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Manuscript revision and pending experiment work, snapshot before restructuring

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Clarity pass over the main text (36-item audit), Discussion rewrite and cut,
acknowledgements, Souly et al. as ref 62, lettered SI panels, model section
moved under Results; plus the untracked curriculum/society/compose/smol
configs, runners, figures, stats and tests that the SI already cites.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y64o8FKP7rCuXzC48pxpMm
This commit is contained in:
Giorgio Gilestro 2026-09-13 16:54:09 +01:00
parent e4804adabc
commit 84124de143
450 changed files with 52813 additions and 1202 deletions
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19
figures/plot_E4.py
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@ -16,7 +16,7 @@ import matplotlib.pyplot as plt
import numpy as np
sys.path.insert(0, str(Path(__file__).parent))
from _figlib import load_bundle, savefig # noqa: E402
from _figlib import load_bundle, savefig, letter_axes # noqa: E402
def U_closed(K_T, rho, q):
@ -37,9 +37,9 @@ def main(results_dir: str = "results/E4") -> None:
ax = axes[0]
for K, c in zip(K_Ts, colors):
sub = g0[g0["K_T"] == K].groupby("rho")["union_coverage"].mean()
ax.plot(sub.index, sub.values, "o", color=c, label=f"K_T={K}")
ax.plot(sub.index, sub.values, "o", color=c, label=f"$K_T$={K}")
ax.plot(rhos, [U_closed(K, r, q) for r in rhos], "-", color=c, lw=1)
ax.set(xlabel=r"teacher correlation $\rho$", ylabel="union tail coverage",
ax.set(xlabel=r"parent correlation $\rho$", ylabel="union tail coverage",
title=r"Supply: union matches $U(K_T,\rho,q)$")
ax.legend(frameon=False, fontsize=8)
@ -48,11 +48,11 @@ def main(results_dir: str = "results/E4") -> None:
for K, c in zip(K_Ts, colors):
sub = g0[g0["K_T"] == K].groupby("rho")
ax.plot(sub["surviving_max"].mean().index, sub["surviving_max"].mean().values,
"-o", color=c, label=f"K_T={K}", ms=4)
"-o", color=c, label=f"$K_T$={K}", ms=4)
ax.plot(sub["surviving_mean"].mean().index, sub["surviving_mean"].mean().values,
"--", color=c, lw=1, alpha=0.7)
ax.set(xlabel=r"teacher correlation $\rho$", ylabel="surviving tail coverage",
title="Realised: max-merge (solid) rises;\nmean-distill (dashed) stays flat")
ax.set(xlabel=r"parent correlation $\rho$", ylabel="surviving tail coverage",
title="Realised: max-merge (solid) rises;\nmean-mixture (dashed) stays flat")
ax.legend(frameon=False, fontsize=8)
# Panel C: surviving vs K_T at rho=0, both operators — the recombination benefit
@ -61,17 +61,16 @@ def main(results_dir: str = "results/E4") -> None:
mx = r0.groupby("K_T")["surviving_max"].agg(["mean", "sem"])
mn = r0.groupby("K_T")["surviving_mean"].agg(["mean", "sem"])
ax.errorbar(mx.index, mx["mean"], yerr=1.96 * mx["sem"], fmt="-o",
color="#1f77b4", capsize=3, label="max-merge (M2N2-style)")
color="#1f77b4", capsize=3, label="max-merge (union-preserving)")
ax.errorbar(mn.index, mn["mean"], yerr=1.96 * mn["sem"], fmt="--s",
color="#d62728", capsize=3, label="mean-mixture distillation")
ax.set(xlabel="number of teachers $K_T$", ylabel="surviving tail coverage",
ax.set(xlabel="number of parents $K_T$", ylabel="surviving tail coverage",
title=r"Benefit needs a union-preserving merge ($\rho=0$)",
xticks=K_Ts)
ax.legend(frameon=False, fontsize=9)
fig.suptitle("E4 — recombination supplies the tail; only a union-preserving merge "
"realises it in the pupil", y=1.03)
fig.tight_layout()
letter_axes(fig)
savefig(fig, results_dir, "E4")