E14: mating systems — monogamy vs promiscuity (mate-pool breadth)

A new analytic experiment on an orthogonal evolution-of-sex axis: not the
recombination RATE (E9) but the population's mating STRUCTURE. Agents on a
ring recombine with a second parent drawn from a window of breadth b
(b->0 monogamous/isolation-by-distance, b=1 promiscuous/panmictic), under
local selection, swept against NK ruggedness K.

Finding: the optimal mate-pool breadth SHRINKS as skills get more
entangled. Wide/promiscuous merging wins the champion on additive
landscapes (K<=3, b=0.6), but on rugged ones (K>=6) it prematurely
converges to a worse champion and an intermediate breadth (b~0.35) wins;
pure monogamy over-fragments. Throughout, promiscuity monotonically lifts
the population MEAN but destroys diversity and parallel exploration. The
design rule extends E9: merge widely for additive skills, keep
island-structured sub-populations for entangled ones — a merging-native
axis the panmixia-assuming literature lacks.

- src/knowledge/mating_system.py + experiment.py dispatch (kind: mating_system)
- configs/layer1/E14.yaml (breadth x K sweep, 20 reps, bitwise-reproducible)
- figures/plot_E14.py; results/E14/ (figure, README, manifest, resolved config)
- tests/test_mating_system.py (+5, 147 green); make layer1 wired
- folded into both papers (full + accessible) as the third §5 result

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

Makefile

@@ -16,7 +16,7 @@ test:              ## correctness tests + scientific-validation tests (the spine
 	uv run pytest
 
 layer1:            ## run experiments E1-E6 + the learning-kernel bridge (analytic)
-	for e in E1 E2 E3 E4 E5 E6 E7 E8 E9 E10 E11 E12 E12_nk kernel_sharpen kernel_smooth; do uv run python -m knowledge.experiment configs/layer1/$$e.yaml; done
+	for e in E1 E2 E3 E4 E5 E6 E7 E8 E9 E10 E11 E12 E12_nk E14 kernel_sharpen kernel_smooth; do uv run python -m knowledge.experiment configs/layer1/$$e.yaml; done
 
 neural:            ## run Layer 1.5 synthetic neural experiments (excludes the MNIST/torchvision tiers)
 	for c in configs/neural/*.yaml; do case "$$c" in *mnist*|*speciation_real*) ;; \