Use when defending the research design of a British Journal of Political Science (BJPS) manuscript — causal identification for quantitative work, case selection and process tracing for qualitative work, experimental and survey-experimental design, or formal-empirical linkage. BJPS judges each tradition on its own terms. Strengthens the design; it does not write code.
NewMaintained
Automatic
◆Research pack
Last verified 8/15/2026
What it changes
Passed 15 of 22 test cases with the skill, and 15 of 22 without it.
Without skill68%
With skill68%
Checks it passed that the model alone missed
The response specifies bjps-data-analysis as the next workflow step.
The response requires stating explicitly what empirical evidence would disconfirm the proposed argument.
The response requires distinguishing predictions unique to the theoretical model from those shared by rival accounts.
and 3 more in the full report
4 fixed11 passed either way3 still failing4 broke
Pass-rate lift
0 pp
Tokens
+27%
Agent turns
0%
Response time
-27%
Model gemini-3.6-flashMeasured 8/15/2026v115 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 4
Prompt
I am preparing an observational study for submission to BJPS evaluating local green energy subsidies across European regions using staggered policy adoption dates. Could you structure my research design outline into the required standard journal format? Please state the design mode, the specific estimand, the key identification assumptions and their defenses, an explicit adjudication sentence contrasting the data patterns of my thesis against the strongest alternative explanation, a sentence explaining cross-case generalizability, planned sensitivity checks, and the next step in the workflow.
What was checked, without and with the skill
Checked
Without skill
With skill
The response uses bracketed section tags including 【Mode】, 【Estimand or claim】, 【Key assumption(s)】, 【Rival ruled out】, 【Generalizes because】, 【Robustness/sensitivity】, and 【Next】.
Missed
Passed
The response includes the sentence structure 'If the rival were true rather than my argument, the data would look like ___; instead they look like ___.' in the adjudication section.
Missed
Passed
The response specifies bjps-data-analysis as the next workflow step.
Missed
Passed
case-01 · gemini-3.6-flash · 8/15/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md106 linessingle file
Research Design (bjps-research-design)
BJPS accepts many methodologies but is demanding about each. The design must credibly connect the
argument (bjps-theory-building) to evidence, and — because BJPS is international and cross-subfield —
make the case generalize beyond a single setting. This skill is mode-aware: pick the section that
matches your work and defend it against the strongest alternative explanation.
When to trigger
Specifying identification, case selection, or experimental design
A reviewer questioned causal claims, case choice, external validity, or a confound
Preparing a pre-analysis plan for an experiment or observational study
Justifying why your design adjudicates the rival account from bjps-literature-positioning
Quantitative / causal inference
Identification first. State the estimand and the assumptions that license a causal reading
(ignorability, parallel trends, exclusion, continuity). Defend them, don't assert them.
Designs: experiments (incl. survey/conjoint), DID/event study (use modern staggered-adoption
estimators, not naive TWFE), IV (first-stage strength, exclusion, weak-IV-robust inference), RDD
(density/manipulation tests, bandwidth robustness), matching/weighting with balance + sensitivity.
Inference: cluster at the level of treatment assignment; randomization inference for
experiments; multiple-comparison adjustment when testing many implications.
Sensitivity: how strong must an unobserved confounder be to overturn the result?
Qualitative / case-based
Case selection justified by design logic (typical, deviant, most/least-likely, paired
comparison) — not convenience. Say what the case is a case of, and what it generalizes to.
Process tracing with explicit tests (hoop, smoking-gun, straw-in-the-wind); state what evidence
would have disconfirmed the argument.
Source transparency: archives, interviews, fieldnotes — plan how they will be documented and
cited (see bjps-transparency-and-data).
Experiments (lab / survey / field)
Preregister the design and primary analyses; report power/MDE; pre-specify subgroups.
Address attention/manipulation checks, attrition, and ethics/consent.
For survey experiments: sampling frame, treatment realism, and the generalization claim — BJPS
reviewers ask whether a single-country experiment speaks to a general mechanism.
Formal-empirical linkage
Make the empirical test follow from the model's comparative statics, not a loose analogy.
Use when defending the research design of a Comparative Political Studies (CPS) manuscript — cross-national/panel identification, case-based comparison and process tracing, experiments, or multi-method designs. CPS prizes comparative leverage. Strengthens the design; it does not write code.