The Policy Feedback Loop: How Bad Data Keeps Bad Policy Alive
- Alex Andrews
- 3 minutes ago
- 3 min read
What Gets Measured Becomes “Success”
By the time we get here, the pattern is hard to ignore. Policies that don’t improve safety don’t just persist - they expand. Not because they’re working, but because the systems evaluating them aren’t designed to measure failure.
In January’s Follow the Money series, we looked closely at the numbers used to justify anti-trafficking efforts: arrests, charges, “rescues,” and operations conducted. These metrics are presented as proof of impact. They appear concrete, countable, and objective. But what they actually measure is activity - not outcomes. They tell us what systems are doing, not whether those actions are improving people’s lives.
Who Controls the Narrative Controls the Outcome
By March, in The Pink Patriarchy, we saw how these numbers gain meaning. Data doesn’t exist in a vacuum - it’s interpreted, framed, and amplified.
Certain voices are elevated as experts.
Certain stories are repeated until they become shorthand for reality. And other experiences - especially those that contradict the dominant narrative - are dismissed, minimized, or excluded entirely.
This is how bad data becomes powerful. Not because it’s accurate, but because it’s useful.
How the Loop Sustains Itself
Once you start tracing it, the cycle becomes clear - and difficult to interrupt.
Arrests are framed as rescues
Those numbers are used to justify funding
Funding incentivizes more enforcement activity
Media amplifies the narrative as proof of success
And then it starts again.
Each step reinforces the next. Each layer adds legitimacy. And nowhere in that cycle is there a requirement to measure harm, long-term outcomes, or the lived experiences of the people most affected.
Who Gets Left Out of the Data
The most striking gap in this system isn’t just what gets counted - it’s who gets excluded. The people navigating these policies in real time are rarely the ones shaping the data used to evaluate them. Their outcomes - housing instability, loss of income, increased risk, barriers to healthcare - are difficult to quantify, and even easier to ignore.
So they are.
What gets counted instead are the metrics that are easiest to produce and most useful for maintaining the system itself.
The Question No One Is Asking
If your data never measures harm, how would you know your policy is failing?
It’s a simple question, but it cuts directly through the structure. Because once you ask it, the gaps become impossible to ignore. The absence of certain metrics isn’t accidental - it’s functional. It allows systems to continue operating without accountability.
Why These Policies Don’t Disappear
Policies don’t survive because they work. They survive because the system measuring them isn’t designed to see the damage.
As long as success is defined by activity rather than outcomes, by visibility rather than safety, by narrative rather than lived experience, the same patterns will continue. The same funding streams will remain intact.
The same harms will be reproduced - and reframed as progress.
If we want different outcomes, we have to start by asking different questions. Not how many arrests were made, but what changed for the people involved. Not how many operations were conducted, but whether risk decreased. Not whether a policy sounds right, but whether it works in practice.
Because until we measure what actually matters, we will keep funding what doesn’t.
