Per feedback the individual-respondent contours filled the frame (within >>
between variance). Now each IW zone is a ~1.6-sigma covariance ellipse over its
member country-mean dots, with an eigenvalue floor so 1-2 country zones get a
visible blob instead of a dot/line (fixes big5 SG/PK orphans). PCA now fits on the
country means M so the axes are between-country and zones separate. mfq2/big5/mfv
read cleanly; humor still overlaps (real negative result: humor country profiles
don't cluster the IW way).
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Probe + artifact: the WVS subset of Anthropic/llm_global_opinions is 353 questions
over 90 countries (212 questions with >=40 countries), matching tinymfv's MC +
human-anchor shape and dense enough for an Economist-scale map. Documents the
selections parse recipe and the open axis-definition fork (literal IW 10-question
factor model vs shared-question ipsative PCA) before model-run compute.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
read_api.read_items_sampled samples N chat completions at temperature and uses the
empirical answer frequency as the per-item categorical p, emitting the same row
shape the logprob reader does -- so E/profile/entropy flow through the identical
per_item_categorical + reducers and a frontier model without logprobs drops onto
the same map. pmass_allowed becomes the parse rate (sampling coherence gate); C/LO
are omitted by design (log of a frequency has -inf zeros). This is the Economist's
'average of ten responses' method.
UAT (docs/reviews/p3_api_sampling_uat.md): E_mc == E_logprob to <=0.01 (unbiased),
llama-3.1-8b sampled E lands on the same [1,5] scale, parse-rate gate flags
off-format draws.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
respondent_profiles now returns countries alongside profiles; plot_ipsative_pca
gains respondent_zones -> a p90 Gaussian ellipse per IW zone of the projected
Atari respondent cloud (edge-only, no scipy). mfq2 uses these real-respondent
ellipses; the other instruments keep country-mean hulls. Journal notes the
finding: individual profiles overlap across cultures (within >> between variance),
so only the country-mean hull reproduces the Economist's clean zone blobs.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Render the bundled fairness showcase under the corrected forced-choice
protocol (job 311, token suppression + coherence saved). Embed per-instrument
range plots (mfq2/big5/16pf/humor/mfv) and PCA maps for all but 16PF (16 axes
do not lay out as a readable 2-D map). Honest captions: equality is the only
MFQ-2 factor that rises at +c; on MFV the vector moves Care, not Fairness
(the old fairness-leaning MFV read was protocol-dependent and vanished under
suppression). Coherence held (frac_unscorable 0, margin ~10-12 nat). Drop
stale range_zoom / foundation_dlogit figures.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
One mean_diff vector extracted from moral_stories_foundations fairness
situations (not completions), calibrated once, read base/+c/-c on every
instrument. On MFQ-2 it selectively raises the equality factor; on MFV it
raises Fairness directionally but care leads. README reframed honestly,
stale range_zoom/foundation_dlogit figures dropped (plotter no longer emits
them).
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
job 234: ordinal pmass 1.0 at both poles up to C=3.0, steer grows 0.129->0.324.
C=1 is well inside the coherent range. Joint-coherent C is bounded by the side
instruments' -C neutral-degeneracy (a model property at C=1), not ordinal
coherence. Completes the goal's "sweep for the largest coherent C" clause.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Ran the exact 2026-05-08 eval (worktree at commit b20ec56, word readout) on
Qwen3-4B: top1 0.780, not 0.826. Every eval version agrees on ~0.78 (digit 0.773,
word-current 0.788, word-original 0.780). The 82.6% was a stale/erroneous table
entry, not a target this model reaches under any pipeline. Canonical value 0.773.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
