feat: dedicated practitioner_next_steps() handler for ChangesInChanges/QDiD

CHANGELOG.md

@@ -131,6 +131,22 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   Cross-language covariate parity is layered - conventions bit-exact given R
   inputs, LP solver proven optimal per tau, end-to-end results gated at
   documented exact-tie selection bounds (see the REGISTRY Deviation note).
+- **Dedicated `practitioner_next_steps()` handler for ChangesInChanges / QDiD.**
+  `ChangesInChangesResults` no longer falls through to the generic handler
+  (which recommends mean parallel-trends checks and HonestDiD - neither fits a
+  distributional 2x2 estimator with no event-study effects). The new handler
+  branches on the shared results class's `estimator` field and covariate
+  status: distributional identification screen (monotone-model /
+  time-invariance assumptions, not mean parallel trends), interior-range
+  guidance (unconditional CiC), conditional-envelope support guidance
+  (covariate CiC), the paper's CiC-over-QDiD recommendation (QDiD fits),
+  two-pre-period distributional placebo, sup-t uniform-band reading of the
+  QTE profile, with/without-covariates comparison, and cross-estimator
+  anchoring against mean DiD. Adds bootstrap-health warnings the shared
+  NaN-ATT check cannot see (inference disabled at `n_bootstrap=0`; replicate
+  failure above the 5% fit-time materiality threshold) and per-instance
+  display names ("ChangesInChanges (CiC)" vs "QDiD") for the shared results
+  class. Guidance-only change - no estimation or inference behavior touched.
 
 ### Changed
 - `diff_diff/guides/llms-autonomous.txt` no longer lists regression discontinuity as

TODO.md

@@ -50,7 +50,6 @@ generic sparse-FE, QR+SVD rank-detection redundancy, `check_finite` bypass — m
 |-------|----------|--------|--------|----------|
 | ChangesInChanges/QDiD tutorial notebook (2x2 distributional walkthrough: QTE grid, interior range, uniform bands, CiC-vs-QDiD comparison) - deferred from the implementation PR as a documented decision. | `docs/tutorials/` | #682 | Mid | Low |
 | Tighten the mypy suppressions that back the enforced-zero posture: burn down `prep_dgp`'s per-module `[index]` override (needs a None-vs-array restructure that preserves the seeded RNG stream), and evaluate re-enabling the globally disabled codes (`arg-type`, `return-value`, `var-annotated`, `assignment`) one at a time — `assignment` alone hid several real annotation drifts found during the 2026-07 triage. | `pyproject.toml` `[tool.mypy]`, `diff_diff/prep_dgp.py` | lint-CI | Mid | Low |
-| `practitioner_next_steps()` dedicated handler for `ChangesInChangesResults` (currently falls back to `_handle_generic`, which is safe; a dedicated handler is the established full-integration step, cf. HAD Phase 5). | `diff_diff/practitioner.py` | #682 | Quick | Low |
 | Align the four legacy dataset loaders (`load_card_krueger`, `load_castle_doctrine`, `load_divorce_laws`, `load_mpdta`) with the loud-fallback pattern of `load_prop99`/`load_walmart`: `UserWarning` + `df.attrs["source"]` marker on synthetic fallback (currently silent), plus optional checksum pinning for the CSV downloads. **Upgraded to a live defect 2026-07-13: the `causaldata/causal_datasets` GitHub repo backing castle/card_krueger/divorce is dead (404), so those loaders silently serve synthetic data everywhere - needs loud fallback + replacement sources.** | `diff_diff/datasets.py` | LWDiD precursor | Quick | Medium |
 | Real-data CI canary for dataset-backed replication tests: `test_methodology_lwdid.py`'s Prop 99 / Walmart goldens skip (visibly) when loaders fall back to synthetic; add a lane or canary asserting `df.attrs["source"] == "lwdid_ssc_ancillary"` in CI so network regressions cannot silently de-gate the replication tests. Pairs with the loader-fallback repair row above. | `tests/test_methodology_lwdid.py`, `.github/workflows/` | LWDiD validation suite | Quick | Low |