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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Policy Analysis in 750 Words: Reflecting on your role as a policy analyst

This post forms one part of the Policy Analysis in 750 words series overview.

One aim of this series is to combine insights from policy research (1000, 500) and policy analysis texts.

If we take key insights from policy theories seriously, we can use them to identify (a) the constraints to policy analytical capacity, and (b) the ways in which analysts might address them. I use the idea of policy analyst archetypes to compare a variety of possible responses.

Key constraints to policy analytical capacity

Terms like ‘bounded rationality’ highlight major limits on the ability of humans and organisations to process information.

• Humans use heuristics or cognitive shortcuts to process enough information to make choices, and institutions are the rules used by organisations to limit information processing.

Terms like policymaking ‘context’, ‘environments’, and multi-centric policymaking suggest that the policy process is beyond the limits of policymaker understanding and control.

• Policy actors need to find ways to act, with incomplete information about the problem they seek to solve and the likely impact of their ‘solution’.
• They gather information to help reduce uncertainty, but problem definition is really about exercising power to reduce ambiguity: select one way to interpret a problem (at the expense of most others), and limit therefore limit the relevance and feasibility of solutions.
• This context informs how actors might use the tools of policy analysis. Key texts in this series highlight the use of tools to establish technical feasibility (will it work as intended?), but policymakers also select tools for their political feasibility (who will support or oppose this measure?).

How might policy analysts address these constraints ethically?

Most policy analysis texts (in this series) consider the role of professional ethics and values during the production of policy analysis. However, they also point out that there is not a clearly defined profession and associated code of conduct (e.g. see Adachi). In that context, let us begin with some questions about the purpose of policy analysis and your potential role:

1. Is your primary role to serve individual clients or some notion of the ‘public good’?
2. Should you maximise your role as an individual or play your part in a wider profession?
3. What is the balance between the potential benefits of individual ‘entrepreneurship’ and collective ‘co-productive’ processes?
4. Which policy analysis techniques should you prioritise?
5. What forms of knowledge and evidence count in policy analysis?
6. What does it mean to communicate policy analysis responsibly?
7. Should you provide a clear recommendation or encourage reflection?

 

Policy analysis archetypes: pragmatists, entrepreneurs, manipulators, storytellers, and decolonisers

In that context, I have created a story of policy analysis archetypes to identify the elements that each text emphasises.

The pragmatic policy analyst

• Bardach provides the classic simple, workable, 8-step system to present policy analysis to policymakers while subject to time and resource-pressed political conditions.
• Dunn also uses Wildavsky’s famous phrase ‘art and craft’ to suggest that scientific and ‘rational’ methods can only take us so far.

The professional, client–oriented policy analyst

• Weimer and Vining provide a similar 7-step client-focused system, but incorporating a greater focus on professional development and economic techniques (such as cost-benefit-analysis) to emphasise a particular form of professional analyst.
• Meltzer and Schwartz also focus on advice to clients, but with a greater emphasis on a wide variety of methods or techniques (including service design) to encourage the co-design of policy analysis with clients.

The communicative policy analyst

•  C. Smith focuses on how to write and communicate policy analysis to clients in a political context.
• Compare with Spiegelhalter and Gigerenzer on how to communicate responsibly when describing uncertainty, probability, and risk.

The manipulative policy analyst.

• Riker helps us understand the relationship between two aspects of agenda setting: the rules/ procedures to make choice, and the framing of policy problems and solutions.

The entrepreneurial policy analyst

• Mintrom shows how to combine insights from studies of policy entrepreneurship and policy analysis, to emphasise the benefits of collaboration and creativity.

The questioning policy analyst

• Bacchi  analyses the wider context in which people give and use such advice, to identify the emancipatory role of analysis and encourage policy analysts to challenge dominant social constructions of problems and populations.

The storytelling policy analyst

• Stone identifies the ways in which people use storytelling and argumentation techniques to define problems and justify solutions. This process is about politics and power, not objectivity and optimal solutions.

The decolonizing policy analyst.

• L.T. Smith does not describe policy analysis directly, but shows how the ‘decolonization of research methods’ can inform the generation and use of knowledge.
• Compare with Hindess on the ways in which knowledge-based hierarchies rely on an untenable, circular logic.
• Compare with Michener’s thread, discussing Doucet’s new essay on (a) the role of power and knowledge in limiting (b) the ways in which we gather evidence to analyse policy problems.

