Overcoming the current challenges caused by climate change and the crisis of society’s relationships with nature requires societal as well as economic transformation [...]

The TARGET approach aims at establishing a reflexive gender equality policy in research performing and research funding organisations. Monitoring has enormous potential to support reflexivity at both the institutional and the individual levels in the gender equality plan (GEP) development and implementation context. To exploit this potential, the monitoring system has to consist of meaningful indicators, which adequately represent the complex construct of gender equality and refer to the concrete objectives and policies of the GEP. To achieve this, we propose an approach to indicator development that refers to a theory of change for the GEP and its policies. Indicator development thus becomes a reflexive endeavour and monitoring a living tool. This requires constant reflection on data gaps, validity of indicators and the further development of indicators. Furthermore, we recommend the creation of space for reflexivity to discuss monitoring results with the community of practice. Keywords Gender monitoring Gender indicators Gender equality policy Policy steering Reflexivity Gender equality plan Citation Wroblewski, A. and Leitner, A. (2022), "Relevance of Monitoring for a Reflexive Gender Equality Policy", Wroblewski, A. and Palmén, R. (Ed.) Overcoming the Challenge of Structural Change in Research Organisations – A Reflexive Approach to Gender Equality, Emerald Publishing Limited, Bingley, pp. 33-52. https://doi.org/10.1108/978-1-80262-119-820221003 Publisher: Emerald Publishing Limited Copyright © 2022 Angela Wroblewski and Andrea Leitner License Published under exclusive licence by Emerald Publishing Limited. This work is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this book (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode 26th April 2021, signed by Angela Wroblewski and Rachel Palmén Introduction The TARGET approach to gender equality plan (GEP) development and implementation is based on the complete policy cycle model developed by May and Wildavsky (1978), which emphasises the role of empirical evidence for policy development in general. The starting point for the development of gender equality policies is the gender analysis, which identifies the main gender equality problems. The results of this analysis are used to define the gender equality priorities and goals, which then form the basis for the development and implementation of concrete measures. Both the implementation of these measures and the development of the context should be closely monitored, while the measures themselves should be evaluated by an external body after a given period of time and/or during the implementation phase. This approach is in line with the expectations formulated by the European Commission (EC) in the context of the GEP requirement in Horizon Europe (EC, 2020, 2021).1 The steps in the process outlined above hold enormous potential for reflexivity. For instance, the gender analysis is far more than the analysis of gender-segregated data such as the assessment of the representation of women and men in different areas or hierarchy levels and their access to resources. In addition, it should contain a discussion of the underlying gender concept (How is gender defined?), the gender equality objectives (What should be achieved?) as well as assumptions on reasons for gender inequalities (What are the underlying mechanisms?) within the organisation. The latter might be gender stereotypes, which influence criteria used in decision-making or the presentation of the organisation to the public (e.g. webpage, folders). Indicators for the gender analysis and monitoring can support this reflexive process if they go beyond simple sex counting. Careful checks should be made to ascertain if the data or indicators used contain some kind of gender bias or if they strengthen – unintendedly – gender stereotypes. Gender indicators should be based on an explicit gender concept, refer to at least one gender equality objective and provide a measurement that allows an analysis of the development of gender equality in the organisation. If gender equality priorities, targets and measures are formulated on such a basis, they will doubtlessly focus not only on increasing female representation but also on eliminating gender bias from structures and processes within the organisation. Monitoring the implementation of such priorities, targets and measures also opens up opportunities for reflection by empirically analysing both the progress towards gender equality and any persistent gender differences (or even backlash), thereby providing food for thought for further discussion. Involving stakeholders in all steps paves the way for an evidence-based gender equality discussion in an organisation, thereby raising awareness and encouraging a deep reflection on both the individual and institutional levels. The results of both the gender analysis and the monitoring should therefore be used to clearly communicate the need for action and the priorities identified. This chapter discusses the principles of monitoring and gender indicators and presents ways of developing a monitoring system for a tailor-made GEP. These will be illustrated using concrete examples taken from monitoring systems developed in the TARGET project. Purpose and Principles of Monitoring