The zone/dot-colour/label-set policy was duplicated inline in plot_value_map and
plot_ipsative_pca -- subtle plotting policy that would silently diverge between
the two figures. One helper now, so they can't drift. Also drop the broad
except-Exception textalloc fallbacks (textalloc is a hard maps dep; the fallback
hid broken layouts) and a dead textalloc import in plot_ipsative_pca.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Hatchling rejects a direct git reference in an optional-dependency unless this
flag is set; without it uv could not build tiny-mfv and every 'uv run' failed.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Russian validation of the Knutson/Kruepke Realistic Moral Vignettes
(norm violation / social affect / intention), sent by the authors.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Replace the hand-rolled OpenAI client with openrouter_wrapper.openrouter_request,
which backs off on 429/provider/upstream/malformed errors (a rate-limited model no
longer kills the run), so retry logic doesn't diverge from the rest of the stack.
read_items_sampled now carries the raw sample texts; wvs_map appends every response
to wvs_iw_responses.jsonl (audit trail -- these API calls cost money).
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Economist encoding: every model is one bold red dot (bigger than the grey society
dots), told apart by its label, with a two-entry colour legend (AI models / N
societies). Title and caption are now off by default -- the README carries the
headline + sources in a nicer voice than baked figure jargon. WVS map passes
neither.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
plot_ordinal now saves map_value.{png,svg} (societies + AI base/steered projected
onto the instrument's two named value axes) next to map_pca_ipsative. Untested
end-to-end (needs a run_allinstr_showcase profile set); the shared plot_value_map
renderer it calls is verified on human-only renders.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
The WVS map's ~70 lines of pole-signpost/hull/textalloc rendering were a copy of
what plot_value_map now does -- call the shared renderer instead (WVS + instruments
one code path). big5 value-axis poles named at both ends (Reserved<->Exploratory,
Volatile<->Stable) so every value map reads as a bipolar contrast, not a unipolar
low<->high.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
The interpretable alternative to the blind ipsative PCA map: two NAMED axes with
four pole signposts through the human-median crosshair, Economist-style zone hulls,
textalloc labels, no compass/minimap. Shared renderer used by every instrument (and
next the WVS map).
value_axes.py defines the per-instrument groupings from the literature:
- mfq2/mfv: Individualizing (care/fairness) <-> Binding (loyalty/authority/purity),
MFT; 2nd axis = equality<->proportionality (mfq2) / liberty<->authority (mfv).
- big5: Plasticity (E+O) x Stability (A+C+reverse-N), DeYoung 2007 meta-traits.
- humor: Adaptive<->Maladaptive x Self<->Other directed, HSQ 2x2 (Martin 2003).
Human-only renders confirm the structure reproduces the literature: West societies
sit Individualizing, African-Islamic sit Binding (mfq2); West high Plasticity+
Stability (big5).
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
The cache was written once at the very end, so a killed run (session teardown)
discarded every sampled model. Persist after each model instead, and expand the
model-star palette to 14 so a large model panel doesn't silently drop stars past
the 6th via zip truncation.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Replace the model legend with textalloc-placed on-map labels (leader lines, coloured
to each star), and route country labels through the same textalloc pass so Pakistan/
Nigeria/Egypt no longer collide. outlying_countries now returns the corner-most
society in each diagonal direction (top-right/bottom-left/...) instead of the n
farthest from the centroid, which bunched on one side and left the bottom-left corner
(Egypt) unlabelled.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
The E-vector cache keyed on Python's builtin hash(), which is salted per process
(PYTHONHASHSEED), so the signature changed every run and the cache never hit across
processes -- silently re-spending on the OpenRouter API each time. Switch to a
stable hashlib key. LLM stars now go in a lower-right legend instead of colliding
inline labels (they cluster in one corner, which IS the result).
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
plot_ipsative_pca now draws the 4 most-separate zones as edge-only convex hulls
(select_spread_zones + draw_zone_hulls) instead of the disc-union blobs, colours
dots by drawn zone, and labels only landmarks + 4 most-outlying + one representative
per zone. One generic rule across every map (WVS + mfq2/big5/mfv), replacing the
per-country disc unions on these maps. Verified on a human-only big5 render.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Economist style: drop the axis ticks, move the neutral crosshair from an arbitrary
0.5 to the human-society median on each axis, and anchor each pole signpost's arrow
to its median crosshair (blended data/axes transform) so the four directions read
against the typical society. Pole labels all horizontal.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Replace hardcoded zone lists with geometric rules that work on any map:
- maps.select_spread_zones: greedy max-coverage on hull areas -- seed the
largest zone, add whichever contributes the most new non-overlapping area.
Drops central/covered zones (Orthodox) and keeps the corner cultures.
- maps.outlying_countries: the n countries farthest from the centroid, unioned
with named landmarks + one representative (most-central member) per drawn zone
so every region has at least one identifiable label.
- draw_zone_hulls: edge-only coloured outline (no fill), contour only for 2+
member groups, label anchored to the hull's top vertex.
WVS map: four arrowed pole signposts (Traditional/Secular-Rational/Survival/
Self-expression) in a padded inner margin so they don't collide with title/ticks;
model stars use a palette disjoint from the zone colours.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Replace the blind ipsative-PCA projection with two named IW axes built from
GlobalOpinionQA WVS items (tinymfv.iw_axes): X = Survival<->Self-expression
(homosexuality, trust, political action), Y = Traditional<->Secular-Rational
(religion importance+belief, abortion, child autonomy). Each item is oriented to
its axis-positive pole by reading the option order, so a reversed row can't flip a
country. Human anchors land where the published IW map puts them (Sweden top-right,
Nigeria/Pakistan bottom-left, East Asia secular-but-survival top-left).
Models answer the same items via the answer-token reader (single-digit option labels
so the 1-10 justifiable scale stays single-token); coords are the same axis-mean.
Add maps.draw_zone_hulls: tight rounded convex hulls (not inflated disc unions),
zone-coloured dots, outlier-only labels, white-haloed region names -- the Economist
grammar. draw_zone_regions stays for the instrument maps' within-country spread.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Cache model E-vectors keyed by the exact question block, so iterating on the zone
style re-projects + re-draws without re-hitting the API (~20 min of calls). A
question a model didn't answer coherently (NaN) is imputed with the human average
at projection so one collapse doesn't drop the whole model dot.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Replace stacked translucent discs (which darkened at overlaps) with a shapely
union per zone -> one merged shape, uniform alpha. Each country's territory is now
its REAL spread ellipse from its respondent/haze cloud (natural varying shape), not
a fixed disc; sizes are rescaled so the median country ~ a legible radius (raw
within-country spread >> between-country, would fill the plot). Every country sits
in its zone, 2-country zones have area. MFV/WVS (country means only) fall back to a
fixed disc. 16pf turned off (unreadable even at 6 macro zones). Adds shapely to the
maps extra.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
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>
