significant differences between the proportions of BME female respondents (45.3%), BME male respondents (56.9%), white female respondents (57.6%) and white male respondents (60.8%) who had been directly encouraged or invited to apply for promotion. However, it is worth noting that while not statistically significant, the proportion of BME women explicitly encouraged to apply for promotion is just over 15 per cent smaller than the proportion of white men reporting this experience.

Nonetheless, respondents displayed significant differences in their desires and expectations for their future career. For instance, female respondents were more likely to say that they would like a senior management post than male respondents, regardless of their ethnicity. Similarly, BME respondents were more likely to report that they expected to obtain a post in senior management than white respondents (see Figure 8.4.1.1), regardless of their gender.

5.27

4.53

4.57

4.02

4.10

3.34

4.15

3.25

Desire to obtain management postBME female

White female

BME male

White male

Expect to obtain management postBME female

White female

BME male

White male

Neutral AgreeDisagree

4.00 4.40 4.80 5.203.603.20

73October 2017



Figure 8.4.1.1 Ratings of desire to obtain senior management post versus expectations by gender and ethnicity


Finally, the proportion of white male respondents (6.3%) who said that they did not want to continue their career in STEMM was significantly larger than the proportions of white female respondents (1.9%) and BME male respondents (1.7%) reporting this intention, but not BME female respondents (5.7%).

Again, there were no significant differences in the proportions of respondents who had previously been encouraged or invited to apply for promotion: 48.1% of women who disclosed as disabled, 55.3% of men who disclosed as disabled, 56.9% of women who had not disclosed as disabled and 60.9% of men who had not disclosed as disabled. However, it is worth noting that the gap between the proportion of women who disclosed as disabled and the proportion of men who had not disclosed as disabled was more than double the gaps between (i) men who had and had not disclosed as disabled, and (ii) men and women who had not disclosed as disabled.

As seen in Figure 8.4.2.1, regardless of gender, respondents who disclosed as disabled were less likely than respondents who had not disclosed as disabled to enjoy:

= being encouraged to develop their career = feeling that their department values their research and external

professional activities

4.55

4.99

2.89

3.19

4.78

4.93

4.39

5.00

5.52

5.12

4.33

4.79

3.17

2.78

4.99

5.42

3.65

4.09

Encouraged to develop careerDisabled

Non-disabled

Formally assigned mentorDisabled

Non-disabled

Served on important committeesDisabled

Non-disabled

Research is valuedDisabled

Non-disabled

Su�cient adminstrative experienceDisabled

Non-disabled

External activities are valuedDisabled

Non-disabled

Accessible senior sta�Disabled

Non-disabled

Supportive line managerDisabled

Non-disabled

Useful and valued appraisalDisabled

Non-disabled

NeutralSomewhat

agreeSomewhat

disagree

4.003.202.80 5.20 5.604.403.60 4.80



Figure 8.4.2.1 Ratings of departmental support for career development by disability status

= access to senior staff = having a supportive line manager = feeling that their appraisal was useful and valuable


75October 2017


Finally, the proportion of female respondents who disclosed as disabled (7.4%) who indicated that they did not want to continue their career in STEMM was significantly larger than the proportion of female respondents who had not disclosed as disabled (1.4%) reporting this intention. In contrast, this difference was present between male respondents who disclosed as disabled (6.6%) and male respondents who had not disclosed as disabled (5.2%).


9.1 Key gender differences in engineering compared with STEMM sciences in general

9 Conclusion

The current report explored gender differences in the experiences and perceptions of male and female academics in engineering. This section begins with a summary of these experiences, as well as a discussion of the instances where the experiences of respondents in engineering diverged from those in the full ASSET 2016 sample. Next, an overview of the intersections between gender and ethnicity and gender and disability status are presented. Finally, the section closes with a selection of recommendations that are particularly relevant to the unique experiences of academics in engineering.

For the most part, the multiple disadvantages identified by female STEMM academics in the full ASSET 2016 report (ECU 2017) were consistent within the sample of respondents working in the different fields of engineering.

