gec-data-analysis
Use when executing and reporting the analysis for a Global Environmental Change (GEC) manuscript so it survives expert, interdisciplinary review — honest uncertainty, robustness, and triangulation appropriate to quantitative, qualitative, or mixed-methods work. Guides analysis norms; it does not fabricate results.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill gec-data-analysis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Data Analysis (gec-data-analysis) GEC reviewers span disciplines and are demanding about rigor on each tradition's own terms. The analysis must deliver the test the framework (`gec-conceptual-framework`) and design (`gec-research-design`) set up, and report it so a reader in another discipline can judge it. This skill covers execution and reporting norms across methods. ## When to trigger - Running main and supporting analyses; building the results section - A reviewer asked for robustness, heterogeneity, alternative measures, or qualitative depth - Reconciling quantitative and qualitative strands in a mixed-methods paper - Making the analysis reproducible before deposit (see `gec-submission`) ## Analysis norms GEC expects 1. **Report uncertainty honestly.** Confidence/credible intervals and effect magnitudes, not just stars; the substantive meaning of the estimate for the human/policy question. 2. **Robustness that probes, not decorates.** Show specifications that could *break* the result (alternative measures, samples, estimators, fixed effects, scale of aggregation), and say what you learn. 3. **Heterogeneity with discipline.** Pre-specify subgroups where possible (e.g., by vu
- When to trigger
- Analysis norms GEC expects
- Qualitative & mixed-methods analysis
- Reproducibility while you work (not at the end)
- Anti-patterns
- What interdisciplinary GEC referees check, by strand
- Worked micro-example (illustrative — land-use change drivers)
- Referee-pushback patterns and the fix
- Calibration anchors (hedged)
- Output format
- Supplementary resources
What does the gec-data-analysis skill do?
Use when executing and reporting the analysis for a Global Environmental Change (GEC) manuscript so it survives expert, interdisciplinary review — honest uncertainty, robustness, and triangulation appropriate to quantitative, qualitative, or mixed-methods work. Guides analysis norms; it does not fabricate results.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill gec-data-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.