The Global Movement for Career and Research Equality: International Day of Women and Girls in Science - Part 1 (Author Q&A)

Gender equality in science requires sustained, measurable action to remove structural barriers and ensure women and girls can build, progress and lead in careers in science.

This International Day for Women and Girls in Science, we asked a selection of Kogan Page thought leaders and expert authors about the importance of encouraging and assisting women in scientific fields, particularly in neuroscience.

From the role of mentorship, sponsorship and peer networks in accelerating women’s careers in science, to how gender equity in science can impact innovation, research outcomes and organizational success, our experts share actionable insights that move beyond performative allyship. They highlight the persistent challenges and myths, such as ignoring women in scientific research, designing inaccessible or unequitable workplace environments and performance bias, that continue to hold women back across the science industries.

Explore the insights, strategies and real-world solutions from our neuroscience experts that can transform the field of science into inclusive environments where all women can thrive.

We are kicking off this Q&A series with Amy Brann, author of Make Your Brain Work.

Why does gender equity in science matter specifically for a field like neuroscience and how does this impact innovation, research outcomes and organizational success?

Amy Brann: Gender equity matters in neuroscience because brains don’t exist in a vacuum - brains develop inside bodies, contexts, cultures and systems. When the people designing studies, interpreting data and building products don’t represent the population we’re trying to serve, we systematically miss signals and amplify noise.

A timely illustration is the renewed attention on car safety testing: the move to introduce/endorse an advanced female-modelled crash test dummy is an example of what happens when we finally treat “who we test on” as a research design issue - not a political one. It’s a correction to decades of biased baselines that left women at higher injury risk in comparable crashes.

In neuroscience, the equivalent blind spots show up when we:

• Under-sample women (or analyse them as an “add-on”) and then generalize findings anyway
• Fail to account for sex-linked physiology that affects brain outcomes (e.g. hormones, pharmacokinetics, immune differences, pain presentation)
• Design “default” environments - labs, protocols, tools, workplace systems - that suit one group better than another

The business consequences are very practical:

• Innovation improves when teams have cognitive diversity and are more likely to challenge assumptions (diverse teams catch “missing variables” earlier)
• Research quality improves because datasets become more representative and findings replicate better across real populations
• Organizational performance improves because you reduce avoidable error, rework, reputational risk and product blind spots, while strengthening trust with customers and employees

This aligns directly with how I talk about performance and change: outcomes are often constrained by what people notice, how they interpret it and what the system signals is “normal.” When organizations design environments that widen attention and reduce bias, performance lifts without it being forced.

What role do mentorship, sponsorship and peer networks play in accelerating women’s careers in science and how might organizations institutionalize these supports?

Amy Brann: Mentorship is the knowledge pathway: it helps women decode hidden rules: what excellence looks like here, how decisions get made and how to build confidence through feedback loops. Sponsorship is the opportunity pathway: it is where careers accelerate: senior people using political and reputational capital to put women forward for visible work, promotions, speaking slots and stretch roles. Peer networks are the resilience pathway: they reduce isolation and create fast learning cycles (“I’m not the only one experiencing this; here’s how to navigate it”).

To institutionalize support (measurably), organizations can:

1. Set sponsorship targets, not just mentoring targets.

Example: “Each Exec sponsor will actively sponsor two women per year into a defined opportunity (P&L role, critical project, board exposure)”. Track opportunities created, not attendance.

2. Build “sponsor-able moments” into talent systems.

Make project staffing, panel selection and promotion slates require documented consideration (and challenge) of gender balance.

3. Measure the intent–action gap.

Many firms intend to support women; fewer can show what changed in behavior and outcomes. A behavioral evaluation approach that tracks movement from intent → action → impact makes support visible and improvable.

4. Protect cognitive bandwidth for development.

Mentoring/sponsorship fails when overloaded people have no time to participate meaningfully. If you want equity, you need systems that don’t silently penalize those with higher load or lower informal access.

What are the most persistent myths or biases about women in neuroscience and what evidence-based arguments can business leaders deploy to debunk them internally and externally?

Amy Brann: A few durable myths I still see (inside organizations as much as in academia) are:

1. Myth 1: “It’s a pipeline problem.”

Reality: The issue is also retention and progression. People leave when the environment repeatedly signals “you don’t belong” or when advancement depends on informal access.

Leader response: Track where attrition spikes (postdoc → faculty; manager → senior leader; specialist → principal). If women enter but don’t progress at the same rate, it’s not the pipeline - it’s the system.

2. Myth 2: “Women are less suited to high-stakes, technical or leadership roles.”

Reality: Performance is profoundly context-dependent. Threat, chronic stress and belonging uncertainty all narrow attention and working memory across humans. A brain in a threat state will not show its best thinking. If the environment triggers threat more often for one group, you get a predictable performance gap that looks like “ability,” but is actually conditions.

Leader response: Treat psychological safety, clarity and fair feedback as performance infrastructure - not “nice-to-haves.”

3. Myth 3: “Meritocracy means we shouldn’t focus on gender.”

Reality: Meritocracy only works when access to visibility, feedback, sponsorship and opportunity is evenly distributed. When it isn’t, “merit” becomes a label applied after the fact.

Leader response: Require structured evidence in promotions: defined criteria, calibrated panels and transparency about how decisions are made.

Looking ahead, what actionable commitments, whether within your organization or the broader industry, could significantly accelerate gender equity over the next decade?

Amy Brann: If the UN goal is full and equal participation, we need commitments that are concrete, tracked and linked to decision points.

Here are five that move the dial:

1. Representation targets at decision thresholds (not just overall headcount)

Example thresholds: lead author roles, grant PIs, lab heads, promotion slates, keynote panels, board/steering committees.

2. “No all-male evidence” standards in research and product validation

Seatbelt testing is the public example of what happens when we correct biased baselines. Make it policy that research designed to generalize must test appropriately across sex/gender (or explicitly state limits).

3. Sponsored stretch roles with audited allocation

Publish (internally) how stretch assignments are allocated by gender. If distribution is uneven, fix the mechanism - not the messaging.

4. Behavioral measurement, not sentiment measurement

Go beyond “people liked the program” to: what changed in behavior, what stuck, what improved. This is where intent–action tracking becomes powerful.

5. Design the environment to reduce bias load and cognitive overload

Equity is harder when people are depleted. Protect focus, reduce constant context switching and build healthier operating norms - cognition is the playing field on which opportunity is converted into performance.

We will keep this conversation on career and research equality for women and girls in science going throughout the week with key insights from our leading subject expert authors.