worlddev-robustness
GitHub用于World Development稿件的稳健性与可信度检查。按威胁类型组织定量、定性及混合方法验证，涵盖规范依赖、测量误差、三角验证等，避免机械罗列附录表格，确保回应审稿人关切。
Trigger Scenarios
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill worlddev-robustness -g -y
SKILL.md
Frontmatter
{
"name": "worlddev-robustness",
"description": "Use when results may be sensitive — to specification, sample, measurement, or inference for quantitative work, or to interpretation and triangulation for qualitative work — in a World Development (WD) manuscript. Organizes checks by threat; it does not invent evidence or citations."
}
Robustness & Trustworthiness (worlddev-robustness)
When to trigger
- The headline result moves under plausible alternative specifications
- A referee suspects the finding is driven by one region, one wave, or one measurement choice
- Development data are messy (recall error, measurement in informal economies, attrition) and this is unaddressed
- A qualitative finding rests on a few vivid quotes with no account of disconfirming evidence
- The robustness section is a mechanical dump of appendix tables organized by table, not by threat
Organize by threat, not by table
The single biggest WD robustness failure is a wall of appendix tables with no logic. A WD referee — often from a different discipline than the author — wants to see that you identified the threats to your specific claim and addressed each one. Structure the robustness work as a short list of named threats, each with the check that retires it and a one-line verdict. For each threat: what would break the claim, what test isolates it, what the test shows.
Quantitative threat map
| Threat | Check |
|---|---|
| Specification dependence | Add/drop controls in a disciplined sequence (Oster-style δ/bounds); specification curve if the literature is unsettled |
| Sample / outlier dependence | Drop influential units, regions, or waves; leave-one-out; trim |
| Measurement error (acute in development data) | Alternative measures; validation against an independent source; bounds |
| Inference fragility | Cluster at the right level; few-cluster wild bootstrap; spatial (Conley) SEs; randomization inference for RCTs |
| Selection / attrition | Lee bounds; selection models; characterize who exits |
| Multiple hypotheses | Romano–Wolf or sharpened q-values across the family of outcomes |
| Mechanism vs. confound | Show the proposed mechanism's footprint; rule out the leading alternative explicitly |
Run the checks the threat justifies — not the full menu. A paper that reports forty robustness tables but never addresses the obvious confound has gold-plated the wrong corner.
Qualitative trustworthiness map
Robustness for qualitative WD work is trustworthiness, and it is judged, not waived:
- Triangulation: corroborate key claims across data sources or informant types.
- Negative-case analysis: actively present and account for evidence that cuts against the argument — its absence is a red flag.
- Member checking / saturation: where appropriate, evidence that interpretations were checked and categories stabilized.
- Audit trail: enough on coding and analysis that another researcher could follow the inference.
- Reflexivity: acknowledge how the researcher's position shaped access and interpretation.
Mixed-methods
Show the strands converge or that divergence is informative. When quant and qual disagree, that tension is data — explain it rather than hiding the weaker strand.
Development-specific traps WD referees catch
- Treating survey measures from informal/subsistence settings as if measured with the precision of administrative data
- Ignoring spatial autocorrelation in geographically clustered development data
- Pooling heterogeneous countries/regions and reporting one average that masks the policy-relevant variation
- Generalizing from one program/site without scope conditions
- Reporting the robust result but not the fragile one a skeptic would run
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. World Development is multidisciplinary development studies; the chain serves its quantitative-causal lane, mixed-methods work uses its own standards.
- Many outcomes / specifications:
romano_wolf(step-down FWER) orbenjamini_hochberg. - OVB sensitivity:
oster_delta/sensemakr. - Inference:
wild_cluster_bootstrap(few clusters),twoway_cluster/conley. - Re-fit off one handle:
audit_result(result_id)lists missing checks + the exactsuggest_functionfor each. - Exhibits:
etable/did_summary_to_latexfrom the handle — no retyped numbers.
Decisive checks in the body, exhaustive battery in the appendix. JF execution walkthrough.
Checklist
- Robustness organized by named threat, each with check + one-line verdict
- Inference matched to the design (clustering level, few-cluster, spatial, randomization)
- Measurement error addressed where development data warrant it
- The leading alternative explanation is ruled out, not merely mentioned
- Qual: triangulation + negative cases + audit trail present
- Heterogeneity that matters for policy is shown, not averaged away
- No significance asterisks; effect sizes and uncertainty reported in real units
Anti-patterns
- A robustness appendix sorted by table number with no threat logic
- Forty checks for a non-threat, zero for the obvious confound
- Burying a fragile headline result and reporting only the survivor specifications
- Qualitative work that quotes only confirming voices and never the disconfirming ones
- Hiding quant/qual divergence in a mixed paper instead of explaining it
Output format
【Journal】World Development (WD)
【Skill】worlddev-robustness
【Verdict】robust / fragile / mixed
【Threats addressed】[threat → check → verdict] for each
【Leading alternative】how it is ruled out
【Qual trustworthiness】triangulation / negative cases / audit trail (if applicable)
【Policy-relevant heterogeneity】shown / hidden
【Source status】verified URL / 待核实 / not asserted
【Next skill】worlddev-tables-figures
Version History
- 1839142 Current 2026-07-05 14:32