Incisive essay from @bailabomba on studying the use of research evidence through critical perspectives that center the marginalized. There is so too much good stuff in here to summarize via twitter (you should just read it). But let me point out a few things that resonated (1/n) https://t.co/nIahyIjwBo

— Jamila Michener (@povertyscholar) December 17, 2019

Using archetypes to define the problem of policy analysis

Studies of the field (e.g. Radin plus Brans, Geva-May, and Howlett) suggest that there are many ways to do policy analysis. Further, as Thissen and Walker describe, such roles are not mutually exclusive, your views on their relative value could change throughout the process of analysis, and you could perform many of these roles.

Further, each text describes multiple roles, and some seem clustered together:

• pragmatic, client-orientated, and communicative could sum-up the traditional 5-8 step approaches, while
• questioning, storytelling, and decolonizing could sum up an important (‘critical’) challenge to narrow ways of thinking about policy analysis and the use of information.

Still, the emphasis matters.

Each text is setting an agenda or defining the problem of policy analysis more-or-less in relation to these roles. Put simply, the more you are reading about economic theory and method, the less you are reading about dominance and manipulation.

How can you read further?

Michener’s ‘Policy Feedback in a Racialized Polity’ connects to studies of historical institutionalism, and reminds us to use insights from policy theories to identify the context for policy analysis.

I have co-authored a lot about uncertainty/ ambiguity in relation to ‘evidence based policymaking’, including:

• Fostering Evidence-informed Policy Making: Uncertainty Versus Ambiguity(PDF)
• To Bridge the Divide between Evidence and Policy: Reduce Ambiguity as Much as Uncertainty
• How to communicate effectively with policymakers: combine insights from psychology and policy studies

See also The new policy sciences for a discussion of how these issues inform Lasswell’s original vision for the policy sciences (combining the analysis of and for policy).

In the Scottish Parliament election, the only clear majority was secured by men

Although the symbolic representation of women in the Scottish Parliament was a key plank of the ‘new politics’ of Scottish devolution, women continue to secure just over one-third of seats. In 2016, women secured 45 of 129 seats (35%), which compares with 37% in 1999, 40% in 2003, 33% in 2007, and 35% in 2011.

The number of women in the Scottish Parliament used to depend strongly on the fate of Scottish Labour: the high point of 40% in 2003 was on the back of 28 Labour MSPs representing 56% of its group and accounting for 55% of women MSPs (Cairney and McGarvey, 2013: 106; Cairney et al, 2015). At the time, it was the only party to ‘twin’ constituencies and alternate women/ men candidates on the regional list (Mackay and Kenny, 2007: 86-7).

Other parties pursued less systematic or effective measures: the Liberal Democrats’ were ‘half hearted’ (Kenny and MacKay, 2013: 8; Cairney, 2011, 30); the SNP had ‘an informal rule of thumb that [regional] lists should be more-or less gender balanced’ (Mackay and Kenny, 2007: 87), the Conservatives sometimes ensured that women ‘were generally placed in favourable positions on the party lists’, and the Greens alternated men and women on party lists with uncertain effect (Kenny and MacKay, 2013: 9).

Now, as Labour’s fortunes have dropped, the decision by the SNP to use stronger measures – including All Women Shortlists for seats vacated by retiring MSPs – seems particularly important (Kenny and Mackay, 2013; Kenny, 2015; Swann, 2016a; on the substantive representation of women, see Engender 2016a; 2016b).

You can see the difference in the membership of the parties that really try …

Women MSPs, by Party, 1999-2016

	1999	2003	2007	2011	2016
SNP	15 (42.9%)	9 (33.3%)	12 (25.5%)	19 (27.5%)	27 (42.9%)
Conservative	3 (16.7%)	4 (22.2%)	5 (31.2%)	6 (40.0%)	6 (19.4%)
Labour	28 (50.0%)	28 (56.0%)	23 (50.0%)	17 (45.9%)	11 (45.8%)
Greens	0 (0%)	2 (28.6%)	0 (0%)	1 (50%)	1 (16.7%)
Lib Dems	2   (11.8%)	2   (11.8%)	2   (12.5%)	1   (20.0%)	0 (0%)
Total	48 (37.2%)	51 (39.5%)	43 (33.3%)	45 (34.9%)	45 (34.9%)

 

Source: adapted and updated (using figures from Gender Politics, 2016 and Swann, 2016b) from Cairney et al (2015: 9). Table does not include ‘other’ parties/ independents.