The main purpose of monitoring is to provide empirical evidence for the assessment of policy implementation and the reflection on current developments regarding gender equality (International Labour Organization, 2020; Wroblewski, Kelle, & Reith, 2017). Usually, the monitoring builds on the empirical analysis of the status quo (gender analysis or audit) and its data sources and indicators. It is, however, more than a regular update of the gender analysis. The monitoring itself will represent a further development due to the implementation of concrete policies and possible changes in the context. Therefore, gender monitoring should be interpreted as a living tool and as such be subjected to constant reflection regarding the reliability and validity of its indicators. A measure is reliable to the extent that it produces the same results repeatedly. While no data collection is totally reliable, the aim is always to reduce measurement error as far as possible. A measure is valid to the extent that it measures what it is intended to measure. The latter is of specific relevance in the gender context, an aspect that will be illustrated in the following. Markiewicz and Patrick (2016, p. 12) define monitoring as: the planned, continuous and systematic collection and analysis of program information able to provide management and key stakeholders with an indication of the extent of progress in implementation, and in relation to program performance against stated objectives and expectations. According to Rossi, Freeman and Lipsey (1999, p. 192), monitoring generally involves ‘program performance in the domain of service utilization, program organization and/or outcomes’. In concrete terms, a continuous monitoring of policy implementation generally pursues four goals, which together support the efficient use of resources: Monitoring should provide an overview of current developments in the context of the policy of interest (e.g. number and gender composition of employees or students, number and gender composition of decision-making bodies). Changes in relevant context indicators might influence policy implementation and should therefore be analysed on a regular basis. The core function of the monitoring is to provide information about policy implementation (e.g. number of policies implemented, number of participants in training programmes and share of women, number of beneficiaries of subsidies and share of women, budget spent on specific measures). The monitoring aims at identifying deviations between planned and actual policy implementation, which may indicate ineffective policy implementation or unrealistic policy assumptions. If such problems are detected at an early stage, they can be counteracted by adapting the policy or its implementation. In an ideal scenario, the indicators used in a monitoring system also provide the basis for policy steering. For example, when performance agreements between a university and the government or within a university (e.g. between the rectorate and the faculties) contain gender equality objectives, which are related to indicators, these indicators should be formulated in a way that corresponds to specific gender equality objectives. In general, the monitoring mainly addresses two groups, who should act on its results. The first is management, which takes monitoring data into account when deciding on the continuation, termination or adaptation of policies. The second are the people implementing the policies, who should use the monitoring results to reflect on and optimise implementation as required. To serve its purpose, a monitoring should be tailored to the concrete context of an organisation and its gender equality policies. The aim is not to provide lots of data (data cemetery) but data that are analysed on a regular basis. Accordingly, efficient monitoring should be based on the following principles (see also Wroblewski et al., 2017): Monitoring systems are based on data that are available on a regular basis and easily accessible. In most cases, monitoring indicators consist of quantitative indicators that are derived from the main objectives in a policy field. However, objectives cannot always be formulated in a quantifiable manner. In such cases, qualitative indicators should be included. A monitoring system should include indicators that describe the context of the policy or measure, its implementation as well as the expected output or outcome. Indicators focusing on the implementation of policies should be derived from a logic model or programme theory that has been explicitly formulated for the concrete policy. Monitoring indicators should be developed with the participation of the main stakeholders. The aim is to establish an agreed set of indicators that all relevant stakeholders accept as meaningful and relevant. This agreed set of indicators should likewise be based on a data source that all stakeholders define as reliable. The agreed set of indicators should be analysed at regular intervals (e.g. yearly or monthly). The timing should be linked to the planned intervals for presentation and discussion of monitoring results (e.g. in the form of annual or monthly reports). Regular presentation of monitoring results will both contribute to a gender equality discourse within the organisation and provide the basis for organisational learning. Even if monitoring provides a basis for the assessment of policy implementation, it still has to be distinguished