Individual skill

asr-data-analysis

Use when executing and reporting the analysis for an American Sociological Review (ASR) manuscript so it survives expert masked review — honest uncertainty, robustness, and evidence handling appropriate to quantitative, demographic, comparative-historical, or computational sociology. Guides analysis norms; it does not fabricate results.

American-Sociological-Review-Skills/skills/asr-data-analysis/SKILL.md

Read pinned source

Source commit 932eb23331721b16e967c59f093781be1928b498

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
Yes
Repository scan complete
No
Skill scan complete
Yes
Observed behavior
Network or broad shell
Last checked
Nov 9, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
1,405
Repository last updated
Sep 27, 2026
License
MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# Data Analysis (asr-data-analysis)

ASR reviewers are methodologically demanding across very different traditions. Whether your evidence
is regression coefficients, life tables, archival sequences, or coded fieldnotes, the analysis must be
transparent, well-documented, and reproducible to the extent your data allow. Design decisions live in
`asr-research-design`.

## When to trigger

- Running main and supporting analyses; building the results/findings section
- A reviewer asked for robustness, heterogeneity, alternative specifications, or more evidence
- Documenting how qualitative claims are grounded in the data
- Making the analysis reproducible before sharing materials
Back to top