Policymaking to reduce gender inequalities: Lessons and challenges

Dr Emily St.Denny, Lecturer in Public Policy, University of Copenhagen

Dr Paul Cairney, Professor of Politics and Public Policy, Faculty of Arts and Humanities

Dr Sean Kippin, Lecturer in Public Policy, Faculty of Arts and Humanities

Every year, March 8^th marks International Women’s Day: an official UN holiday to draw attention to women’s rights and gender equality, celebrating achievements and highlighting challenges. There is a strong consensus that reducing gender inequality is the right thing to do and has wider economic and social benefits. There is also evidence that some gender gaps have narrowed, for example in education.

Nevertheless, significant inequalities still persist, despite policy interventions from states and organisations like the European Union and the United Nations. For instance, women remain underrepresented in politics and in corporate leadership, are more likely to be poor, and are frequently victims of gendered violence, harassment and discrimination.

As part of our research for the IMAJINE project, we studied how governments might make better policies to reduce gender inequalities. Ideas abound, and feminist civil society and policy actors have generated new visions to improve gender equality policy and policymaking.

Despite this, many advocates remain disappointed by slow progress and poor outcomes. We therefore sought to analyse the rich literature on gender inequality policy to identify potential lessons to help policymakers more effectively tackle the issue. In particular we looked at the case of ‘Gender mainstreaming’ as one example of an influential policy agenda that has gained global prominence.

Overall, we identify three challenges facing policymakers seeking to make and deliver effective inequality reduction policies:

Challenge 1: Defining equality

Gender equality is an ambiguous and contested term. Interpretations of how and why gender inequality constitutes a problem vary significantly and beliefs about how best to address it are subject to ongoing debate. We can identify some common ground, with broad consensus that ‘gender inequality’ refers to the fact that some individuals, especially women, face discrimination, hardships, or missed opportunities on the basis of their gender. Nevertheless, when policy actors seek to make sense of gender equality as a policy goal, they contribute to three different interpretations of the problem based on what they consider ‘equality’ to mean. These different interpretations lead to different diagnoses of the solution and, ultimately, different forms of public action.

• Equality of treatment: women and men are the same and therefore deserving of equal treatment (e.g. establish of anti-discrimination laws).
• Equality of opportunity: there are differences between men and women that identify women as deserving of special protection or affirmative action to redress socially and historically entrenched inequalities.
• Equality of outcome/impact: focus on equal outcomes, for example through ‘gender mainstreaming’ – a strategy to ensure that the goal of advancing gender equality is actively integrated into all stages of the policymaking process across all sectors.

This ambiguity can be assessed in different ways. On the one hand, it has allowed broad coalitions to mobilise in its defense and elevate it as an important issue. On the other, ambiguity has made it possible to label a wide range of policies as ‘gender equality policies’, some of which are (intentionally and unintentionally) ineffective or become so in the absence of coordination with other policy efforts.

Policymakers seeking to improve gender equality through public action must therefore grapple with a trade-off: define the term very specifically and perhaps increase its meaningfulness as a concrete policy goal but risk narrowing the possible impact of policy and alienating those with alternative interpretations.

Challenge 2: Designing effective policies

Policymakers can choose from different instruments to craft their response, but options are limited by calculations of what is feasible.

One choice is between ‘soft’ instruments that rely on voluntary take-up, such as benchmarking and the issuance of recommendations, and ‘hard’ instruments, which are imposed and include penalties for non-compliance.

For example, in the case of the EU, we can contrast the publication of gender equality data by the European Institute for Gender Equality, which is intended to incentivize Member States to continually strive to improve their position, with the introduction of the EU Work-Life Balance Directive, which requires Member States to introduce earmarked paternity leave.

There is a tendency for soft instruments to be associated with a weaker commitment to gender equality, held responsible for a dilution of policy efficacy over time. Our research suggests, however, that soft instruments have their uses. In particular, since they do not require strong consensus to adopt, they are easier to introduce and adapt to local circumstances. For this reason, they may also serve as a useful way to prime support across the policy community ahead of trying to introduce harder and more binding instruments.

