Mo's Field Notes

Issue 6

Clean Numbers, Uneven Realities

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

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Data ethics often focuses on values like transparency, fairness, and accountability, but these rarely translate into practice. Most ethical harm arises from routine decisions under constraints: measuring what’s easy, excluding inconvenient data, and reporting to meet requirements rather than reality. Ethics is an operational issue, not just a philosophical one.

In public health, this manifests in surveillance definitions that prioritize comparability over nuance, intake forms optimized for speed that erase context, and dashboards that evolve into performance metrics. These decisions are made under pressure, like when agencies must act swiftly, demonstrate control, and communicate clearly amid uncertainty. Data becomes a tool for reassurance; clean numbers signal competence, while messy data feels like failure, even if it is more truthful.

Data quality issues, such as missing values, delays, and inconsistencies, often reflect systemic issues: overburdened clinics, staff juggling multiple systems, or underserved communities. Labeling this data as “messy” can obscure the structural inequalities behind it.

Ethical practice isn't about fixing every dataset but about interpretation, understanding what data gaps signal, and resisting the urge to see incomplete data as personal failure. It’s about recognizing the limits of what numbers can convey honestly.

Harm reduction offers a useful lens: working within imperfect conditions to minimize damage. Applied to data, it means acknowledging that dashboards and reports influence decisions and perceptions, even if only provisionally. Practically, this involves slowing down when signals are weak, adding context, flagging uncertainty, and avoiding unfair comparisons, none of which are often recognized or rewarded.

Governance determines whether this ethical approach is feasible. It shapes who can question indicators, delay publication, or bear responsibility. Without clear governance, ethical considerations are treated as obstacles rather than safeguards.

Effective governance balances urgency with boundaries, allows professional judgment, protects staff who raise concerns, and prevents data from becoming blunt tools under pressure.

There is no tidy resolution here. Public health systems will continue to operate under urgency, scrutiny, and limited resources. Data will continue to be asked to stand in for certainty during uncertainty. Under these conditions, ethics is not a destination. It is a daily practice of restraint, attention, and care.

These notes are meant to be practical. They are for the moments when a report feels too confident, a dashboard feels too clean, or a deadline asks you to move faster than the data allows.

Practical resources worth saving

WHO Data Quality Review Toolkit This toolkit offers concrete ways to assess accuracy, completeness, and consistency while explicitly linking these checks to decision-making consequences. It is useful not because it is perfect, but because it forces you to ask what poor data will actually do once it leaves your hands. Access Toolkit

Tool: The Data Ethics Canvas The Open Data Institute’s data ethics canvas and governance guides are practical and scenario-based. They help teams surface risks, power dynamics, and downstream uses before harm becomes inevitable. They are especially useful in mixed teams where not everyone speaks “data” fluently. Access Tool

Data Feminism by Catherine D’Ignazio and Lauren Klein A clear articulation of how power shapes data, offering actionable principles over slogans. It complements Indigenous community data governance models, which provide a radically different foundation for ethical control. Read Now

These are field notes, not a manifesto. They are meant to be used, scribbled on, returned to when the next form, dashboard, or dataset asks you to move a little too fast past the human reality it claims to represent.

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

-Mo

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