from evaluation. Monitoring is the systematic documentation of key aspects of policy implementation that indicate whether the policy is functioning as intended or adhering to some appropriate standards. In contrast, evaluation is the systematic assessment of the operation and/or the outcomes of a program or policy, compared to a set of explicit or implicit standards, as a means of contributing to the improvement of the program or policy. (Weiss, 1998, p. 4) Since an evaluation usually takes place after a certain period of policy or programme implementation, it conveys an ex-post perspective. If the evaluation is performed in parallel to implementation, it is referred to as an ongoing evaluation that is characterised by blurred boundaries between monitoring and evaluation. However, while monitoring is carried out internally, evaluation aims at providing an external view on implementation. An evaluation can be commissioned by those implementing the policy or programme or by a superior authority (e.g. a state authority in the case of state-funded policies). Monitoring and evaluation are complementary approaches. The complementarity can take different forms (Markiewicz & Patrick, 2016, p. 17): The relationship is sequential when monitoring generates questions to be answered in an evaluation or evaluation identifies areas that require future monitoring. It is informational when monitoring and evaluation draw on the same data sources but ask different questions and frame different analyses. It is organisational when monitoring and evaluation draw on the same data sources, often channelled through the same administrative unit. It is methodological when monitoring and evaluation share similar processes and tools for obtaining data. It is hierarchical when performance data are used by various hierarchies, sometimes for monitoring and sometimes for evaluation. Finally, it is integrative when both approaches are designed at one time, unified and draw on a shared monitoring and evaluation framework. Regardless of the concrete relationship, monitoring and evaluation functions are integral to the effective operation of policies and programmes and increase the overall value they create. Gender Indicators The monitoring of a GEP ideally contains indicators that allow the assessment of its implementation as well as its outcomes. Hence, the monitoring is composed of gender indicators. Gender indicators do not represent gender equality per se. As gender equality is a complex construct, a gender indicator can only be an approximation. As Beck (1999, p. 7) puts it: An indicator is an item of data that summarises a large amount of information in a single figure, in such a way as to give an indication of change over time, and in comparison to a norm. Hence, indicators differ from statistics: the latter merely present facts while the former involve comparison to a norm and interpretation. A gender indicator is thus an indicator that captures gender-related change over time. The deviation between the indicator and the construct to be measured has to be reflected on and considered in the interpretation. In this context, the conceptualisation of gender and its equivalent in empirical evidence is of specific relevance. While gender is seen from a theoretical point of view as socially constructed (Butler, 1990; West & Fenstermaker, 1995; West & Zimmermann, 1987), it is usually coded dichotomously in administrative data (female/male). Accordingly, the variable sex or gender available in empirical data does not provide information about gender (Döring, 2013; Hedman, Perucci, & Sundström, 1996; United Nations Economic Commission for Europe (UNECE) & World Bank Institute, 2010). In addition, sex and gender interact with each other, for example, when the male body was the main reference in human medicine and clinical trials were conducted primarily by men, or when gender research in the 1960s focused mainly on women and was mainly conducted by female researchers (Stefanick & Schiebinger, 2020). Gender refers to norms, behaviours and roles associated with being a woman, man, girl or boy, as well as their relationships with one another. As a social construct, gender can change over time. Furthermore, both sex and gender produce inequalities that intersect with other social and economic inequalities. Hence, when discussing gender-based discrimination, gender intersects with other factors of discrimination such as age, socioeconomic status, disability, ethnicity, gender identity and sexual orientation (van der Haar & Verloo, 2013; Verloo, 2006; Walby, Armstrong, & Strid, 2012). To approach this complex construct in empirical analysis, the variable sex is differentiated by other relevant variables – if these are available. The availability of information on other relevant characteristics like disability, care responsibilities or gender identity is the exception rather than the norm. The assumption that specific characteristics like care responsibilities mainly apply to women may lead to an unintended emphasising of gender stereotypes and supports the identification of discrepancies as gender-based even though they are based on other characteristics (Degele, 2008; Stadler & Wroblewski, 2021). This problematic aspect gains additional relevance because available data might be gender biased, especially in the case of administrative data. The production of administrative data tends to overrepresent realities, which are male