Apologies for the Harvard versus weblink referencing. This is a short section  copy/pasted from an article  that I am writing for Scottish Affairs (to be published in August 2016). You can find the full paper here:  Cairney 2016 Scottish Parliament election 2016 in Scottish Affairs 11.5.16

Policy Concepts in 1000 Words: Feminism, Postcolonialism, and Critical Policy Studies

See also three more recent posts:

1. Policy in 500 Words: Power and Knowledge
2. Policy in 500 Words: Feminist Institutionalism
3. Policy Analysis in 750 words: Linda Tuhiwai Smith (2012) Decolonizing Methodologies

In this post, let’s begin with a transition from two others: combining theories, and critical policy studies/ the NPF. Both posts raise the same basic question: what is science? This question leads to a series of concerns about the criteria we use to determine which theories are most worthy of our investment, and the extent to which social scientific criteria should emulate those in natural science.

One set of criteria, which you can find in the ‘policy shootout!’, relates to the methods and principles we might associate with some branches of natural science (and use, for example, to support astronomy but not astrology):

• A theory’s methods should be explained so that they can be replicated by others.
• Its concepts should be clearly defined, logically consistent, and give rise to empirically falsifiable hypotheses.
• Its propositions should be as general as possible.
• It should set out clearly what the causal processes are.
• It should be subject to empirical testing and revision

If we were to provide a caricature of this approach, we might associate it with other explicit or implicit principles, such as:

1. The world exists independently of our knowledge of it, and our role is to develop theories to help us understand its properties (for example, discover its general laws).
2. These principles help us produce objective science: if the methods and results can be replicated, they do not depend on individual scientists.

In other words, the caricature is of a man in a white lab coat gathering knowledge of his object of study while remaining completely separate from it. Such principles are generally difficult to maintain, and relatively tricky in the study of the social world (and it seems increasingly common for one part of PhD training to relate to reflexivity – see what is our role in social scientific research)? However, critical challenges go far beyond this point about false objectivity.

The challenge to objective science: 1. the role of emancipatory research

One aspect of feminist and postcolonial social science is to go beyond the simple rejection of the idea of objective social science: a further key (or perhaps primary) aim is to generate research with emancipatory elements. This may involve producing research questions with explicit normative elements and combining research with recommendations on social and political change.

The challenge to objective science: 2. a rejection of the dominant scientific method?

A second aspect is the challenge to the idea that one dominant conception of scientific method is correct. Instead, one might describe the scientific rules developed by one social group to the exclusion of others. This may involve historical analysis to identify the establishment of an elite white male dominance of science in the ‘West’, and the ‘Western’ dominance of science across the world.

To such scientists, a challenge to these criteria seems ridiculous: why reject the scientific principles that help us produce objective science and major social and technological advances? To their challengers, this response may reflect a desire to protect the rules associated with elite privilege, and to maintain dominance over the language we use to establish which social groups should be respected as the generators of knowledge (the recipients of prestige and funding, and perhaps the actors most influential in policy).

The challenge to objective science: 3. the democratisation of knowledge production

A third is the challenge to the idea that only well-trained scientists can produce valuable knowledge. This may involve valuing the knowledge of lived experience as a provider of new perspectives (particularly when people are in the unusual position to understand and compare their perspective and those of others). It also involves the development of new research methods and principles, combined with a political challenge to the dominance of a small number of scientific methods (for example, see rejections of the hierarchy of knowledge at which the systematic review of randomised control trials is often at the top).

Revisiting the live debate on the NPF and critical/ interpretive studies

This seems like good context for some of the debate on the NPF (see this special issue). One part of the debate may be about fundamentally different ideas about how we do research: do we adhere to specific scientific principles, or reject them in favour of a focus on, for example, generating meaning from statements and actions in particular contexts?

Another part may reflect wider political views on what these scientific principles represent (an elitist and exclusionary research agenda, whose rules reinforce existing privileges) and the role of alternative methods, in which critical policy studies may play an important part. In other words, we may be witnessing such a heated debate because critical theorists see the NPF as symbolic of attempts by some scholars to (a) reassert a politically damaging approach to academic research and (b) treat other forms of research as unscientific.

Where do we go from here?

If so, we have raised the stakes considerably. When I wrote previously about the problems of combining the insights and knowledge from different theories, it often related to the practical problems of research resources and potential for conceptual misunderstanding. Now, we face a more overt political dimension to social research and some fundamentally different understandings of its role by different social groups.

Can these understandings be reconciled, or will they remain ‘incommensurable’, in which we cannot generate agreement on the language to use to communicate research, and therefore the principles on which to compare the relative merits of approaches? I don’t know.

Initial further reading

Paying attention to this intellectual and political challenge provides a good way ‘in’ to reading that may seem relatively unfamiliar, at least for students with (a) some grounding in the policy theories I describe, and (b) looking to expand their horizons.

