From governance-journal-skills
Executes and reports cross-national governance analysis for Governance journal manuscripts, covering inference, clustering, robustness, multi-method triangulation, measurement validity, and small-N comparative samples.
How this skill is triggered — by the user, by Claude, or both
Slash command
/governance-journal-skills:govern-data-analysisThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
*Governance* reviewers are comparative-method sophisticated and the journal requires a **Data
Governance reviewers are comparative-method sophisticated and the journal requires a Data
Availability Statement describing whether and how replication materials can be accessed. Analyze as if
a competent reader will follow your inference across countries — because they will. This skill covers
execution and reporting norms; design decisions live in govern-research-design.
Institutional outcomes are confounded by hard-to-measure history and capacity. Report how strong an unobserved confounder would have to be to overturn the result (e.g., Oster's δ/bounds, sensemakr-style robustness values, E-values). State the benchmark covariate you compare against.
【Main estimate】magnitude + interval + cross-national substantive meaning
【Inference】clustering level; few-cluster correction if N small
【Measurement】index + version; result holds across alternative measures? [Y/N]
【Robustness】specs that could break it → what held
【Sensitivity】strength of unobserved confounder needed to overturn (δ / RV / E-value)
【Pre-specified vs exploratory】clearly separated?
【Reproducible】master script + seeds + pinned index versions? [Y/N]
【Next】govern-tables-figures
../../resources/external_tools.md — estimation, few-cluster inference, synthetic control, QCA, and sensitivity packages../../resources/official-source-map.md — Data Availability Statement and pre-analysis-plan policynpx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin governance-journal-skillsGuides analysis execution and reporting for World Politics manuscripts, emphasizing honest uncertainty, robustness checks, cross-national inference, measurement validation, and reproducibility for Dataverse replication.
Runs and reports analyses for Comparative Political Studies manuscripts: estimation, uncertainty, robustness, and multi-method triangulation on comparative data.
Guides analysis reporting for BJPS manuscripts: honest uncertainty, robustness checks, heterogeneity, and reproducibility. Use for main and supplementary analyses.