Compared with men, women in engineering:

= were underrepresented in senior posts and overrepresented in early career positions

= tended to be on fixed-term and part-time contracts

= were less likely to have obtained their current post through a formal promotion

= rated their department as being less committed to gender equality

= felt that men had the advantage in the allocation of tasks and resources related to professional development and markers of esteem

= considered it easier for a man to obtain a senior post in their department

= were less positive in their opinions regarding life in their department (eg whether it is a supportive environment, values teaching and is transparent and fair in the allocation of resources)

= rated the impact of having a family/children, protected characteristics and administrative duties on the average academic career more negatively

= felt that their sex, sexual orientation, marital or civil partnership status, gender identity, age and caring responsibilities had negatively impacted their own career progression

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9 Conclusion

= felt like they were less able to relocate, less involved in the social life of their department and less able to count on support from their partner or family, regardless of whether they had previously taken parental leave or not

= were more likely to have taken parental leave and less likely to feel prepared to return from parental leave

= reported that time constraints, financial costs, ineligibility and caring responsibilities had blocked their access to training in the last 12 months

= were less likely to feel that their department encourages them to undertake activities that contribute to their career development

= were less likely to have a formally assigned mentor, serve on important departmental committees and feel that their department values their research and external professional activities

However, the results reported for the engineering subsample differed from those reported for the full sample in three key areas. The first area pertains to how the academics in the engineering subsample distributed their time across their research and teaching duties. In contrast to the results reported for the full sample, male and female respondents in engineering spent similar portions of their time on research, teaching and public engagement. Given the noted importance of research-related activities (eg having substantive research output, successfully applying for grants and being involved in well-regarded projects) for academic career progression (ie section 5.4.1), this more balanced distribution of time among men and women in engineering could indirectly promote balance in other areas such as improving the representation of female academics in more senior posts or on full-time contracts.

The second noteworthy contrast concerns respondents’ training opportunities: there were considerably fewer gender differences in the training opportunities reported by men and women in engineering compared with those reported in the full sample. Specifically, there was only one training area out of the ten listed that did not have a significant gap between men and women in the full sample and this was teaching. In all other areas, proportionally more men had obtained training compared with women. In contrast, among respondents in engineering, the only training areas that proportionally more men than women reported having


9 Conclusion

9.2 Summary of intersectional results

experience in was for administrative tasks related to management and professional development. In all other areas, the proportions of male and female respondents reporting that they had received this form of training were similar. A comparable pattern was present for the training barriers reported by men and women in engineering compared with the full sample. For instance, out of the six contextual barriers listed in the ASSET 2016 survey, only three (time, money and eligibility) were disproportionately reported by women in engineering, versus all six in the full sample. Notably, although the proportions of men (5.2%) and women (7.7%) who reported that an unsupportive or obstructive line manager had blocked their access to training in the last 12 months were not significantly different among respondents in engineering, these proportions are generally larger than those reported by men (4.0%) and women (7.0%) in the full STEMM sample.

The final area of contrast between the results for the full sample and the subsample of respondents in engineering pertain to their experiences regarding promotion and development. Specifically, the proportion of male respondents (60.0%) who reported that they were encouraged or invited to apply for a promotion or post at a higher grade did not significantly differ from the proportion of female respondents (55.1%) who reported this experience. In addition, men and women in engineering reported similar access to senior staff and a supportive line manager on average, as well as both feeling that their appraisal was useful and valuable. The lack of a gender-related difference in the explicit and more subtle departmental support for male and female respondents’ career development may be why there were no significant differences in the proportions of men and women reporting that they would like to continue their careers outside of STEMM (5.4% and 2.7%, respectively) or in STEMM but outside of higher education (8.2% and 6.1%, respectively).

9.2.1 Gender and ethnicity

Investigating the intersection between gender and ethnicity among respondents in engineering revealed a pattern that differed from the compounded disadvantage identified for BME women in the full sample in three main ways. First, the disadvantages for BME women in the engineering subsample were not present across all six aspects of working life covered in the ASSET 2016 survey. For example, while

79October 2017

9 Conclusion

BME men and BME women reported different recruitment methods for obtaining their current post (with BME women being more likely to have applied for an advertised post), there were no significant differences between BME men and BME women in their views of life in their department, training opportunities and barriers or expectations for obtaining a post in senior management.

