Make the question carry the analysis.
The research track establishes why the study matters, what is already known, where the live debate sits, and what the available data can credibly add.
1. Define the policy problem
Begin with an environmental or natural resource policy problem whose consequences, trade-offs, or distributional effects matter. Identify the decision setting, affected people and places, relevant institutions, and the mechanism that may connect policy to outcomes.
2. Read the conversation
Build a focused literature map rather than a stack of summaries. Track the questions researchers ask, the theories or mechanisms they use, the evidence they treat as persuasive, and the disagreements that remain.
Useful notes distinguish:
- established findings from open questions;
- causal claims from descriptive evidence;
- policy objectives from implementation constraints;
- substantive disagreement from differences in data, scale, or method.
3. Formulate the research question
A strong question is specific enough to guide data and method choices but consequential enough to matter beyond one dataset. It should identify the outcome or pattern of interest, the environmental or policy context, and the comparison or mechanism the analysis will study.
4. Build the analysis plan
Connect each part of the question to observable data and an explicit analytical step. Define the unit of analysis, time and geographic coverage, key variables, transformations, visual evidence, spatial methods, machine-learning role, transparent baseline, validation strategy, and important limitations.
5. Prove feasibility at research kick-off
By the Research Kick-off Report on Tuesday, October 20, move beyond an intended design: acquire a real sample, document its provenance and quality, create an initial research-motivated figure and map when relevant, and show how the proposed analysis will be validated. This checkpoint is where an infeasible scope should be narrowed.
6. Interpret in context
Results do not speak for themselves. Return to the literature and policy setting to explain what the evidence supports, where uncertainty remains, how the findings fit or challenge prior work, and what the analysis cannot establish.
The technical and research tracks should evolve together. New data constraints may narrow the question; new literature may change the model; and early results may reveal a better comparison. Document those decisions as part of the research process.