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Its axes run from Traditional to Secular-Rational and from Self-expression to Survival.`}),(0,C.jsx)(me,{data:e,hidden:n}),(0,C.jsxs)(`p`,{className:`caption`,children:[`Use the family controls to compare saved rated coordinates. The lines are weak descriptive correlations for the dated models currently shown; n and R² update with visibility. Hover or keyboard focus a mark for its coordinates and recorded release date. See the `,(0,C.jsx)(`a`,{href:`https://github.com/wassname/moral-maps`,children:`code and records`}),`.`]})]})}function ge(){let[e,t]=(0,_.useState)(null);return(0,_.useEffect)(()=>{fetch(`wvs/wvs_map_data.json`).then(e=>e.json()).then(t)},[]),(0,C.jsxs)(`main`,{children:[(0,C.jsx)(`h1`,{children:`How do AI models score on human values surveys? Which culture are they most similar to? Is it changing over time?`}),(0,C.jsxs)(`p`,{className:`lede`,children:[`We start with the `,(0,C.jsx)(`a`,{href:`https://www.worldvaluessurvey.org/`,children:`World Values Survey`}),`, a map of human values across about ninety countries.`]}),e&&(0,C.jsx)(he,{data:e})]})}(0,v.createRoot)(document.getElementById(`root`)).render((0,C.jsx)(ge,{})); \ No newline at end of file diff --git a/docs/index.html b/docs/index.html index e0e27d2..14fed15 100644 --- a/docs/index.html +++ b/docs/index.html @@ -4,8 +4,8 @@ Frontier LLMs on the World Values Survey - - + +
diff --git a/docs/wvs/wvs_map_data.json b/docs/wvs/wvs_map_data.json index 17a83e1..6ba0bd2 100644 --- a/docs/wvs/wvs_map_data.json +++ b/docs/wvs/wvs_map_data.json @@ -10,10 +10,15 @@ ] }, "capability_x": { - "blocker": "Capability scores are omitted until the source owner confirms redistribution permission.", + "fetched_utc": "2026-09-17T08:31:00Z", "label": "Artificial Analysis Intelligence Index", + "mapping": "slop/research/wvs/20260917_artificialanalysis/wvs_intelligence_index_mapping.json", + "matched_models": 9, + "raw_source": "slop/research/wvs/20260917_artificialanalysis/artificialanalysis_models_2026-09-17T083100Z.html", + "raw_source_sha256": "eff84596d778cc3c3665c701d96e46b8e11f36044ef44177beac41b98c2b21e1", + "selection_rule": "For each explicitly matched canonical release, use the highest listed Intelligence Index effort in this saved source. This source snapshot contains one listed effort for each mapping below.", "source_url": "https://artificialanalysis.ai/models", - "status": "blocked" + "status": "available" }, "countries": [ { @@ -727,6 +732,9 @@ "label": null, "name": "qwen3.6-27b", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "abf45a27f4bafad0eb264aac33b1e49e9d0404e141966954d0707930d56665e3", "readout": "rated categorical response", @@ -744,6 +752,9 @@ "label": null, "name": "qwen3.5-35b-a3b", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "7ee20ca2b88f69dd06b9de3018deea4cb7a418e3119e17862cd0b32146daae1a", "readout": "rated categorical response", @@ -761,6 +772,9 @@ "label": null, "name": "qwen3.6-max-preview", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "fa9ff591d389ad2d8a4b7e3fc1410ed588508fe286430c06a941180b0590422b", "readout": "rated categorical response", @@ -778,6 +792,9 @@ "label": "muse-spark-1.3", "name": "muse-spark-1.3", "provenance": { + "intelligence_index": 48.1690107719685, + "intelligence_source_effort": "max", + "intelligence_source_name": "Muse Spark 1.3 (max)", "items": 12, "protocol_id": "3c9d4fedebcab41719f4247ca94fa35430f57d0a34f3a539012e0632e35413de", "readout": "rated categorical response", @@ -795,6 +812,9 @@ "label": null, "name": "qwen3.8-27b", "provenance": { + "intelligence_index": 33.9015108057476, + "intelligence_source_effort": "xhigh", + "intelligence_source_name": "Qwen3.8 