# WP35 — Limitations (written after Phases 4–5, before the paper)

Each item names the deliverable it qualifies. "EMPIRICAL" refers to Seshat/EA/V-Dem estimates; "SIMULATED" to the
agent-based results; neither is causal.

## A. Data (EMPIRICAL)
1. **Crisis-selected outcome.** CrisisDB covers 150 of 626 polities; H2-A tests severity conditional on a recorded crisis.
2. **Undated facts.** 93.7% of Polaris social-complexity facts have no date; "pre-crisis" capacity is mostly whole-polity
   capacity. A dated-only test was not estimable.
3. **Presence codes.** Seshat K items record whether an institution existed, not its reach, quality or cost.
4. **Scale-only D.** No usable indicators of division of labour or dispersion in Polaris; occupational complexity is coded
   for 75 polities only and was excluded.
5. **Collinearity.** corr(D, K) = 0.84; P keeps 17% of the joint variance and is a residual; measurement error in either
   index leaks into P.
6. **Coder circularity.** Polaris codes and CrisisDB codes are produced by the same project from overlapping
   historiography; a polity known to have collapsed may be coded as less administratively capable.
7. **Polity boundaries.** Seshat polities are periodization decisions; "polity end" (Y2) is not an instability event.
8. **Modern K and democracy.** The six V-Dem capacity items correlate 0.75 with electoral democracy; the capacity
   interpretation competes with regime type. Expert coders rate periods knowing later events.
9. **Modern D.** Maddison population starts in 1820 for most countries; land area only from 1886; no dispersion measure.
10. **Ethnographic Atlas.** Cross-section with focal years −2000 to 1965; no outcome; EA031 is a coarse ordinal measure;
    midpoints of open categories are bounds.
11. **Crosswalks.** 39 V-Dem countries (mostly historical or micro-states) lack Maddison population and drop out.

## B. Design and inference (EMPIRICAL)
12. **No identification.** Associations only (research/identification.md). The modern negative control shows P associated
    with past events as strongly as with future events, so P marks chronically unstable countries rather than forecasting
    onsets; the Oster-adjusted coefficient crosses zero and the Cinelli–Hazlett robustness value is 0.07.
13. **Power.** Seshat binary Y1b is underpowered (MDE ≈ 0.6 SD); only the fractional severity outcome has adequate power.
14. **Few clusters.** 42 regions / 10 macro-regions; cluster-robust inference with few clusters is anti-conservative;
    alternative clusterings are reported.
15. **Baselines decide the verdict.** By the pre-registered rule, P must beat every baseline out of sample in ≥ 80% of
    folds: it fails against the D-only baseline in Seshat (leave-one-region-out) and against the K-only baseline in the
    modern panel (both schemes). The mismatch index therefore adds no predictive content beyond its own components.
16. **Placebo.** A Seshat placebo index (scale minus production infrastructure) performs about as well as P; the modern
    placebo (scale minus polyarchy) is weaker than P but still significant.
17. **Nonlinearity.** The modern hinge/spline improvement is 0.001 nats per observation and meets the 80% rule by one fold;
    it is reported as marginal, not as a threshold.
18. **Equinox-2020 replication** was pre-registered but not executed (time); it is listed as a blocked task in the final audit.

## C. Theory (PROPOSITION / CONJECTURE)
19. Theorems 1–5 concern an idealized communication system; nothing in them is tested on historical data. C1–C3 are
    conjectures; C1 (proxy monotonicity) is undermined by the collinearity and placebo results above.
20. Capacity is exogenous in the model; historically it is built in response to demand.

## D. Simulations (SIMULATED)
21. Institutions are imposed, not emergent; results describe the cost structure of imposed regimes.
22. Message and bit accounting is stylized (one-bit acknowledgements, fixed admin overhead per task); absolute numbers are
    not comparable to any historical quantity. Only within-simulation comparisons are meaningful.
23. Decoding success does not depend on the plan drawn, so distribution shocks affect cost but not success by
    construction; this is a modelling choice, not a finding.
24. Hierarchy saturation depends on the administrative-capacity ratio, a free parameter swept from 0.25 to 4; the
    "phase" boundary near ratio 1 follows from Theorem 5 and is confirmed, not discovered.
25. Shannon codes (not Huffman) are used so that the measured stale-code penalty is comparable to Theorem 3; with weakly
    concentrated plan distributions a Shannon code can be longer than raw coding (one cell), and a learning cost of 200
    bits per agent is repaid only with a large, concentrated plan space and a long horizon.

## E. Process
26. Executed autonomously by a language-model agent in one session; the PI has not yet reviewed the code or the text.
27. Reference verification relied on Crossref metadata; chapter contents of Johnson (1982) and the published tables of
    Sng (2014) were not read.