Second, the opinions and experiences of BME women and white women were often similar. For instance, both perceived an advantage for men in the allocation of tasks and resources related to professional development and markers of esteem. In some cases, BME women in the engineering subsample could even be seen as having an advantage: compared with white women who had taken parental leave, proportionally more BME women had taken parental leave had more access to initial low research supervision, support networks and shared parental leave.

Third, there were a number of differences in the experiences of BME men and white men. BME men rated their departments as more demanding of their time and effort than white men and were more positive about the impact of teaching experience on the average academic career than all other groups. Additionally, compared with white men, proportionally more BME men had obtained training in postgraduate supervision, grant application skills and project planning/financial management. Conversely, the proportions of white male respondents who had obtained training in administrative tasks related to management and unconscious bias were significantly larger than the proportion of BME male respondents.

While the current report shows that there are some marked disadvantages for BME men and BME women working in engineering in higher education, how these disadvantages manifest across the individual aspects of working life and impact career progression remains unclear. It is worth noting that there were multiple instances where the gender difference between BME female and BME male respondents was not statistically significant but at least comparable to the significant gap between white male and white female respondents. For instance, regarding respondents’ intentions for their future career, the statistically non-significant gap between the proportion of BME men (1.7%) and BME women (5.7%) reporting that they do not want to continue their career in STEMM was not much smaller than the statistically significant gap between the proportion of white men (6.3%) and white women (1.9%) with this intention.


9 Conclusion


Taken together, the above results suggest that the experiences of both BME men and women in engineering vary compared with those reported for the full sample of STEMM academics.

In general, the pattern of results in the sample of respondents in engineering was consistent with that identified in the full ASSET 2016 sample: academics who had disclosed as disabled experienced more difficulties and disadvantages than their colleagues who had not disclosed as disabled. Within the engineering subsample, compared with respondents who had not disclosed as disabled, respondents who disclosed as disabled:

= were less likely to describe their department as a supportive environment or transparent and fair

= spent more time on average on teaching and less time on research

= were more negative about the impact of having a family or children and the impact of protected characteristics on the average academic career

= felt less involved in the social life of their department

= experienced more barriers to training including those associated with cost, eligibility, age, disability status and having an obstructive line manager

= felt less encouraged by their department to undertake activities that contribute to career development

= did not feel that their department placed particular value on their research or external professional activities

= had reduced access to senior departmental staff

= were more likely to have an unsupportive line manager

= were less positive about the utility and value of their appraisals

Notably, there were a handful of instances where disadvantages related to disability were limited to women. Compared with female respondents who had not disclosed as disabled, female respondents who disclosed as disabled:

= reported a stronger advantage for men in the allocation of tasks and resources related to professional development and markers of esteem

81October 2017

9 Conclusion

9.3 Recommendations

= were the most negative in their ratings of the impact of disability status on their own career progression

= had less leadership training

= were more likely to say that they had been unable to access training that they needed or wanted because they were ineligible or because it was not offered at their institution

= were the most likely to say that they did not want to continue their career in STEMM

These unique experiences of women who disclosed as disabled highlight how identifying with multiple underrepresented groups may compound or exacerbate the experience of gender inequality.

The following recommendations are driven by respondents’ reported experiences of gender equality and reinforced by their description of these experiences in the open-ended questions of the ASSET 2016 survey. While these recommendations are phrased in terms of alleviating discrepancies between men and women’s experiences in general, many could be adapted or used as a starting point for addressing the imbalances specific to the physical sciences or other imbalances, such as those related to the intersections between gender and ethnicity and gender and disability status.

= Develop mentoring or sponsorship programmes to increase the visibility of staff in early career posts (eg by increasing exposure to senior staff, clarifying promotion processes and providing opportunities to serve on departmental committees) (ECU 2012).

= Ensure academic contracts accommodate flexible working policies.

= Establish a set budget (time and money) for training programmes.

= Establish transparent workload allocation models that promote balance in the distribution of research, teaching and administrative duties among staff.

= Promote the development of supportive and career progressing networks (examples of good practice available in an ECU 2017 report for HEFCE).

= Ensure all staff have opportunities to engage with senior departmental staff.