dominated. This becomes a problem if such data are used for analysing gender imbalances, for example, when labour market statistics are used to analyse gendered patterns of employment because official statistics only consider paid employment (Criado-Perez, 2019; D’Ignazio & Klein, 2020; Hedman et al., 1996). Gender indicators are not merely statistics on men and women. They highlight the contributions of men and women to society and (in our context) to science and research as well as their different needs and challenges. To depict this complex picture adequately, a set of indicators that covers all relevant aspects is required. The interpretation of one isolated indicator may be misleading. In the context of gender equality policies, the monitoring has to contain indicators, which address all three main gender equality objectives. In other words, it must contain indicators about women’s representation in all fields and at all hierarchical levels, indicators that represent structural barriers for women (such as women’s participation in decision-making) and indicators that display the integration of the gender dimension into research content and teaching. Data availability differs for these three dimensions, which in turn affects the validity of indicators. It is easier, for example, to depict women’s representation than it is to show the gender dimension in research content and teaching (see EC, 2018, 2019a, 2019b, 2019c, 2019d). In most cases, the availability of data on objective, gender-balanced representation in all fields and at all hierarchical levels is quite good. Education establishment knows the gender composition of students and staff in different disciplines as well as in decision-making bodies. Information on the share of women at different hierarchical levels is likewise usually available. Data availability is not so common when it comes to structural barriers for women’s careers. Information on the representation of women at different stages in appointment procedures, for instance, is not available by default. The availability of data on the integration of the gender dimension into research and teaching content is generally limited. Different data sources – such as administrative data that is electronically available (e.g. student or staff records) or project/publication repositories (to identify projects and publications with gender content) – are likewise relevant for monitoring. However, it is not always possible to extract gender-relevant information from electronic data management systems (e.g. in the context of recruitment). Hence, the development of indicators for gender analysis or gender monitoring often requires an adaptation of existing data sources, the establishment of new data collection mechanisms and specific data collection (e.g. a survey). Indicators can be either quantitative (e.g. number, percentage, ratio) or qualitative (e.g. assessment in qualitative terms). Regardless of their type, indicators should always be SMART2 (Doran, 1981). Ideally a combination of qualitative and quantitative approaches will be used to compensate for the shortcomings of both approaches (e.g. Flick, 2018; Mertens, 2017). The previous comments point to three key aspects of indicator development: First, it is important to use a consistent gender construct. Second, indicators should be derived from gender equality objectives and targets. Third, data collection is not an end in itself but should contribute to the purpose of monitoring. In the following, we will illustrate these aspects in reference to institutional context indicators and indicators addressing policy implementation for the three gender equality objectives. Institutional Context Indicators Institutional context indicators allow a description of the status quo of gender equality in the institution and provide the main information about the institution needed to interpret developments and changes properly. For a proper interpretation of these indicators, further information on the context is required (e.g. number of staff and students, number of management positions and decision-making bodies or number of new appointments). Changes in the share of female professors, for instance, should be interpreted with caution when the institution only has a few professorial positions. In such a case, one newly appointed woman or one retiring woman can have a big influence on the share of female professors. Furthermore, the interpretation of a lack of change requires information on the number of appointment procedures in the respective period. In the case of research funding organisations (RFOs), institutional context indicators refer to their core task, namely funding. These can include the number of calls or funded projects, the budgets available for funding or the number and composition of review panels. Institutional context indicators describing the status quo of gender equality are usually also used to measure outcomes. They should represent all three gender equality dimensions addressed in the GEP. Table 2.1 provides concrete examples for such indicators for research performing organisations (RPOs) and RFOs. Table 2.1. Examples for Institutional Context Indicators for RPOs and RFOs. RPOs RFOs Gender balance in all disciplines and at all hierarchical levels Share of women in disciplines (students, staff) and hierarchical positions Share of women among applicants Share of female principal investigators Decision-making Share of women