Lets a model be described as a 2.9 sigma member of the West instead of
"somewhere west of Silicon Valley". Signed per-axis z says which way and how
far on a named axis; Mahalanobis says how odd the placement is overall, and
uses the cluster covariance because the zones are elongated and tilted.
Reads the committed coords in wvs_model_ci.md rather than the coord cache,
so it reruns offline without re-querying seventeen models.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The MFV foundation readout is centered log-ratio (clr), not a logit. Renames the
showcase JSON/CSV consumers' keys (dclr/dclr_sem) and the shared reader-space-shift
column to match steering-lite's writers; the survey 'C = logit contrast' readout
keeps its logit naming.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Draw the title and github.com/wassname/moral-maps note in the empty bottom-left
INSIDE the axes so a crop can't strip attribution and there's no whitespace band.
Give the models overlay extra top headroom so the most-secular model stars and
their labels seat inside the frame instead of spilling above it. Regenerate PNG+SVG.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Import name tinymfv -> moralmaps, pip name tiny-mfv -> moral-maps, GitHub
URLs wassname/tinymfv -> wassname/moral-maps. HuggingFace dataset id
wassname/tiny-mfv left as-is (separate namespace, published data artifact).
Historical docs/spec/* and RESEARCH_JOURNAL keep their dated paths.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
MFV country norms fail cross-country measurement invariance (Jimenez-Leal 2025: non-invariance + DIF,
'cross-cultural comparisons restricted') and are stitched from 5 studies, so the culture map/quadrant
drew false structure (inverted West vs Latin America). Delete plot_mfv_map + plot_mfv_value and the
value_coords_contrast/axis_contrast helpers; MFV keeps only the range plot, now against ONE pooled
human reference (mean of the 8 z-scored samples), no per-country identity. Add data-dir note + README
caveats citing the sources.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
One shared orient_geographic() helper folds axis signs into the coords (value maps) or into Vt
(ipsative PCA, so dots/haze/steer/compass all inherit one flip). Replaces the WVS-only invert_x hack;
every map now reads left/right the same way. Regenerate instrument showcase maps.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Renders the dream artifact: a 5x5 grid of MFV profile bar charts (one per
(hc, cc) cell), per-foundation dlogit heatmaps for MFV, per-factor C heatmaps
for ordinal instruments, and a pmass coherence heatmap. Reads the 2D-grid
profiles CSVs written by steering-lite's run_2d_grid_showcase.py.
The 17-model IW map now renders through labelplace.allocate_labels; save the artifact
into the repo (png for viewing, svg for hand-editing labels, CI table as companion).
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Replace the fling-to-open-space-with-a-leader zone placement with _hull_label_pos:
walk the hull's own boundary vertices, nudge each slightly outward, and put the
label on the vertex whose nearest dot/label is farthest -- so the name sits against
an uncrowded arc of its own outline, no leader line. And flip X (invert_x) so
Self-expression is on the left and Survival on the right: this is a better map than
the Economist's, and it puts the cultural West on the left / East Asia on the right.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Zone labels now get a dedicated open-space search (_open_slot: scan a ring around
the hull centroid, keep the slot whose nearest dot/label is farthest) instead of
adjustText's local minimum -- so Latin America/African-Islamic land in the sparse
margins with a leader to their hull, not the crowded centre. And with 17 models the
names were too many: plot every star but LABEL only the latest per family (highest
version), dropping the redundant 'claude-' so the flagship reads 'opus-4.8'. Colour
+ legend carry the unlabelled siblings.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Computed from raw participant ratings in dat_rep.sav (OSF cmwpv, full 90-item
Clifford MFV, 1-5), using the author's own item->foundation map from the R
notebook. Complete-case N=756 reproduces the paper's abstract exactly. The
paper's headline is a genetic-algorithm-abbreviated MFV; we deliberately used
the FULL 90 items so Australia is comparable to the other full-instrument rows.
The paper's other sample (580 US MTurk) is skipped -- it would duplicate US.
Cloud now 7 -> 8. Fresh-eyes subagent reproduced all six means to <=0.0005.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Models are now stars coloured by lab family instead of one Economist red, hue
chosen to echo the lab's home region: Chinese labs warm (qwen orange, deepseek
pink) near the East-Asia red, US labs cool (claude purple, gpt blue, gemini/gemma
sea blue, grok indigo, llama steel), Europe green (mistral). Legend keys each
family. Also drop the ' (rated)' tag from on-map labels and Nigeria from the
always-on landmarks (Egypt already anchors the African-Islamic corner).
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
With a dozen+ models the 95% CI crosses overlap into noise. Remove the whiskers
from plot_value_map (clean red dots) and instead write a widest-first CI table
(wvs_model_ci.md) next to the figure. The table also documents that the wide CIs
are item-disagreement (a model rating different WVS items inconsistently on an
axis), which more samples will not shrink -- not sampling noise.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Clifford MFV wrongness vignettes, 1-5 scale (same as existing LatAm/Japan
rows). Care collapsed from their split physical(4.09)+emotional(3.53) to a
single 3.81; other foundations from their Table 1 with paper 95% CIs.
Grows the human country cloud 5 -> 6.
Note: the Dutch and LatAm authors both flag MFV measurement non-invariance
(DIF) across countries, so between-country means are a rough reference, not
a calibrated ranking. Map is ipsative (within-country z), which is affine-
invariant to the scale, so it reads relative foundation emphasis.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Replace the single forced-choice sampling reader (1 bit/call, truncated verbose
models to empty at max_tokens=32, positionally biased) with a dense readout:
rate every option 1-5 as JSON, N samples, binary items order-balanced to cancel
positional bias, ratings mapped back to canonical order and normalized to a
distribution. All of a model's calls fire concurrently (asyncio.gather over the
async openrouter_wrapper; per_call=1 since providers ignore n>1). Each model
carries a bootstrap 95% CI (over items + samples) drawn as error bars, so mushy
models (deepseek-flash was near coin-flip) read as uncertain, not confident dots.
One flaky provider is skipped, not fatal.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
_zscore now asserts nonzero variance (a flat profile drew a degenerate all-zero
map that looked valid) instead of dividing by std+1e-9. _soft_nll docstring now
states the 1e-12 floor it actually applies (was 'Unbounded'). Trim archaeology
comments (guided/wvs/read_api) to the invariant, dropping the dated model names.
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 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>