9 Conclusion

= Explore options to offer analogous leave to staff caring for another adult to that offered to staff caring for children.

= Provide staff returning from parental or carer leave with additional options such as a low initial teaching or administrative workloads.

= Expand promotion criteria to include performance in other professional skills such as teaching and administrative experience.

= Reduce variability in the amount and type of support provided by line managers by ensuring that (i) line management duties are evenly distributed, (ii) line managers have the opportunity to develop their management skills (eg through management training programmes or unconscious bias training), and (iii) motivating line managers to prioritise these duties by increasing their accountability and adding incentives for being a good line manager.

83October 2017

10 References

ECU (2012) Mentoring: progressing women’s careers in higher education. Equality Challenge Unit, London. www.ecu.ac.uk/publications/mentoring-progressing-womens-careers-in-higher-education

ECU (2015) Equality in higher education: statistical report 2015: part 1: staff. Equality Challenge Unit, London. www.ecu.ac.uk/publications/equality-higher-education-statistical-report-2015

ECU (2016) Equality in higher education: staff statistical report 2016. Equality Challenge Unit, London. www.ecu.ac.uk/publications/equality-in-higher-education-statistical-report-2016

ECU (2017) ASSET 2016: experiences of gender equality in STEMM academia and their intersections with ethnicity, sexual orientation, disability and age. Equality Challenge Unit, London. www.ecu.ac.uk/publications/asset-2016

HEFCE commissioned report by ECU (2017) Findings: Sector-leading and innovative practice in advancing equality and diversity. Higher Education Funding Council for England, Bristol. www.hefce.ac.uk/pubs/rereports/year/2017/edpractice

http://www.ecu.ac.uk/publications/mentoring-progressing-womens-careers-in-higher-education

http://www.ecu.ac.uk/publications/mentoring-progressing-womens-careers-in-higher-education

http://www.ecu.ac.uk/publications/equality-higher-education-statistical-report-2015

http://www.ecu.ac.uk/publications/equality-higher-education-statistical-report-2015

http://www.ecu.ac.uk/publications/equality-in-higher-education-statistical-report-2016

http://www.ecu.ac.uk/publications/equality-in-higher-education-statistical-report-2016

http://www.ecu.ac.uk/publications/asset-2016

http://www.ecu.ac.uk/publications/asset-2016

http://www.hefce.ac.uk/pubs/rereports/year/2017/edpractice

http://www.hefce.ac.uk/pubs/rereports/year/2017/edpractice


Sub-discipline ASSET 2016 HESA 2014/15 staff recordsFemale Male Female Male

No. % % No. % % No. % % No. % %

Chemical engineering 21 7.9 40.4 31 5.1 59.6 280 6.0 26.7 768 4.0 73.3

Civil engineering 26 9.8 31.3 57 9.5 68.7 423 9.1 21.8 1516 8.0 78.2

Electrical, electronic and computer engineering

20 7.5 15.6 108 17.9 84.4 618 13.3 14.3 3711 19.5 85.7

General engineering 46 17.3 33.3 92 15.3 66.7 773 16.7 20.8 2948 15.5 79.2

IT, systems sciences and computer software engineering

98 36.8 33.6 194 32.2 66.4 1478 31.9 22.2 5178 27.2 77.8

Mechanical, aero and production engineering

45 16.9 31.5 98 16.3 68.5 753 16.2 15.8 3999 21.0 84.2

Mineral, metallurgy and materials engineering

10 3.8 31.3 22 3.7 68.8 314 6.8 26.1 889 4.7 73.9

Total 266 100 30.6 602 100 69.4 4639 100 19.6 19009 100 80.4

1.1 Gender

Appendix: sample characteristics

Table 1.1.1 ASSET 2016 engineering subsample and HESA 2014/15 staff records by sub-discipline and gender

Source HESA 2014/15 staff records (ECU 2016).