in decision-making bodies Share of women among evaluators Share of women in RFO decision-making bodies Gender dimension in research and teaching content Share of research projects that address the gender dimension Share of teaching courses that consider the gender dimension Share of research projects that address the gender dimension Source: own research. Indicators for Policy Implementation Examples for indicators that focus on the implementation of policies can include the number of participants in programmes, the budget spent on programme implementation or the number of complaints addressed to an equality officer. A meaningful indicator for the monitoring of policy implementation should be derived from the concrete objective of the GEP or the concrete policy. In the course of policy development, a logic model (W.K. Kellogg Foundation, 2004) or theory of change (Funnell & Rogers, 2011) should be formulated, which explains the underlying assumptions on why the policy is expected to reach its target groups and objectives. Following this approach, the starting point for indicator development are the objectives, activities and targets formulated in the GEP. The objective is what is to be ultimately achieved, the final form or situation we would like to see. But it also has to be clearly distinguished from a vision. A vision can be idealistic; a goal must be more realistic. An organisation will ideally have a fixed vision that does not change over time. However, it can have different objectives and targets that are periodically adjusted to the vision. In most cases, and given their different purposes, it makes sense to differentiate between monitoring and evaluation targets. The targets formulated in the GEP relate to a strategic level or in evaluation terms to the impact. Monitoring targets generally refer to the implementation level, that is, the desired outputs of policies or measures (e.g. 100 employees should receive gender competence training in a specific year). They also need to be formulated for time spans that are covered by the monitoring (data collection dates/frequencies, e.g. annual, biannual). Evaluation targets, in contrast, refer to the impact or level of outcome. Indicators for this level cannot be measured in short frequencies (e.g. monthly or even biannually), and it is therefore of no practical use to set such short evaluation intervals. Targets at each level should be set at the same frequency/period as was planned for their measurement. Accordingly, targets at outcome level (for evaluative purposes) should ideally be set at three- or five-year intervals. The dimensions which monitoring indicators should represent also apply to the outcome or evaluation level. However, achieving the desired outputs does not necessarily result in achievement of the expected outcomes. Although this should logically be the case, assumptions that the measures should work can prove to be wrong, or unexpected circumstances can arise, which might affect outputs or outcomes. Table 2.2. Examples for Visions, Objectives and Targets. Visions Objective Evaluation Targets at Impact Level Monitoring Targets Structural barriers for women’s careers are abolished To foster equality in recruitment practices Increase the share of women among newly appointed professors up to the share of women among applicants Increase the share of women among newly appointed professors to X% by Y (date) Women and men are equally represented in decision-making To foster gender balance in decision-making committees and boards Increase the share of women in decision-making committees and boards Increase the share of women in board X to X% by Y (date). Increase the share of gender-balanced committees to X% by Y (date) All research projects consider the gender dimension in content in all stages of the research process To promote the integration of the gender dimension into research and innovation Increase the share of research projects that consider the gender dimension in their content Fund X (#) research projects that consider the gender dimension in their content per year Increase the share of reviewers with gender competence or expertise X% of all reviewers received gender training in year Y Source: own research. The assumptions as to why interventions should lead to their expected outcome are usually formulated in a theory of change or programme theory. A program theory is an explicit theory or model of how an intervention, such as a project, a program, a strategy, an initiative or a policy, contributes to a chain of intermediate results and finally to the intended or observed outcomes. (Funnell & Rogers, 2011, p. xix) The formulation of a theory of change allows lessons to be learned from failure and success and by referring to monitoring results. Reflections on policy or programme implementation based on monitoring can lead to an adaption of objectives or the implementation framework. The theory of change defines the central processes or drivers by which change is expected to come about for the organisation or the target group. The assumptions on which the theory of change is based could be derived from a formal research-based theory or an unstated, tacit understanding about how things work. A simplified representation of a theory of change is the logic model. The program logic model is defined as a picture of how your organization does its work – the theory and assumptions underlying the program. A program logic model