test: add Tutorial 24 drift guard (staggered-vs-collapsed power claims)

TODO.md

@@ -172,7 +172,6 @@ Deferred items from PR reviews that were not addressed before merge.
 
 | Issue | Location | PR | Priority |
 |-------|----------|----|----------|
-| Drift test for tutorial 24 qualitative power claims (monotonic dilution fast→slow; CS-vs-2×2 MDE crossover/near-parity at slow rollout) — pins the prose against estimator-default/simulation drift | `docs/tutorials/24_staggered_vs_collapsed_power.ipynb` | staggered-analysis-2x2 | Low |
 | ImputationDiD covariate-path variance lacks dedicated R `didimputation` parity / hand-calc. The PR-B FE-design correction (keep all unit dummies) affects the covariate projection too, but only the no-covariate staggered panel is R-parity'd (the covariate path shares the same validated projection code and passes the full suite). Add a covariate (time-varying X) R golden asserting overall/event-study SE parity, or a small dense-design hand-calc for the covariate projection. | `tests/test_methodology_imputation.py`, `benchmarks/R/generate_didimputation_golden.R` | imputation-validation follow-up | Low |
 | Port the CI `<notebook-prose>` extraction into the reviewer-eval harness so `docs/tutorials/*.ipynb` cases (currently guarded out of `verify-corpus`/`run`) can be reviewed with CI-equivalent context | `tools/reviewer-eval/adapters/ci_prompt.py` | local-review | Low |
 | **Premise corrected — no CI impact (verified 2026-06-07).** The "slow CI" motivation does not hold: no CI workflow installs R (no `setup-r` / `r-lib/actions` / `fixest` / `r-base` install anywhere in `.github/workflows/`), so every R-parity test skips in CI behind a per-file availability gate (`fixest_available` in twfe, `_check_r_contdid()` in continuous_did, `require_r` / `r_available` in `conftest.py`, etc.) — consolidating `Rscript` spawns yields zero CI speedup. The originally-cited file already session-caches its R fits: `test_methodology_twfe.py` exposes `r_twfe_results` / `r_twfe_results_with_covariate` as `scope="session"` fixtures, so each R model runs once per session, not once per test. The only residual is a LOCAL-dev micro-optimization for developers who have R installed: `test_methodology_continuous_did.py` (the `_run_r_contdid` helper plus three standalone inline `Rscript` calls) and `test_methodology_callaway.py` (`_run_r_estimation` called inline in three test methods, plus `_get_r_mpdta_and_results` re-run by the MPDTA R-parity tests) re-spawn `library(...)` per call with no session-level result cache. Applying the twfe session-fixture pattern there would speed local R-parity runs only. Low value; retained as a local-dev note. | `tests/test_methodology_continuous_did.py`, `tests/test_methodology_callaway.py` | #139 | Low |