Policymakers seeking to improve efforts to reduce gender inequality should therefore think carefully about policy design in relation to overall coherence, or the extent to which policy actions mutually reinforce each other. Seen this way, policy coherence becomes an ongoing and everyday concern about the extent to which instruments and actions work effectively together over time, rather than simply at the moment of introduction. This may involve trade-offs over instrument selection as well as policy goals, such as whether to focus on securing immediate material objectives or achieving longer-term strategic goals. 

Challenge 3: More than an implementation gap

An ‘implementation gap’ refers to the discrepancy between policy choices and actual outcomes. Thinking of the challenge of contemporary gender equality policy as an implementation gap is too reductive. It is not just that effective gender equality policy is hard to make and even harder to implement effectively. It is also that the way we make policy, and many of the people involved, actively contribute to sustaining gender inequalities.

Some of this can be attributed to resistance by some policymakers to gender equality as a legitimate and desirable goal. However, a lot can be attributed to the fact that many well-intentioned policy actors have not grasped the structural nature of gender inequality. Consequently, they are ill-equipped to address inequalities and inadvertently reproduce them. This can be seen when gender equality policy takes the shape of bureaucratic  instruments and ‘tick box’ exercises rather than a more meaningful commitment to reforming the way we make and deliver policy. At the same time, making gender everybody’s business also risks making it nobody’s business if specialized equality institutions are dismantled for being redundant.

Overall, what our research suggests is that policymakers must let go of the illusion that gender equality can be achieved as a matter of mundane routine, without having to make fundamentally political decisions about big questions including: what do we mean by equality, what does it look like in practice, and are we willing to get out of our comfort zone to achieve it?

This post first appeared on the University of Stirling Public Policy blog

Policy learning to reduce inequalities: a practical framework

This post first appeared on LSE BPP on 16.11.2020 and it describes the authors’ published work in Territory, Politics, Governance (for IMAJINE)

While policymakers often want to learn how other governments have responded to certain policies, policy learning is characterized by contestation. Policymakers compete to define the problem, set the parameters for learning, and determine which governments should take the lead. Emily St.Denny, Paul Cairney, and Sean Kippin discuss a framework that would encourage policy learning in multilevel systems.

Governments face similar policy problems and there is great potential for mutual learning and policy transfer. Yet, most policy research highlights the political obstacles to learning and the weak link between research and transfer. One solution may be to combine academic insights from policy research with practical insights from people with experience of learning in political environments. In that context, our role is to work with policy actors to produce pragmatic strategies to encourage realistic research-informed learning.

Pragmatic policy learning

Producing concepts, research questions, and methods that are interesting to both academics and practitioners is challenging. It requires balancing different approaches to gathering and considering ‘evidence’ when seeking to solve a policy problem. Practitioners need to gather evidence quickly, focusing on ‘what works’ or positive experiences from a small number of relevant countries. Policy scholars may seek more comprehensive research and warn against simple solutions. Further, they may do so without offering a feasible alternative to their audience.

To bridge these differences and facilitate policy learning, we encourage a pragmatic approach to policy learning that requires:

• Seeing policy learning through the eyes of participants, to understand how they define and seek to solve this problem;
• Incorporating insights from policy research to construct a feasible approach;
• Reflecting on this experience to inform research.

Our aim is not ‘evidence-based policymaking’. Rather, it is to incorporate the fact that researchers and evidence form only one small component of a policymaking system characterized by complexity. Additionally, policy actors enjoy less control over these systems than we might like to admit. Learning is therefore best understood as a contested process in which actors combine evidence and beliefs to define policy problems, identify technically and politically feasible solutions, and negotiate who should be responsible for their adoption and delivery in multilevel policymaking systems. Taking seriously the contested, context-specific, and political nature of policymaking is crucial for producing effective advice from which to learn.