links outcomes (both short- and long-term) with program activities/processes and the theoretical assumptions/principles of the program. (W.K. Kellogg Foundation, 2004, p. III) Opens in a new window.Fig. 2.1.Logic Model (Source: W.K. Kellogg Foundation (2004, p. 1).). The logic model is merely a simplified representation of mechanisms that lead to the expected outcome and impact because it does not consider feedback loops or nonlinear relations. However, referring to a theory of change when developing policies and monitoring indicators forces responsible stakeholders to think carefully about the concrete objectives and targets of an intervention and be realistic about the expected outcome given a specific input. Table 2.3 provides example input and output indicators for the three gender equality dimensions. Table 2.3. Examples for Implementation Indicators. Policy/Programme Aim Input Indicator Output Indicator Abolishment of structural barriers for women’s careers Share of job advertisements that are formulated in gender-sensitive language Share of selection committee members who participated in anti-bias training Share of women among newly appointed staff in relation to the share of female applicants Gender balance in decision-making Number of gender competence training measures for members of decision-making bodies Share of women in newly established decision-making bodies Integration of gender dimension into research content and teaching Share of researchers who participated in awareness-raising or training measures focusing on the gender dimension in research content Share of research projects that formulate gender-specific research questions (self-assessment) Share of teachers who participated in training measures focusing on gender-sensitive didactics Share of courses with literature focusing on relevant gender issues in in their syllabus Source: own research. Referring to a logic model supports the formulation of consistent and coherent policies and reduces the risk of failure due to unrealistic expectations that implementation cannot meet. It also provides criteria for the success and failure of policies (Engeli & Mazur, 2018). To illustrate this, we will now look in more detail at how the logic model can be applied to quotas for decisi

Im Zuge der neoliberalen Universitätsreform wurde ein Management by Objectives als hochschulpolitisches Steuerungsinstrument etabliert. Diese Steuerungslogik wurde auch auf Gleichstellung übertragen. Die damit verbundene Quantifizierung von Gleichstellung wird vonseiten der feministischen Hochschulforschung kritisch gesehen, da gleichstellungspolitische Ziele auf quantitativ abbildbare Probleme beschränkt bleiben. Der vorliegende Beitrag untersucht am Beispiel österreichischer Universitäten das Instrument des Gender-Monitorings im Spannungsfeld von theoretischen Ansprüchen und Datenverfügbarkeit und zeigt Ansatzpunkte für dessen Weiterentwicklung auf. Zentrale Aspekte, um das Potenzial eines Gender-Monitorings für Gleichstellungspolitik nutzen zu können, sind die Entwicklung theoretisch fundierter gleichstellungspolitischer Ziele, die Reflexion von Datenlücken im Monitoring und dessen Einbettung in einen gleichstellungspolitischen Diskurs.

How did gender mainstreaming and the introduction of sex quotas in management affect the gender equality project in higher education? After 20 years of establishing gender equality structures and monitoring the proportion of women in decision-making, persistent gender inequality in universities confirms a paradoxical situation: while the number of women in decision-making has increased, institutional policies in universities have had minimal effects in eliminating gender inequality. By discussing two main components of gender mainstreaming—the representation of women and its transformative claim—our analysis points to two missing and interlinked factors that help explain the paradox. We argue that ensuring the empowerment of gender structures and building gender competence are prerequisites for overcoming the status quo.

Austrian gender equality policy in higher education is characterized by the successful implementation of a comprehensive set of gender equality policies and persistent gender imbalances. After the introduction of a legal quota for university bodies, for instance, female representation in decision-making bodies increased significantly within a short period of time. However, this did not lead to a cultural change or the abolishment of barriers to women’s careers. Research has attributed this paradoxical situation to a lack of reflexivity because the current gender equality policies do not force institutions or individuals to challenge traditional practices, which are perceived to be merit-based and therefore gender neutral. To overcome this paradox, the Austrian Federal Ministry of Education, Science, and Research launched a policy process aimed at strengthening gender competence in all higher education processes—management, administration, teaching, and research. This paper provides a critical discussion of the Austrian quota regulation and its implementation. It also introduces the concept of gender competence and outlines the underlying assumptions as to why the new policy is expected to contribute to change. Following a critical reflection on these assumptions, the paper also discusses how existing steering instruments have to be adapted to support individual and institutional reflexivity.

