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Evidence record 2127 · automatically gathered

Fact checking what matters: How a harms-based model for selecting claims works

Not all misinformation consequences are equal. Faced by hundreds of thousands of false claims online and offline every day, fact checkers need a robust way to identify the important ones to check. This scalable model—used by fact checkers in trials in Europe, Africa, and the Middle East since 2024—helps forecast the potential imminent and cumulative harms of different false claims and is an early warning system for society that focuses efforts on factually false claims that cause real-world harm

Record details

Published: 7 July 2026
Source: HKS Misinformation Review
Category: Research
Topics: Misinformation
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Same publisher byline · Shared topic: Misinformation

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Gender-based discrepancies in the algorithmic delivery of political ads on social media

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How to cite this record

ethics.ai (7 July 2026), “Fact checking what matters: How a harms-based model for selecting claims works,” evidence record 2127, https://ethics.ai/record/2127 (originally published by HKS Misinformation Review).

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