Possibly the closest link to our focus is when:

• Bacchi (1999) describes ‘the politics of policy studies’ by applying insights from policy studies (including power, framing, and social construction) to the study of policy.
• See also Policy Analysis in 750 words: Carol Bacchi’s (2009) WPR Approach

First, we know that policy problems do not receive policymaker attention because they are objectively important. Instead, actors compete to define issues and maximise attention to that definition. Second, we do the same when we analyse public policy: we decide which issues are worthy of study and how to define problems. Bacchi (1999) argues that the ‘conventional’ policy theorists (including Simon, Bardach, Lindblom, Wildavsky) try to ‘stand back from the policy process’ to give advice from afar, while others (including Fischer, Drysek, Majone) “recognise the analysts’ necessarily normative involvement in advice giving” (1999: 200). Combining both points, Bacchi argues that feminists should engage in both processes – to influence how policymakers and analysts define issues – to, for example, challenge ‘constructions of problems which work to disempower women’ (1999: 204). This is a topic (how should academics engage in the policy process?) which I follow up in a study of EBPM.

For a wider discussion of feminist studies and methods, see:

• Fonow and Cook’s ‘pragmatic’ discussion about how to do feminist public policy research based on key principles:

‘Our original analysis of feminist approaches to social science research in women’s studies revealed some commonalities, which we articulated as guiding principles of feminist methodology: first, the necessity of continuously and reflexively attending to the significance of gender and gender asymmetry as a basic feature of all social life, including the conduct of research; second, the centrality of consciousness-raising or debunking as a specific methodological tool and as a general orientation or way of seeing; third, challenging the norm of objectivity that assumes that the subject and object of research can be separated from each other and that personal and/or grounded experiences are unscientific; fourth, concern for the ethical implications of feminist research and recognition of the exploitation of women as objects of knowledge; and finally, emphasis on the empowerment of women and transformation of patriarchal social institutions through research and research results’ (Fonow and Cook, 2005: 2213).

• Lovenduski on early attempts to reinterpret political science through the lens of feminist theory/ research.

Note the links between our analysis of power/ideas and institutions as the norms and rules (informal and formal, written and unwritten) which help produce regular patterns of behaviour which benefit some and exclude others (and posts on bounded rationality, EBPM and complexity: people use simple rules to turn a complex world into manageable strategies, but to whose benefit?).

With feminist research comes a shift of focus from sex (as a primarily biological definition) and gender (as a definition based on norms and roles performed by individuals), and therefore the (ideal-type) ‘codes of masculinity and femininity’ which underpin political action and even help define which aspects of public policy are public or private. This kind of research links to box 3.3 in Understanding Public Policy (note that it relates to my discussion of Schattschneider and the privatisation/ socialisation of conflict, which he related primarily to ‘big business’).

• A good way into the study of feminist activism, and to explore the fact that ‘feminism’ sums up a wide range of activity and approaches (just like, say, ‘new institutionalism’) is to read Elizabeth Evans’ The Politics of Third Wave Feminism. You might also read Evans’ discussion of method (comparing the UK and US) with my post on comparative public policy research.
• See also Stevi Jackson on Women’s Studies, Gender Studies and Feminism
• Of course, another good way ‘in’ to a discussion is to begin with something really well written, thoughtful, and informative. For example, see bell hooks’ Feminism is for Everybody

Then see two articles which continue our theme of combining theories and insights carefully:

• Kenny’s discussion of feminist institutionalism, which seems like one of many variants of new institutionalism (e.g. this phrase could be found in many discussions of new institutionalism: ‘seemingly neutral institutional processes and practices are in fact embedded in hidden norms and values, privileging certain groups over others’ – Kenny, 2007: 95) but may involve ‘questioning the very foundations and assumptions of mainstream institutional theory’. Kenny argues that few studies of new institutionalism draw on feminist research (‘there has been little dialogue between the two fields’) and, if they were to do so, may produce very different analyses of power and ‘the political’. This point reinforces the problems I describe in combining theories when we ignore the different meanings that people attach to apparently identical concepts.
• Mackay and Meier’s concern (quoted here) that new institutionalism could be ‘an enabling framework – or an intellectual strait-jacket” for feminist scholarship’. Kenny and Mackay identify similar issues about ‘epistemological incompatibilities’ when we combine approaches such as feminist research and rational choice institutionalism.
• These approaches receive more coverage in the 2nd edition of Understanding Public Policy, and are summarised in Policy in 500 Words: Feminist Institutionalism

Here is one example of a link between ‘postcolonial’ studies and public policy:

• Munshi and Kurian’s identify the use of ‘postcolonial filters’ to reinterpret the framing of corporate social responsibility, describing ‘the old colonial strategy of reputation management among elite publics at the expense of marginalized publics’ which reflects a ‘largely Western, top-down way of doing or managing things’. In this case, we are talking about frames as structures or dominant ways to understand the world. Actors exercise power to reinforce a particular way of thinking which benefits some at the expense of others. Munshi and Kurian describe a ‘dominant, largely Western, model of economic growth and development’ which corporations seek to protect with reference to, for example, the ‘greenwashing’ of their activities to divert attention from the extent to which ‘indigenous peoples and poorer communities in a number of developing countries “are generally the victims of environmental degradation mostly caused by resource extractive operations of MNCs in the name of global development”’ (see p516).

