Agent skill · Code Review & Quality

popdevr-research-design

Use when defending the research design of a Population and Development Review (PDR, Wiley / Population Council) manuscript — choosing among demographic methods (life tables, decomposition, event-history, age-period-cohort, projections) and, where the question is causal, defending identification, with the population-and-development linkage made explicit. PDR judges each method on its own terms and asks what it shows about development. Strengthens the design; it does not write code.

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-research-design --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 8 KB
Bundled scripts: none
Path: Population-and-Development-Review-Skills/skills/popdevr-research-design/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 909 · +31 this week
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Research Design (popdevr-research-design) PDR accepts a wide range of approaches — empirical demography, formal demography, and conceptual synthesis — but is demanding about each, and it asks one extra question: **does the design illuminate the population-and-development linkage**, not just a demographic quantity? The design must credibly connect the argument (`popdevr-theory-building`) to evidence a broad readership will trust. This skill is method-aware: pick the section that matches your question and defend it against the strongest rival. ## When to trigger - Choosing the method that actually answers a population-and-development question - A reviewer questioned the rate construction, the identification, or the development linkage - Specifying a decomposition, event-history, age-period-cohort, or projection design - Justifying why your design adjudicates the rival account from `popdevr-literature-positioning` ## Match the method to the question - **Life tables** — for survival, life expectancy, and exposure: period vs. cohort, abridged vs. complete; multiple-decrement (cause-specific) where the development story is cause-specific. - **Decomposition** — to attribute a difference

What's inside
Steps it walks through
  1. When to trigger
  2. Match the method to the question
  3. When the question is causal (population ↔ development)
  4. The adjudication test (PDR-specific)
  5. Cross-country comparability (a recurring PDR design problem)
  6. When the contribution is a synthetic essay (no new estimate)
  7. Execution bridge (StatsPAI / Stata MCP)
  8. Anti-patterns
  9. Output format
  10. Supplementary resources
More from Awesome-Journal-Skills
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About this skill
What does the popdevr-research-design skill do?

Use when defending the research design of a Population and Development Review (PDR, Wiley / Population Council) manuscript — choosing among demographic methods (life tables, decomposition, event-history, age-period-cohort, projections) and, where the question is causal, defending identification, with the population-and-development linkage made explicit. PDR judges each method on its own terms and asks what it shows about development. Strengthens the design; it does not write code.

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-research-design --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.

Keep going