Research Verification and Source Quality · Lesson 1

Classify claims by consequence

Course overview · 4 min reading + 12 min practice, estimated

Principles and method

Not every claim deserves the same verification effort. Identify which claims would change eligibility, outreach relevance or a commercial decision. Separate direct evidence, interpretation and speculation. Define a verification standard proportionate to the consequence. A public company announcement may support the occurrence of an event, while a candidate’s personal responsibility needs a different check. AI output is not an independent source merely because it sounds specific. Keep unsupported claims out of decision documents or label them explicitly as unresolved.

Worked example

A candidate’s public job title can support an initial research lead. A claim that they hold a mandatory current licence requires checking the relevant evidence before relying on it for eligibility.

Put it into practice

Rank five fictional claims by decision impact and assign a verification step.

Use fictional information and keep your work in your own notes.

Compare your approach: self-review guidance

Give high-consequence claims stronger checks and a clear rule against reliance while unresolved. Do not spend all available time polishing low-impact background facts while leaving essential evidence unchecked.

Download the course workbook

Sources and further reading

Original Academy teaching and fictional examples. These references provide context, not endorsement. Edition 2026.09; updated 2026-09-24.

How our learning is designed