Policy learning to reduce inequalities

We apply these insights as part of the EU Horizon 2020 project Integrative Mechanisms for Addressing Spatial Justice and Territorial Inequalities in Europe (IMAJINE). Its overall aim is to research how national and territorial governments across the European Union pursue ‘spatial justice’ and try to reduce inequalities.

Our role is to facilitate policy learning and consider the transfer of policy solutions from successful experiences. Yet, we are confronted by the usual challenges. They include the need to: identify appropriate exemplars from where to draw lessons; help policy practitioners control for differences in context; and translate between academic and practitioner communities.

Additionally, we work on an issue – inequality – which is notoriously ambiguous and contested. It involves not only scientific information about the lives and experiences of people, but also political disagreement about the legitimate role of the state in intervening in people’s lives or redistributing of resources. Developing a policy learning framework that is able to generate practically useful insights for policy actors is difficult but key to ensuring policy effectiveness and coherence.

Drawing on work we carried out for the Scottish Government’s National Advisory Council on Women and Girls on approaches to reducing inequalities in relation to gender mainstreaming, we apply the IMAJINE framework to support policy learning. The IMAJINE framework guides such academic–practitioner analysis in four steps:

Step 1: Define the nature of policy learning in political systems.

Preparing for learning requires taking into account the interaction between:

• Politics, in which actors contest the nature of problems and the feasibility of solutions;
• Bounded rationality, which requires actors to use organizational and cognitive shortcuts to gather and use evidence;
• ‘Multi-centric’ policymaking systems, which limit a single central government’s control over choices and outcomes.

These dynamics play out in different ways in each territory, which means that the importers and exporters of lessons are operating in different contexts and addressing inequalities in different ways. Therefore, we must ask how the importers and exporters of lessons: define the problem, decide what policies are feasible, establish which level of government should be responsible for policy and identify criteria to evaluate policy success.

Step 2: Map policymaking responsibilities for the selection of policy instruments.

The Council of Europe defines gender mainstreaming as ‘the (re)organisation, improvement, development and evaluation of policy processes, so that a gender equality perspective is incorporated in all policies at all levels and at all stages’.

Such definitions help explain why mainstreaming approaches often appear to be incoherent. To map the sheer weight of possible measures, and the spread of responsibility across many levels of government (such as local, Scottish, UK and EU), is to identify a potentially overwhelming scale of policymaking ambition. Further, governments tend to address this potential by breaking policymaking into manageable sectors. Each sector has its own rules and logics, producing coherent policymaking in each ‘silo’ but a sense of incoherence overall, particularly if the overarching aim is a low priority in government. Mapping these dynamics and responsibilities is necessary to ensure lessons learned can be effectively applied in similarly complex domestic systems.

Step 3: Learn from experience.

Policy actors want to draw lessons from the most relevant exemplars. Often, they will have implicit or explicit ideas concerning which countries they would like to learn more from. Negotiating which cases to explore, so that it takes into consideration both policy actors’ interests and the need to generate appropriate and useful lessons, is vital.

In the case of mainstreaming, we focused on three exemplar approaches, selected by members of our audience according to perceived levels of ambition: maximal (Sweden), medial (Canada) and minimal (the UK, which controls aspects of Scottish policy). These cases were also justified with reference to the academic literature which often uses these countries as exemplars of different approaches to policy design and implementation.

Step 4: Deliberate and reflect.

Work directly with policy participants to reflect on the implications for policy in their context. Research has many important insights on the challenges to and limitations of policy learning in complex systems. In particular, it suggests that learning cannot be comprehensive and does not lead to the importation of a well-defined package of measures. Bringing these sorts of insights to bear on policy actors’ practical discussions of how lessons can be drawn and applied from elsewhere is necessary, though ultimately insufficient. In our experience so far, step 4 is the biggest obstacle to our impact.

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