It is also worth noting that I have, in some ways, lumped feminism and postcolonialism together when they are separate fields with different (albeit often overlapping and often complementary) traditions. See for example Emejulu’s Beyond Feminism’s White Gaze.

For more discussion, please see

Policy Analysis in 750 words: Linda Tuhiwai Smith (2012) Decolonizing Methodologies

Women don’t understand facts (and fracking)

A recent poll suggests that women are far less likely to support commercial fracking than men. For a while, the same divide was detected in relation to Scottish independence. The common factor is that you can learn a lot from people’s attitudes to gender by how they try to explain these divides.

A common starting point is that women are less likely to take risks (quick and cheap Google examples 1, 2, 3, 4, 5, 6). Then lots of people make fools of themselves by adding to the explanation: women prefer security/ a ‘safety blanket’ because their role is to nurture, earth mothers are closer to the environment, men are buccaneers, men are more ‘rational’ when they consider risk, and so on.

Or, perhaps they are misreported. I don’t know.

For example, it is now being reported in the Times that Professor Averil MacDonald (‘the new champion of the shale gas industry’) says: ‘Vast numbers of women are opposed to fracking because they “don’t understand” and follow their gut instinct rather than the facts’ (the same interpretation can be found in the Guardian, Daily Mail, and Independent).

The message that I think MacDonald was presenting is this: people are less likely to support fracking if they didn’t study particular sciences at school; and, women are less likely to have studied those sciences at school. Maybe, at its core, is a good point about challenging the barriers to women studying, and choosing a career in, certain science subjects (i.e. these findings might give us a window of opportunity to discuss such barriers).

Turned into a newspaper headline it becomes this: “Fracking? Women ‘don’t understand the science’”.

Beyond this point, there are four other things worthy of discussion:

1. You can’t separate your values from your empirical studies and scientific explanations

Some people like to present themselves as objective truth-seeking scientists, but they are kidding themselves or trying to kid other people. Scientific study is infused with our values, from what is worthy of our study, to how to study it, and what counts as good research, evidence, and explanation. Normally, you just see the end without considering all the assumptions that people make at the beginning. Or, people engage in inductive science, then struggle with post-hoc explanation (‘umm, like, women are different, eh?’).

2. You can’t separate politics from explanation

Part of the problem with gender-based conclusions is that people jump to explanations based on the too-broad category ‘women’ (or ‘men’) without considering the political implications of treating one gender as one group of people. Maybe it gets you somewhere initially, as a way of efficiently identifying correlations, but it gets you nowhere if you then try and come up with one overarching explanation for what is going on. It’s quite bad science and it’s very bad politics, contributing to unsubstantiated stereotypes. The overall correlation also distracts us from more detailed explanations based on gender and a wide range of other factors, which contributes to a further political problem: it reinforces the argument that somehow the difference between a positive or negative political choice boils down to the attitudes of women.

3. People go beyond their expertise

It is common for people to develop an undeserved general reputation for expertise, built on specific expertise in one discipline or field. It’s always worth being particularly skeptical when people with a background in natural science pronounce on social behaviour, or indeed when political scientists try to explain psychology or how gravity works. Just as you wouldn’t ask me to give a lecture on the combustion engine, don’t rely primarily on STEM professors to explain the outcomes of surveys.

4. All people combine ‘rational’ and gut-level shortcuts

If you read something like Daniel Kahneman’s Thinking Fast and Slow, you won’t find him saying that only women make gut, intuitive, or emotional decisions. We’re all at it. In fact, in my forthcoming Palgrave ‘Pivot’ book The Politics of Evidence-based Policymaking* I use that basic insight to explain policymaking: Policymakers cannot consider all evidence relevant to policy problems. They use two shortcuts: ‘rational’ ways to establish the best evidence, and ‘irrational’ decision-making, drawing on emotions and beliefs to act quickly.

*Yes, I wrote this post largely to advertise my next publication.

The ways in which feminism has ruined my life