27B (xhigh)", "items": 12, "protocol_id": "ed8190c48b2a3778bba8afff7381bb9f1578211b5e8f750d21321b62617c82c3", "readout": "rated categorical response", @@ -812,6 +832,9 @@ "label": "qwen3.8-flash", "name": "qwen3.8-flash", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "3443c17ae66d3fb529a058128b662024c4bc0601394e614bb693b388ec4c988b", "readout": "rated categorical response", @@ -829,6 +852,9 @@ "label": "gemma-4-31b-it", "name": "gemma-4-31b-it", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -846,6 +872,9 @@ "label": null, "name": "qwen3.5-122b-a10b", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "e0a9daef251d975c5e805e159f3813dd0c55b3f0919876b828e572b0530bea88", "readout": "rated categorical response", @@ -863,6 +892,9 @@ "label": null, "name": "grok-4.20", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -880,6 +912,9 @@ "label": null, "name": "qwen3.5-plus-20260420", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "6d6ce30e9fbc5fdb07229b0a08e067d77511857069a4e572613d3e48b7c8b261", "readout": "rated categorical response", @@ -897,6 +932,9 @@ "label": null, "name": "gemini-2.5-pro", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -914,6 +952,9 @@ "label": "grok-4.3", "name": "grok-4.3", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -931,6 +972,9 @@ "label": null, "name": "deepseek-v4-flash", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -948,11 +992,14 @@ "label": null, "name": "gpt-5.4", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", - "release_created": null, - "release_source": "historical coordinate", + "release_created": "2026-03-05", + "release_source": "saved OpenRouter catalog 2026-09-17: openai/gpt-5.4", "run_id": null, "samples": null }, @@ -965,6 +1012,9 @@ "label": "deepseek-v4.1-flash", "name": "deepseek-v4.1-flash", "provenance": { + "intelligence_index": 39.545442472527, + "intelligence_source_effort": "max", + "intelligence_source_name": "DeepSeek V4.1 Flash (Reasoning, Max Effort)", "items": 12, "protocol_id": "8c27d32cd851de5f217cb354b15dc270cc6f4ec2d02fb15dbb20fde0790c3571", "readout": "rated categorical response", @@ -982,6 +1032,9 @@ "label": null, "name": "qwen3-coder-30b-a3b-instruct", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "39659697ca3437f62be4fb8e129e6b3902a91b5acac3243ca914dfc917dd563b", "readout": "rated categorical response", @@ -999,6 +1052,9 @@ "label": null, "name": "qwen3-30b-a3b", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "8700e79d3eccf358a0de1029f7b40e2db339bb6d11403b8e69cb7a66a7b0c668", "readout": "rated categorical response", @@ -1016,6 +1072,9 @@ "label": "gpt-6-astra", "name": "gpt-6-astra", "provenance": { + "intelligence_index": 52.814069395513, + "intelligence_source_effort": "max", + "intelligence_source_name": "GPT-6 Astra (max)", "items": 12, "protocol_id": "95bb4d3939e9937823357b5cd87adb1a6640cc5b04e0841dfec03095331a5e44", "readout": "rated categorical response", @@ -1033,6 +1092,9 @@ "label": "mistral-large-2512", "name": "mistral-large-2512", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -1050,6 +1112,9 @@ "label": null, "name": "gemma-3-27b-it", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -1067,6 +1132,9 @@ "label": "llama-4-maverick", "name": "llama-4-maverick", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -1084,6 +1152,9 @@ "label": null, "name": "qwen3-coder", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "304db4b1aa6c80d734f802749c75143feddfcdb740c4131385e927148ba7d05b", "readout": "rated categorical response", @@ -1101,6 +1172,9 @@ "label": null, "name": "qwen3.7-flash", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "82875b6ee164d0d980eba738bf05f69959234567b91f9cfd01fcabca0bd70dac", "readout": "rated