85October 2017


Table 1.2.2 ASSET 2016 engineering subsample and HESA 2014/15 staff records by ethnic group

Table 1.2.1 ASSET 2016 engineering subsample and HESA 2014/15 staff records by sub-discipline and ethnicity

1.2 Ethnicity

ASSET 2016 HESA 2014/15 staff records

No. % No. %

White 695 81.6 13639 86.9

BME total 157 18.4 2055 13.1

Black 10 1.2 128 0.8

Asian 54 6.3 763 4.9

Chinese 55 6.5 651 4.1

Mixed 18 2.1 257 1.6

Other 20 2.3 256 1.6

Total 852 100.0 15694 100.0


Sub-discipline ASSET 2016 HESA 2014/15 staff recordsBME White BME White

No. % % No. % % No. % % No. % %




41 23.6 32.0 87 12.5 68.0 1258 22.2 31.8 2703 16.8 68.2



42 24.1 14.4 250 36.0 85.6 1323 23.4 21.4 4859 30.2 78.6


31 17.8 21.7 112 16.1 78.3 1187 21.0 27.0 3207 19.9 73.0


3 1.7 9.4 29 4.2 90.6 277 4.9 25.9 792 4.9 74.1

Total 174 100 20.0 694 100 80.0 5660 100 26.0 16112 100 74.0




Table 1.3.2 ASSET 2016 engineering subsample and HESA 2014/15 staff records by impairment type

Table 1.3.1 ASSET 2016 engineering subsample and HESA 2014/15 staff records by sub-discipline and disability status

1.3 Disability

Sub-discipline ASSET 2016 HESA 2014/15 staff recordsHad not disclosed as disabled

Disclosed as disabled

Had not disclosed as disabled

Disclosed as disabled

No. % % No. % % No. % % No. % %




108 15.0 85.0 19 12.8 15.0 4214 18.5 97.3 115 13.4 2.7



230 31.9 78.5 63 42.6 21.5 6362 27.9 95.6 294 34.3 4.4


127 17.6 88.2 17 11.5 11.8 4635 20.3 97.5 117 13.6 2.5


25 3.5 78.1 7 4.7 21.9 1178 5.2 97.8 26 3.0 2.2

Total 720 100 82.9 148 100 17.1 22790 100 96.4 858 100 3.6

ASSET 2016 HESA 2014/15 staff records

No. % No. %

Had not disclosed as disabled 682 82.7 22791 96.8

Disclosed as disabled 143 17.3 765 3.2

Blind or serious visual impairment 3 0.4 21 0.1

Communication or social impairment 9 1.1 17 0.1

Deaf or serious hearing impairment 7 0.8 39 0.2

General learning difficulty 0 0.0 7 0.0

Long-standing illness or health condition

48 5.8 159 0.7

Mental health condition 45 5.5 45 0.2

Physical impairment or mobility issues 7 0.8 77 0.3

Specific learning difficulty 31 3.8 136 0.6

Other 29 3.5 264 1.1

Total 825 100.0 23556 100.0



87October 2017

Index

Table 2.3.1 Individual sub-disciplines by gender 11

Table 2.5.4.1 Sample sizes by gender and protected characteristic of interest 13

Table 3.1.1 Ratings of department’s commitment to gender equality 15

Figure 3.1.1 Ratings of department gender distribution by gender 15

Figure 3.1.2 Department commitment to gender equality by gender and sub-discipline 16

Figure 3.2.1 Perceived allocation of tasks and resources by gender 17

Figure 3.2.2 Perceived allocation of additional academic duties by gender and sub-discipline 18

Figure 3.3.1 Proportion of respondents’ ratings of ease in obtaining senior post by gender 20

Figure 3.5.1.1 Perceived allocation of tasks and resources by gender and ethnicity 22

Figure 3.5.2.1 Perceived allocation of tasks and resources by gender and disability status 23

Figure 4.1.1 Recruitment method by gender 24

Table 4.3.1 Breakdown of summary scores and average ratings across items related to respondents’ decision to take their current post 25

Figure 4.3.1 Influence of quality of working life in taking up current post by gender and sub-discipline 26

Figure 4.3.2 Influence of commitment to equality in taking up current post by gender and sub-discipline 27

Figure 4.4.1.1 Influence of commitment to equality in taking up post by gender and ethnicity 28

Table 5.1.1 Current posts by gender 29

Figure 5.1.1 Salary band by gender 30

Figure 5.2.1 Time spent on academic duties by gender 32

Figure 5.3.1 Ratings of life in their department by gender 33

Table 5.4.1.1 Average ratings of all factors impacting the average academic career by gender 34