Expectations of research, technology and innovation (RTI) policy are shifting towards effectively addressing major societal challenges. Due to its potential to increase innovative dynamics, to develop new knowledge and create new solutions, social innovation is increasingly promoted. This raises questions about (potential) effects and impacts of social innovation. The assessment of impacts is a rather new topic in this field, respective research is still in its early stages. This paper proposes to focus on the change of social practices within RTI ecosystems when assessing social innovation. The ecosystem approach is not only a helpful concept to analyse the emergence and diffusion of social innovation in a specific context, it can also be used to support and guide policy design. Implication for evaluation design are discussed and analytical categories presented. A set of measurement dimensions is proposed that can be used in evaluation designs and for future research.

European Research Area (ERA) Priority 4 focuses on gender equality and gender mainstreaming in research and innovation. The objective is to foster scientific excellence and a breadth of research approaches by fully utilising gender diversity and equality and avoiding an indefensible waste of talent. Within their National Action Plans (NAPs), European Union Member States are asked to develop policies which address gender imbalances particularly at senior levels and in decision making and which strengthen the gender dimension in research. Member States and Associated Countries should initiate gender equality policies in research performing organisations (RPOs) and research funding organisations (RFOs). They should also monitor the effectiveness of such policies on a regular basis and adjust measures as necessary. The report benchmarks the implementation of Priority 4 in national ERA roadmaps or NAPs, identifies best practices in national legal and policy environments which support progress towards achieving Priority 4. Based on the assessment of the NAPs and their results recommendations for a new ERA are formulated.

This entry provides an overview of gender equity policies in Austria, Germany and Switzerland, including their shared need for such policies, and then explores the importance of women’s studies, the promotion of women, and gender mainstreaming to strengthen gender equality. Then the entry examines the paradox that exists in higher education in the 21st century: while gender equity policies have been successfully implemented, the dominant culture in academia remains unchanged.

The report summarises the results of the evaluation of the three career advancement programmes at Danube University Krems implemented by the Office for Equality and Gender Studies. Danube University Krems is breaking new ground with regard to the development of gender equality measures, as it is the first university in Austria to subject its measures for the advancement of women and gender equality in their entirety to an external evaluation rather than a selected measure.

This entry describes three different approaches—promotion of women, gender mainstreaming, and cultural/structural change —which are used to pursue the three goals of gender equality in higher education: to abolish all forms of discrimination in access to higher education as well as in career progression, to change the gender biased university culture and to strengthen the gender dimension in research content and teaching.

Little is known to date about the practice and perceptions of RRI among researchers in Europe as well as the integration of the gender dimension into everyday RRI practices. This lack was addressed by two large-scale surveys that were launched in the course of the EU-funded MoRRI project (Monitoring the evolution and benefits of RRI, Contract number RTD-B6-PP-00964-2013, Duration 09/2013-03/2018). The analysis shows that the institutional environment positively influences the degree of RRI activities and the general attitudes towards more responsible research and innovation: researchers working in an institutional environment that systematically supports the practice of RRI are more active in RRI practices than researchers who do not rely on such structures. For the gender equality dimension, this means that institutions with a gender equality plan (GEP) in place are more inclined to support female researchers than institutions without such institutional incentives. Furthermore, researchers with experiences in EU-funded projects are more likely to be engaged in RRI activities. Even if female researchers have a stronger inclination to engage with society than their male counterparts, gender competence proves to be the relevant distinguishing criterion. Gender competent researchers are more often involved in other RRI activities.

This article examines whether and under which conditions a rising participation of women in higher education management contributes to cultural and structural change in science and research. In Austria, the introduction of a statutory quota regulation for university decision-making bodies like the rectorate, the senate, or the university council brought about a rapid and substantial increase in the share of female rectors and vice rectors. However, there are also gender-specific differences among rectorate members: women are significantly younger than men when they take up a rectorate position and switch less frequently from a professorship to such a position. This situation and the gender expertise of the rectors and vice rectors themselves contribute to the potential for change. Explicit gender equality goals and the establishment of gender competence as a qualification criterion for all rectors and vice rectors would be needed to make use of the potential of women in the rectorate to be agents for cultural and structural change.