categorical response", @@ -1118,6 +1192,9 @@ "label": null, "name": "qwen3-vl-235b-a22b-instruct", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "61ab1adae3781ca3893328a845d4d517daa5fb47e07ea189da1df45388f62d42", "readout": "rated categorical response", @@ -1135,6 +1212,9 @@ "label": null, "name": "qwen-plus", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "88ba5af838eda5d298b312553d7c941e72a37cbf28890cdb9d8436b5f40e7cfe", "readout": "rated categorical response", @@ -1152,6 +1232,9 @@ "label": null, "name": "gpt-5.3-chat", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -1169,6 +1252,9 @@ "label": null, "name": "deepseek-v4-pro", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -1186,6 +1272,9 @@ "label": null, "name": "llama-4-scout", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -1203,6 +1292,9 @@ "label": null, "name": "qwen3-vl-30b-a3b-instruct", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "0a798666aeed20785b4661c8c2fe4a6fc6853796bc2f3c45133863469e5b3f82", "readout": "rated categorical response", @@ -1220,6 +1312,9 @@ "label": null, "name": "qwen3.5-397b-a17b", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "921707cb0d3db143e948e9d78cd8191f4ee720eaf56b6934e2d13d9ce9e3382f", "readout": "rated categorical response", @@ -1237,6 +1332,9 @@ "label": null, "name": "qwen3.5-plus-02-15", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "74e3649a6961000bab284e801fe811d5c8fc4cf1db15af52bb10959f5a5a37c1", "readout": "rated categorical response", @@ -1254,6 +1352,9 @@ "label": "glm-5.3", "name": "glm-5.3", "provenance": { + "intelligence_index": 44.855717385614, + "intelligence_source_effort": "max", + "intelligence_source_name": "GLM-5.3 (max)", "items": 12, "protocol_id": "d81f7e66b3c4c720f8dd80768d3dfc25de6edeaf6a352cfed40e961f21fcfa22", "readout": "rated categorical response", @@ -1271,6 +1372,9 @@ "label": null, "name": "qwen3.7-plus", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "f095e0d2dbafdb91b51be3d0b3bd5a597730c8e3c397e0461023c87e924d92f8", "readout": "rated categorical response", @@ -1288,6 +1392,9 @@ "label": null, "name": "qwen3-30b-a3b-instruct-2507", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "88ed922f271a76721ad18f0b7bb9693a48377e2507d02a4b78fa08b451972d83", "readout": "rated categorical response", @@ -1305,11 +1412,14 @@ "label": null, "name": "gpt-5.5", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", - "release_created": null, - "release_source": "historical coordinate", + "release_created": "2026-04-24", + "release_source": "saved OpenRouter catalog 2026-09-17: openai/gpt-5.5", "run_id": null, "samples": null }, @@ -1322,6 +1432,9 @@ "label": null, "name": "qwen3.6-35b-a3b", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "b35b916c22649e91ded175aede34f3937a16f42a354f7abab01a17bf2b0dfc97", "readout": "rated categorical response", @@ -1339,6 +1452,9 @@ "label": null, "name": "qwen3.6-flash", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "fa37fc90604e5032183ec460bcc2632507566c3be3e9085f61a6ca85582b7d47", "readout": "rated categorical response", @@ -1356,6 +1472,9 @@ "label": null, "name": "qwen3.6-plus", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "96d86b64bf7ceff8eed0daff1aa0396ee69609b5867942a7c2c9d33093f03c9d", "readout": "rated categorical response", @@ -1373,6 +1492,9 @@ "label": null, "name": "qwen3-235b-a22b", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "842298c634ec0f57848b605f67fca161631a852a68192cae1a5377b1d9f31566", "readout": "rated categorical response", @@ -1390,6 +1512,9 @@ "label": null, "name": "qwen-2.5-72b-instruct", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "9c1d40b30945565e488b212177e40c29f730c2e96d4b07d09cbc135ba75a81f0", "readout": "rated