Figure 5.4.2.1 Areas of perceived impact on the average academic career by gender 36

Figure 5.5.1 Areas of perceived impact on respondents’ academic careers by gender 37

Figure 5.5.2 Perceived impact of sex on respondents’ own career progression by gender and sub-discipline 38

Figure 5.5.3 Perceived impact of sexual orientation on respondents’ own career progression by gender and sub-discipline 39

Table 5.5.1.1 Perceived impact of protected characteristics on own versus average academic career by gender 40

Figure 5.5.1.1 Perceived impact of protected characteristics on own and average academic career by gender 41

Figure 5.6.1.1 Ratings of departmental demands on time and effort by gender and ethnicity 42

Figure 5.6.1.2 Perceived impact of teaching experience on the average academic career by gender and ethnicity 42

Figure 5.6.2.1 Perceived impact of family/children on the average academic career by gender and disability status 43

Figure 5.6.2.2 Perceived areas of impact on respondents’ own career by gender and disability status 44


Index

Table 6.1.1.1 Proportions of respondents by type of parental leave and gender 45

Figure 6.1.1.1 Factors related to career progression by gender and parental leave status 46

Figure 6.1.1.2 Ability to relocate by gender and sub-discipline 47

Figure 6.1.1.3 Feeling supported by family or partner by gender and sub-discipline 48

Table 6.1.2.1 Proportion of respondents who did and did not receive or request information regarding childcare-related policies and options prior to parental leave 49

Figure 6.1.3.1 Reported availability of options/resources in the department to facilitate return from parental leave 50

Table 6.1.3.1 Average ratings of helpfulness of options to facilitate return from parental leave by gender 51

Figure 6.1.4.1 Ratings of feeling prepared to return from parental leave by gender 53

Figure 6.2.1 Difficulty returning to work by gender and parental leave status 54

Figure 6.3.1.1 Female respondents’ access to options/resources to facilitate return from parental leave by ethnicity 55

Figure 7.1.1 Training opportunities by gender 58

Figure 7.2.1 Training barriers by gender 59

Table 7.2.1 Training barriers related to protected characteristics by gender 60

Figure 7.2.2 Training opportunities by gender and sub-discipline 61

Figure 7.2.3 Training barriers by gender and sub-discipline 62

Figure 7.3.1.1 Training opportunities by gender and ethnicity 64

Figure 7.3.2.1 Training barriers by gender and disability status 65

Figure 8.1.1 Proportion of respondents encouraged or invited to apply for promotion by gender and sub-discipline 66

Figure 8.2.1 Ratings of departmental support for career development by gender 68

Figure 8.2.2 Assignment of formal mentor by gender and sub-discipline 69

Figure 8.2.3 Value of external professional activities by gender and sub-discipline 70

Figure 8.3.1 Ratings of desire to obtain senior management post versus expectations by gender 71

Figure 8.4.1.1 Ratings of desire to obtain senior management post versus expectations by gender and ethnicity 73

Figure 8.4.2.1 Ratings of departmental support for career development by disability status 74

Table 1.1.1 ASSET 2016 engineering subsample and HESA 2014/15 staff records by sub-discipline and gender 84

Table 1.2.1 ASSET 2016 engineering subsample and HESA 2014/15 staff records by sub-discipline and ethnicity 85

Table 1.2.2 ASSET 2016 engineering subsample and HESA 2014/15 staff records by ethnic group 85

Table 1.3.1 ASSET 2016 engineering subsample and HESA 2014/15 staff records by sub-discipline and disability status 86

Table 1.3.2 ASSET 2016 engineering subsample and HESA 2014/15 staff records by impairment type 86

Equality Challenge Unit

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© Equality Challenge Unit 2017 Information in this publication may be reproduced solely by ECU subscribers and the universities and colleges that ECU is funded to support, as long as it retains accuracy, the source is identified and it will not be used for profit. Use of this publication for any other purpose is prohibited without prior permission from ECU. Alternative formats are available: E [email protected] limited by guarantee. Registered in England and Wales, No. 05689975. Charity no. 1114417 (England, Wales) and SC043601 (Scotland).

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