Questions before papers
Start with a question someone needs to answer, then link the papers, evaluations, data, and models that could help.
1. The proposal
A short list to keep and revisit
Each team could maintain a few questions or research Clusters of research questions, approaches, and environments. where better evidence could change important decisions. Members could also maintain their own prioritization. The team list could record their different views.
Keep disagreement visible
Members can rank items differently, suggest alternatives, and explain their reasons. Keep those differences in the record.
Revisit the list
Someone could take responsibility for each active item and set a date to revisit it. When the team drops an item, keep a short explanation in a folded or filtered view.
How this could fit with field specialist work
Teams already discuss papers, assess priorities, vote on evaluations, and consider who could manage them. A short list of broader questions might help with some of that work, especially when choosing which research to look for next.
2. A possible structure
One compact table, with several views
A single table could hold the team shortlist, members' suggestions, ideas from existing prioritization work, and items the team has set aside.
| Question or cluster | Who might use the answer? | Why it may matter | Current disagreement | Promising next work | Owner and review |
|---|---|---|---|---|---|
| Short, decision-relevant formulation | Named types of funders, policymakers, researchers, or advocates | A concise path from better evidence to better decisions | What informed people disagree about, including minority views | Evaluation, synthesis, replication, modeling, new data, or experiment | Human owner Review every 6–12 months |
Suggested views
- Group-curated: no more than five to seven prioritized questions or clusters.
- Member suggestions: each person's nominations, judgments, and reasons.
- Prompts to consider: items drawn from our databases, funder agendas, crux mapping, or AI-assisted research.
- Deprioritized or retired: preserved with reasons and a date.
Possible lightweight judgments
- How much could an answer change real decisions?
- How uncertain or disputed is the answer?
- Is useful progress tractable in the next few years?
- Is the area receiving attention roughly proportionate to its importance?
- What evidence would most change the member's view?
3. Illustrative starting points
Some examples to discuss
These examples draw on papers The Unjournal has discussed or prioritized and on our Pivotal Questions work. What would your team add, change, or drop?
Animal welfare, markets, and attitudes
- What share of plant-based meat purchases displaces chicken, beef, or no animal product—and how does this vary with price, availability, and consumer type?
- Which inputs—growth-factor prices, cell density, bioreactor scale, capital costs, or energy use—dominate uncertainty in cultivated-meat cost projections?
- How should evaluators compare interventions that affect different species, numbers of animals, lengths of time, and severities of suffering?
Global health and development
- Which lead-exposure interventions in lower-income countries—paint regulation, cookware replacement, remediation, or nutrition—are most cost-effective, and how uncertain are current burden estimates?
- How durable are gains from group psychotherapy or cognitive behavioral therapy in lower-income settings, and when does therapy outperform or complement cash transfers?
- Do agricultural information services raise smallholder productivity at scale, and are language access, credit, or insurance the more important constraints?
AI governance and catastrophic risks
- How rapidly do returns to reinforcement-learning compute diminish relative to pretraining or inference-time compute, and what would this imply for capability timelines?
- Do current frontier-model dangerous-capability evaluations predict the capabilities that appear after deployment, tool use, or stronger elicitation?
- Will the fixed costs of compute and training concentrate frontier AI in a few firms—and would concentration make effective oversight easier or harder?
Psychology, behavioral science, and attitudes
- Which misinformation interventions produce durable changes in sharing or real-world behavior, rather than only short-lived corrections to stated beliefs?
- Which messages or experiences expand moral concern toward farmed animals, future generations, or artificial beings—and which produce backlash or polarization?
- When people use AI advice, what predicts appropriate reliance rather than over-trust, and how does AI use affect confidence, polarization, or willingness to defer to experts?
4. Human judgment and AI
How could AI help?
AI can suggest questions, find related research, and help identify disagreements. Members should decide which suggestions deserve a place on the list.
Independent input first
Ask members for their own questions before showing AI suggestions. That gives us a better chance of hearing ideas the prepared material missed.
Show where ideas came from
Label suggestions from AI or our databases with their source and date. Keep them in a separate view until members have discussed them.
Human responsibility
A person should check, rewrite, and take responsibility for each item the team adds. Preserve members' judgments and record later changes.
5. A flexible meeting format
An example meeting agenda
Here's one possible schedule. Teams could spend most of a meeting on papers awaiting decisions, or give more time to broader research questions when that seems useful.
0–5 min
Updates and agenda choices
Agree on where the meeting's attention is most useful today.
5–25 min
Actual research papers
Discuss promising papers, prioritization assessments, final votes, and possible evaluation managers.
25–35 min
Process questions
Discuss delays or gaps in finding, selecting, and evaluating research.
35–50 min
Pivotal questions and directions
Discuss which questions to add, revise, or set aside.
50–60 min
Decisions and ownership
Record next steps, owners, unresolved disagreements, and what should return at a later meeting.
Optional +20
Members' research and research use
An informal space for people who can stay longer to discuss their own work, how research is being used, possible collaborations, or useful feedback.
Adjust the timings and sections to suit the meeting. The extra 20 minutes are optional for anyone who wants to stay.
6. Questions for discussion
What should we keep, change, or drop?
About the underlying idea
- Would keeping this list help your team choose useful research?
- Should there be a short group-curated list, individual lists, or both?
- Who might use it, and what would help them?
- How often should it be revisited?
About the meeting and workflow
- How much meeting time, if any, should this receive?
- Should independent member suggestions come before prepared database and AI prompts?
- What should we know about a question before adding it?
- Would anyone be willing to help pilot or maintain this for one group?
A possible small pilot
We could try this with two or three active teams. Ask members for their own suggestions, then bring in existing Unjournal prioritization material. Aim for at most five to seven items per team and check after one or two meetings whether the list helped.
Why start with a hosted page?
A page is easy to share and comment on while we work out whether the idea is useful. If teams want to keep their lists, we could put them in Coda or connect them to the existing research-prioritization database.