categorical response", @@ -1407,6 +1532,9 @@ "label": null, "name": "qwen-plus-2025-07-28", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "ac52652ff1f09e1f1972a8b751e1b1deca329cb555df54755aada79791bed940", "readout": "rated categorical response", @@ -1424,6 +1552,9 @@ "label": null, "name": "qwen3.7-max", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "1c31668055e399de28805046bc08075035efbad0cdb1ff7d8926841a282e07a5", "readout": "rated categorical response", @@ -1441,6 +1572,9 @@ "label": null, "name": "qwen3-235b-a22b-2507", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "dc09c3fe433c95591b336b279603c546152daf6534d90699323b3bcde754f5bf", "readout": "rated categorical response", @@ -1458,6 +1592,9 @@ "label": null, "name": "qwen3.5-9b", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "3016d2c1ab8d8f88f01723d2d695be996c7f1fdcd442a51cfbb6c7b7110a25e9", "readout": "rated categorical response", @@ -1475,6 +1612,9 @@ "label": null, "name": "qwen2.5-vl-72b-instruct", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "02d386b067d55e0639d33db8b6f1e5c708c30acbada3125dcbabde47dc90edcf", "readout": "rated categorical response", @@ -1492,6 +1632,9 @@ "label": null, "name": "qwen3-vl-32b-instruct", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "43ddc43fb5a29c7fbf21c8f32b42a909c2118feb9255959ecaeab7dadb1f3dde", "readout": "rated categorical response", @@ -1509,6 +1652,9 @@ "label": null, "name": "gpt-5.6-sol", "provenance": { + "intelligence_index": 47.0613568915036, + "intelligence_source_effort": "max", + "intelligence_source_name": "GPT-5.6 Sol (max)", "items": 12, "protocol_id": "1a70f47789af20900f2799992b09e83af9490be6579098a6178d613d5ba7856c", "readout": "rated categorical response", @@ -1526,6 +1672,9 @@ "label": null, "name": "qwen3-max-thinking", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "bca0745bdc1554718d57891098f366214f05e9e896007a916d14a06efa33471a", "readout": "rated categorical response", @@ -1543,6 +1692,9 @@ "label": null, "name": "qwen3-coder-plus", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "182a7e88869698133f1175f18e53e7f6f2f056739559d325b211bd065235a71c", "readout": "rated categorical response", @@ -1560,6 +1712,9 @@ "label": "inkling", "name": "inkling", "provenance": { + "intelligence_index": 25.5423060999384, + "intelligence_source_effort": "xhigh", + "intelligence_source_name": "Inkling (xhigh)", "items": 12, "protocol_id": "67a70b1b03ba85be79dc122cc888a080fde239205624135a9147168e7e77293d", "readout": "rated categorical response", @@ -1577,6 +1732,9 @@ "label": null, "name": "qwen3-vl-8b-instruct", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "1d7f4015decbcbe955adb79817b970981ca1d3165ed121b458b213ba1060f675", "readout": "rated categorical response", @@ -1594,6 +1752,9 @@ "label": null, "name": "qwen-2.5-7b-instruct", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "66ad076e1a37493e4d3db982a0220048e520103459cefc709bc8f09f3fef6c9a", "readout": "rated categorical response", @@ -1611,6 +1772,9 @@ "label": "kimi-k3", "name": "kimi-k3", "provenance": { + "intelligence_index": 43.7841729518782, + "intelligence_source_effort": "max", + "intelligence_source_name": "Kimi K3 (max)", "items": 12, "protocol_id": "0043a43d1a2188f7c728ccda08eee7b062232366d8a4e912c72bdc938e37fe44", "readout": "rated categorical response", @@ -1628,6 +1792,9 @@ "label": null, "name": "qwen3.5-27b", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "7058adf367d238c6c92e1b83ae71f6556362e9fc7a243297b6fc65e54e2c2886", "readout": "rated categorical response", @@ -1645,6 +1812,9 @@ "label": null, "name": "qwen3-32b", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "580a5840948209ecb177dc6fdaf36e265a32ccfe223d791eb3235fea9269f27e", "readout": "rated