Why Data Literacy Matters for Reproductive Justice
In the fight for reproductive justice, stories and lived experiences are essential. They illuminate the narratives and lives impacted by abortion bans, and show care through our eyes. In showing the truth of our reproductive realities, data can also paint an important picture.
Data can reveal patterns of injustice, support advocacy initiatives, and galvanize community engagement. It can provide community organizers and organizations with hard, quantitative evidence to make our demands even stronger when we make our case to power. However, in an era flooded with information (and disinformation) where the systems in power have an incentive to limit education and access to trustworthy information, not all data is reliable. Knowing how to separate meaningful ‘signals’ and information from irrelevant or incorrect ‘noise’ is more important than ever.
Reproductive justice reaches far beyond just abortion access. Reproductive Justice is about the right to have children, to not have children, and to parent in safe and healthy environments. Achieving that vision means exposing the systems that deny those rights – and data can help make those systems even more visible. When used ethically and accurately, data spotlights oppression but when twisted, data can be used to obscure the truth, create false excuses for harmful policies, and dismiss the voices that matter most.
That’s why data literacy is not just a technical skill, it’s an issue of justice.
Reliable data helps fuel ARC-Southeast’s work to support Southerners in accessing safe and compassionate reproductive healthcare in the following ways:
- – Measure how far people are traveling for care after clinic closures and restrictive policies
- – Identify who is most affected by abortion bans
- – Pinpoint gaps in funding and service provision
- – Track how policy changes drive disparities in healthcare outcomes
- – Contribute to telling a holistic story of the barriers to healthcare access and systemic oppression that people in our communities face
These insights support advocacy, inform funding, and emphasize the magnitude of injustice. But when data is misused, manipulated, or incomplete, it can mislead the public, reinforce bias, or erase entire communities from the conversation.
Knowing What to Look For
Not all statistics tell the full story. To evaluate whether a piece of data is trustworthy, start with a few basic questions:
- – Where did it come from?
- – Who collected it? Is the source credible? What were their goals?
- – How was it gathered? Was the sample size large and representative? Were the methods of gathering data ethical and transparent?
- – What might be missing? Are key factors like race, income, or geography left out? Are certain communities underrepresented?
- – How is it presented? Are visualizations exaggerated or misleading? Is the data cherry-picked or taken out of context?
Learning to spot red flags helps prevent the spread of misinformation and makes movement building work more effective.
Dangers of Data
Data is not neutral – data reflects the values and intentions of the people collecting and communicating it. Often, the people and systems in power name the existence of ‘data’ to make inaccurate claims, spread propaganda, and perpetuate stigma. One relevant example of this is the recent “new data” that conservative policymakers have been using to question the FDA approval of the abortion pill mifepristone, claiming that ‘new data analysis’ shows a higher rate of “serious adverse effects” associated with the pill than previously studied. However, medication abortion is still safe and effective, and these claims were proven to have been manipulated based on incomplete, illegitimate data.
Conclusions are only as good as the data they are based on. The pure existence of ‘data’ is not enough to support a conclusion – if data is inaccurate, incomplete, or misleading, then the claims made based on this data must be called into question. The following (non-exhaustive) list names a couple of the most common ways that data is manipulated to make inaccurate claims:
- Cherry-picking:
- Selecting only the data points that support a claim and ignoring contradicting evidence
- Confusing correlation with causation:
- Two things happening together doesn’t mean one caused the other
- Lack of disaggregation:
- Presenting data as if it applies equally to all, ignoring factors of race, income, gender, and geography and the role of systemic oppression in disparities
- Corrupt or non-reputable sources:
- Trusting research conclusions championed by sources that either do not have adequate / relevant expertise in the field, or are directly incentivized to make certain claims
- Inflating risk:
- Exaggerating rare cases to draw conclusions about broader danger
Protecting the Movement from Misinformation
Reproductive justice advocates and people seeking healthcare regularly encounter false or misleading statistics, especially on social media. Some of this content spreads by accident (misinformation), while other content is deliberately deceptive (disinformation). Both can do real harm.
Developing data literacy helps us:
- – Fact-check viral claims before sharing them
- – Spot misleading visual tricks or false claims
- – Understand how algorithmic bias can amplify harmful narratives
- – Educate others about how data can be weaponized
It’s not enough to ignore bad data. We need to name it, understand how it is a tool of state oppression and propaganda, challenge it, and replace it with truth.
Strengthening Stories with Data
Numbers don’t move people – stories do, and stories are far more than just numbers. But when data is paired with lived experience, the result is powerful.
When used thoughtfully, data:
- – Grounds personal stories in broader patterns
- – Brings increased visibility to the targeted harm caused by oppressive policies
- – Lends credibility and urgency to our demands
- – Data is not a replacement for storytelling nor does it capture the whole story, but it is often a necessary component of holistic storytelling.
Coming Soon: A Toolkit for Justice
We are developing a new data literacy training toolkit for reproductive justice-centered community building. This toolkit will contain educational content on practical methods to help ask better questions, spot flawed data, and use good data to strengthen community engagement and strategy. With the right tools, we can make sure our truths are heard, understood, and impossible to ignore.