Leadership, Power, and Public Health Policy

Welcome back to the fifth issue of Mo's Field Notes.

If you complete any form, you may be asked about your occupation, income, household size, education, health insurance, and commute time. But it doesn’t ask who manages appointments, tracks medications, handles interruptions, remembers birthdays, notices when the fridge is empty, or adjusts work hours if family care falls apart. The form is clean, simple, and neutral, focusing on what organizations can count.

But what it leaves out isn’t accidental. In public health, silence doesn’t make noise. It hides in standard categories, averages that hide differences, and datasets that focus on paid work, official systems, and apparent results. Gender appears as a basic demographic detail, but the power dynamics tied to gender are usually in the background. We count people, but rarely the burdens they carry.

This isn’t because people or institutions don’t know. Institutions are built to notice what keeps them going. Much of what supports families, workplaces, and economies, such as caring for others, providing emotional support, coordinating activities, and managing risks, is informal, feminized work that’s not easily measured. These activities keep systems running smoothly but stay invisible. They’re often seen as natural, private, or personal rather than as essential infrastructure.

When data doesn’t capture these hidden efforts, policies tend to overlook them. Responsibility shifts onto individuals. Women are told to manage stress better, to “lean in” or step back, or to find a better balance. Meanwhile, these systems still rely quietly on unpaid work, continuing efficiently and proudly, based on data that doesn’t reflect this reality.

This pattern happens everywhere. In health research, studies have historically focused on men, treating women’s bodies as a complication. Economic measures track productivity but ignore the behind-the-scenes work that makes it possible. Workplace metrics often assume someone else handles everyday life needs. Even progressive organizations often look at gender equality only by who’s in top leadership, ignoring conditions at the base.

The illusion persists: we think systems are fair because spreadsheets look neutral; gaps seem smaller because averages move; progress appears real because visible signs improve. But underneath, burdens barely change.

This isn’t about bad intentions. Most people within these systems are limited by what their tools show, what institutions reward, and what’s manageable on paper. Data isn’t inherently biased or intentionally misleading; it reflects choices about what’s considered important, what’s visible, and what can be ignored.

Feminist scholars and data experts have warned about this for decades. Knowledge is influenced by where and how it’s gathered. Measurement is political. Ignoring certain work and experiences gives power over those who are invisible, making their burdens easier to overlook and their risks higher.

Public health recognizes this in theory by discussing social factors, systemic influences, and underlying causes. But gendered work often remains implied rather than directly measured. It’s assumed to be part of family roles, caregiving norms, or stories of resilience, without being examined as a finite resource that can be drained.

As March comes and institutions celebrate women’s strength and leadership on International Women’s Day, it’s worth asking what that strength is actually making up for. Celebrating without truly recognizing these burdens can feel meaningless. Being visible doesn’t change the fact that resources and support often aren’t redistributed. Without that change, progress stays superficial.

Below are a few readings and resources that address the question of who and what go uncounted, and why.

Readings & Resources

I am not offering solutions here. The point is not to fix absence with a new dashboard or a better checkbox. The point is to notice what keeps slipping past our instruments, and to resist the comfort of thinking that what we can see is all there is.

Some gaps persist because they serve the system as it is. Naming them does not close them. However, it does make them harder to ignore.

Thank you for reading. I hope you found this issue helpful. See you in the next issue!

-Mo

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