categorical response", @@ -1662,6 +1832,9 @@ "label": null, "name": "qwen3-14b", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "49ae9f7a09090534a15fac734c2611c445a17139cad6c5684fa0581722f3fd70", "readout": "rated categorical response", @@ -1679,6 +1852,9 @@ "label": null, "name": "qwen3-coder-next", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "57bed80fd5b94157effe68fe998c7c12612fea210c1371dbf230097a7e8e0717", "readout": "rated categorical response", @@ -1696,6 +1872,9 @@ "label": null, "name": "qwen3-next-80b-a3b-instruct", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "9d8a5189c078672eb884784938b183944fb161d0e716e2c44722540b17603e34", "readout": "rated categorical response", @@ -1713,6 +1892,9 @@ "label": null, "name": "claude-opus-4.7", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -1730,6 +1912,9 @@ "label": null, "name": "qwen3-8b", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "589e10fa7924ecf8f88650d6587ff37c440f47c6c4cc4325c7009ef8d4eeb4ec", "readout": "rated categorical response", @@ -1747,6 +1932,9 @@ "label": null, "name": "claude-opus-4.8", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -1764,6 +1952,9 @@ "label": "gemini-3.7-flash", "name": "gemini-3.7-flash", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": 12, "protocol_id": "cd5db529649a179032180cecafe4fd98aff124ee3654f7d60996de704e2b63ef", "readout": "rated categorical response", @@ -1781,6 +1972,9 @@ "label": "fable-5.1", "name": "claude-fable-5.1", "provenance": { + "intelligence_index": 53.3737509623252, + "intelligence_source_effort": "max", + "intelligence_source_name": "Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback)", "items": 12, "protocol_id": "4230ccaa1e160c793a906aef6b786d735d9fdbf71c3333691b0eba17dcf33928", "readout": "rated categorical response", @@ -1798,6 +1992,9 @@ "label": null, "name": "claude-opus-4.6", "provenance": { + "intelligence_index": null, + "intelligence_source_effort": null, + "intelligence_source_name": null, "items": null, "protocol_id": null, "readout": "recovered rounded historical coordinate", @@ -1811,7 +2008,7 @@ } ], "note": "source: github.com/wassname/moral-maps", - "schema": 2, + "schema": 3, "title": "Frontier LLMs on the\nWorld Values Survey", "zone_hulls": [ { diff --git a/scripts/wvs_react/src/main.jsx b/scripts/wvs_react/src/main.jsx index abeb876..2b20038 100644 --- a/scripts/wvs_react/src/main.jsx +++ b/scripts/wvs_react/src/main.jsx @@ -1,6 +1,6 @@ import React, { useEffect, useMemo, useRef, useState } from 'react'; import { createRoot } from 'react-dom/client'; -import { VIEW, assertLayout, roundedHull } from './layout.js'; +import { VIEW, RINGS, LABEL_STEPS, assertLayout, box, hits, inside, roundedHull } from './layout.js'; import './style.css'; const LOGO_ROOT = 'wvs/'; @@ -16,10 +16,11 @@ function Tooltip({ active, geometry, id = 'model-tooltip', panel }) { const release = active.provenance.release_created && release {active.provenance.release_created}; return ; } @@ -38,9 +39,9 @@ function ModelMarker({ model, placement, geometry, setActive, clearActive, marke ; } -function ordinaryLeastSquares(models, value) { - const x = models.map(model => Date.parse(model.provenance.release_created)); - const y = models.map(value); +function ordinaryLeastSquares(models, xValue, yValue) { + const x = models.map(xValue); + const y = models.map(yValue); const uniqueX = new Set(x); if (uniqueX.size < 2) return null; const xMean = x.reduce((sum, value) => sum + value, 0) / x.length; @@ -53,70 +54,114 @@ function ordinaryLeastSquares(models, value) { return { slope, intercept, n: models.length, r2: total === 0 ? null : 1 - residual / total }; } -function ReleaseScatter({ data, hidden, field, title }) { +function ReleaseScatter({ data, hidden, field, title, axisMode }) { const dated = useMemo(() => data.models.filter(model => Number.isFinite(Date.parse(model.provenance.release_created ?? ''))) .toSorted((a, b) => a.provenance.release_created.localeCompare(b.provenance.release_created) || a.name.localeCompare(b.name)), [data]); - const visible = dated.filter(model => !hidden.has(model.family)); + const matched = useMemo(() => data.models.filter(model => Number.isFinite(model.provenance.intelligence_index)) + .toSorted((a, b) => a.provenance.intelligence_index - b.provenance.intelligence_index || a.name.localeCompare(b.name)), [data]); + const plotted = axisMode === 'release-date' ? dated : matched; + const visible = plotted.filter(model => !hidden.has(model.family)); const coordinate = model => field === 'x' ? -model.x : model.y; - const fit = ordinaryLeastSquares(visible, coordinate); + const xValue = model => axisMode === 'release-date' ? Date.parse(model.provenance.release_created) : model.provenance.intelligence_index; + const fit = ordinaryLeastSquares(visible, xValue, coordinate); const [active, setActive] = useState(null); const width = 1200, height = 320, left = 96, right = 35, top = 42, bottom = 48; - const dates = dated.map(model => Date.parse(model.provenance.release_created)); - const values = dated.map(coordinate); - const minDate = Math.min(...dates), maxDate = Math.max(...dates); + const xValues = plotted.map(xValue); + const values = plotted.map(coordinate); + const minX = Math.min(...xValues), maxX = Math.max(...xValues); const minValue = Math.min(...values), maxValue = Math.max(...values); - const dateX = date => left + (date - minDate) / (maxDate - minDate) * (width - left - right); + const plotX = value => left + (value - minX) / (maxX - minX || 1) * (width - left - right); const valueY = value => top + (maxValue - value) / (maxValue - minValue || 1) * (height - top - bottom); const panelId = `release-${field}`; const tooltipId = `${panelId}-tooltip`; const yDirection = field === 'y' ? data.axis.y : [...data.axis.x].reverse(); - const visibleDates = visible.map(model => Date.parse(model.provenance.release_created)); - const fitEnd = fit && [Math.min(...visibleDates), Math.max(...visibleDates)].map(date => [dateX(date), valueY(fit.intercept + fit.slope * date)]); + const visibleX = visible.map(xValue); + const fitEnd = fit && [Math.min(...visibleX), Math.max(...visibleX)].map(value => [plotX(value), valueY(fit.intercept + fit.slope * value)]); + const frontier = useMemo(() => { + if (axisMode !== 'release-date') return []; + let high = -Infinity; + return visible.filter(model => Number.isFinite(model.provenance.intelligence_index)).filter(model => { + if (model.provenance.intelligence_index <= high) return false; + high = model.provenance.intelligence_index; + return true; + }); + }, [axisMode, visible]); + const frontierPlacement = useMemo(() => { + const bounds = { left, right: width - right, top, bottom: height - bottom }; + const taken = plotted.map(model => box(plotX(xValue(model)), valueY(coordinate(model)), 16, 16)); + const placement = {}; + for (const model of frontier) { + const anchor = { x: plotX(xValue(model)), y: valueY(coordinate(model)) }; + const size = { width: model.name.length * 8 + 12, height: 18 }; + let found = null; + for (const step of LABEL_STEPS) { + for (const [dx, dy] of RINGS) { + const candidate = box(anchor.x + dx * (step + size.width / 3), anchor.y + dy * step, size.width, size.height); + if (inside(candidate, bounds) && !taken.some(obstacle => hits(candidate, obstacle))) { found = candidate; break; } + } + if (found) break; + } + if (!found) throw new Error(`no frontier label location for ${model.name}`); + placement[model.name] = { ...found, anchor }; + taken.push(found); + } + return placement; + }, [frontier, plotted, minX, maxX, minValue, maxValue]); const activate = (model, event) => { const box = event.currentTarget.closest('.scatter-shell').getBoundingClientRect(); const point = event.currentTarget.getBoundingClientRect(); - setActive({ ...model, tooltipValue: coordinate(model), tooltipLeft: `${Math.min(82, (point.left - box.left) / box.width * 100)}%`, tooltipTop: `${Math.min(78, (point.top - box.top) / box.height * 100)}%` }); + setActive({ ...model, tooltipValue: coordinate(model), tooltipIndex: axisMode === 'capability' ? model.provenance.intelligence_index : null, tooltipLeft: `${Math.min(82, (point.left - box.left) / box.width * 100)}%`, tooltipTop: `${Math.min(78, (point.top - box.top) / box.height * 100)}%` }); }; return

{title}

- + {title} - Scatter plot with release date on the horizontal axis and {yDirection.join(' to ')} increasing upward on the vertical axis. {visible.length} dated models are visible from {visibleFamilyNames(Object.groupBy(data.models, model => model.family), hidden).join(', ') || 'no families'}. Each white-ring logo mark is a model. {fit ? `The thin line is an ordinary least squares descriptive fit to the ${fit.n} currently visible dated models${fit.r2 === null ? '; R squared is unavailable because the y values are constant' : `; R squared is ${fit.r2.toFixed(2)}`}.` : 'The fit is hidden because fewer than two distinct release dates are visible.'} Hover or keyboard focus a mark for model-specific details. + Scatter plot with {axisMode === 'release-date' ? 'release date' : 'Artificial Analysis Intelligence Index'} on the horizontal axis and {yDirection.join(' to ')} increasing upward on the vertical axis. {visible.length} of {plotted.length} matched models are visible from {visibleFamilyNames(Object.groupBy(data.models, model => model.family), hidden).join(', ') || 'no families'}; {data.models.length - plotted.length} plotted models lack this x value and are omitted only here. Each white-ring logo mark is a model. {fit ? `The thin line is an ordinary least squares descriptive fit to the ${fit.n} currently visible matched models${fit.r2 === null ? '; R squared is unavailable because the y values are constant' : `; R squared is ${fit.r2.toFixed(2)}`}.` : 'The fit is hidden because fewer than two distinct x values are visible.'} Hover or keyboard focus a mark for model-specific details. {Array.from({ length: 5 }, (_, index) => )} {yDirection.join(' -> ')} {'↑'} - {new Date(minDate).toISOString().slice(0, 10)} - {new Date(maxDate).toISOString().slice(0, 10)} + {axisMode === 'release-date' ? new Date(minX).toISOString().slice(0, 10) : minX.toFixed(1)} + {axisMode === 'release-date' ? new Date(maxX).toISOString().slice(0, 10) : maxX.toFixed(1)} {maxValue.toFixed(2)} {minValue.toFixed(2)} {fitEnd && OLS, n={fit.n}, R² {fit.r2 === null ? 'unavailable' : fit.r2.toFixed(2)}} {!fit && Fit unavailable: fewer than two release dates} - {dated.map(model => activate(model, event)} onPointerLeave={() => setActive(null)} onFocus={event => activate(model, event)} onBlur={() => setActive(null)}> - - + + )} + {axisMode === 'release-date' && frontier.map(model => {model.name})}
; } -function ReleaseScatters({ data, hidden }) { - return
-
-
- - {data.capability_x.blocker} -
Frontier LLMs on the World Values Survey @@ -173,8 +211,8 @@ function Map({ data }) {

Since 1981, the World Values Survey has asked people in about ninety countries the same questions. Its axes run from Traditional to Secular-Rational and from Self-expression to Survival.

-