cscw-experiments
Use when designing or auditing the empirical work behind a CSCW paper — interview and ethnographic rigor, trace and log analysis, surveys, deployments, and mixed methods — matching each method's own validity standard and the ethics of studying real communities.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cscw-experiments --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.
# CSCW Empirical Work "Experiments" is the wrong word for most CSCW evidence, and that is the point. The venue is deliberately methods-pluralist: interview studies, ethnography, large-scale trace analysis, surveys, field deployments, controlled experiments, and mixed designs all publish here — **each judged by its own tradition's standard of rigor, not by a quantitative default.** The commonest reviewing disaster is a paper that borrows a method without its discipline. ## Rigor, by method family | Method | What rigor means here | What reviewers flag | | --- | --- | --- | | Interviews | Purposeful sampling with a rationale; saturation or a defended stopping rule; a described analysis process (coding approach, memoing, disagreement handling) | "We interviewed 12 people and themes emerged" with no analytic trail | | Ethnography / field observation | Duration and depth of engagement; researcher's relationship to the setting; thick description that earns the interpretation | Drive-by observation labeled ethnography | | Trace / log analysis | Construct validity (does the log field measure the practice claimed?); an identification strategy for any causal wording; robustness to platform qu
- Rigor, by method family
- Group-level design decisions
- Ethics as design, not paperwork
- Evidence-plan skeleton
What does the cscw-experiments skill do?
Use when designing or auditing the empirical work behind a CSCW paper — interview and ethnographic rigor, trace and log analysis, surveys, deployments, and mixed methods — matching each method's own validity standard and the ethics of studying real communities.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cscw-experiments --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 984 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.