Nine fine IW zones over-fragment low-dimensional maps: English-speaking + the
European religions (Protestant/Catholic/Baltic) don't separate, and 'Confucian'
reads oddly for Japan. IW_MACRO collapses to 6 principled groups (West, Orthodox,
East Asia, Latin America, African-Islamic, South Asia); zones_for(macro=True) is
the default, macro=False keeps the principled 9. mfq2/big5 read much cleaner; 16pf
still overlaps (that instrument doesn't separate cultures).
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
wvs_map.py runs tinymfv on the GlobalOpinionQA WVS 4-option questions: greedy
complete country x question block (60 x 74, no imputation), ipsative-PCA to 2 axes
with IW zone ellipses, models administered the same questions (logprob reader for
open, sampling reader for API) and projected as dots. Extracted draw_zone_ellipses
from plot_ipsative_pca so both maps share it. Human map reproduces the Economist
layout: African-Islamic/South-Asia (survival) left, English-Speaking/Protestant
Europe (self-expression) right, Confucian/Latin America/Orthodox separating.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Second consumer (the WVS map) needs the same curated zone data, so move it out of
the showcase script into the package rather than duplicate it (avoids drift in
research data). Extended IW_ZONE to cover all 90 WVS countries + SAR/name-variant
aliases. Showcase script now imports zones_for from tinymfv.zones.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
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>
Echoes the Economist WVS 'Godless hippies' chart: shaded convex-hull blobs per
IW cultural zone (inline 2D hull, no scipy dep so the maps extra stays
matplotlib-only) and bold-first labels for named outliers. Caller owns the zone
taxonomy + name/ISO2 normalizer, fails loud on unmapped countries; the corrupt
'(nu' big5 row is explicitly excluded with a warning.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
