25:["$","title",null,{"children":"What Drives Stasis Among the Greek Poleis? | Thomas Butcher | Observable"}] 4b:T69c,## Introduction *Stasis* (civil strife, often translated "civil war") was one of the great political dangers of the ancient Greek world. Between 500 and 300 BCE, the 1,035 poleis (city-states) in the Hansen and Nielsen inventory had 411 attested episodes of stasis in total, but they were not spread evenly: 901 poleis have none on record, while Syracuse alone has 20. This project asks which characteristics of a polis go with having more of it. Better-documented poleis show more stasis partly because historians simply know more about them. So every comparison here is shown twice: raw, and after removing how well documented each polis is. ## Data Sources 1. **Polis dataset, version 21.08.25** (Prof. Scott Arcenas, University of Montana). One row per polis, built on Hansen and Nielsen's *An Inventory of Archaic and Classical Greek Poleis* (2005), with the attested staseis from Arcenas (2018). Every variable is described in the codebook. 2. **Natural Earth, 1:10m land** (public domain). Used only for the coastline on the map. [naturalearthdata.com](https://www.naturalearthdata.com/downloads/10m-physical-vectors/10m-land/) 3. **Pleiades gazetteer.** The source of most polis locations in the dataset. [pleiades.stoa.org](https://pleiades.stoa.org/) Resources Used: * The data cleaning, correlation ranking, expected-staseis model and map geometry come from Ben's Python code (`staseis_plots.py` and `build_map.py` in the group's GitHub repository, benbarlog/polis). This notebook reads the results of that code. * Generative AI (Claude) was used to learn syntax and different methods with plots in Observable JavaScript, and to turn the Python results into this notebook. 4c:T509,rankingChart = { const rows = correlations; const label = d => (d.n < 1000 ? `${d.name} (n=${d.n})` : d.name); const signed = (v, digits = 2) => (v < 0 ? "−" : "") + Math.abs(v).toFixed(digits); const raw = "Raw", controlled = "Controlled for prominence (prom 1)"; return Plot.plot({ title: "Spearman correlation of each feature with attested staseis", width: Math.min(width, 900), height: 90 + rows.length * 28, marginLeft: 175, marginRight: 46, marginBottom: 46, style: {fontWeight: 600, fontSize: "13px"}, x: {label: "Spearman ρ with attested staseis →", domain: [-0.4, 0.6], grid: true, tickFormat: v => signed(v, 1)}, y: {label: null, domain: rows.map(label), tickSize: 0, padding: 0.4}, color: {domain: [raw, controlled], range: [palette.orange, palette.blue], legend: true}, marks: [ Plot.ruleX([0]), Plot.ruleY(rows, {y: label, x1: "raw", x2: "controlled", stroke: "#999", strokeWidth: 3}), Plot.dot(rows, {x: "raw", y: label, r: 5, fill: () => raw}), Plot.dot(rows, {x: "controlled", y: label, r: 6.5, fill: () => controlled}), Plot.text(rows, {x: d => Math.max(d.raw, d.controlled), y: label, text: d => signed(d.controlled), dx: 12, textAnchor: "start", fill: palette.blue}) ] }); } 4d:T470,expectedChart = Plot.plot({ title: "Attested staseis against prominence, with the count documentation alone predicts", width: Math.min(width, 900), height: 440, marginLeft: 55, marginBottom: 50, style: {fontWeight: 600, fontSize: "13px"}, x: {type: "log", label: "Prominence: columns of text in HN →", domain: [0.1, 25], ticks: [0.1, 0.3, 1, 3, 10, 20], tickFormat: d => String(d), grid: true}, y: {type: "symlog", constant: 1, label: "↑ Attested staseis", domain: [-0.25, 24], ticks: [0, 1, 2, 5, 10, 20], tickFormat: d => String(d), grid: true}, marks: [ Plot.dot(polis, {x: "prom_1", y: "staseis", r: 3.4, fill: palette.blue, fillOpacity: 0.4}), Plot.line(d3.sort(polis, d => d.prom_1), {x: "prom_1", y: "expected", stroke: palette.orange, strokeWidth: 3.5}), Plot.text([{prom_1: 14, expected: 9}], {x: "prom_1", y: "expected", text: () => "expected from documentation alone", fill: palette.orange, dy: -14, textAnchor: "middle"}), Plot.tip(polis, Plot.pointer({x: "prom_1", y: "staseis", title: d => `${d.name}\n${d.region}\nStaseis: ${d.staseis}\nExpected: ${d.expected.toFixed(1)}`})) ] }) 4e:T25c6,mapFigure = { const {meta, land} = mapData; const key = mapFeature, v = meta.vars[key], stats = analysis.features[key]; const fname = features.find(f => f.key === key)?.name ?? v.col; const adj = mapMode.startsWith("Observed"); // The starting views, in km on Ben's map plane (north up): a center and half the width shown. // mapState is shared by both maps, so they always look at the same place. const {greek, aegean} = meta.views; const presets = { "Greek world": {cx: greek.x, cy: greek.y, half: 2050 / greek.zoom}, "Aegean": {cx: aegean.x, cy: aegean.y, half: 2050 / aegean.zoom}, "Everything": {cx: 0, cy: 0, half: 2050} }; if (mapState.view !== mapView) Object.assign(mapState, presets[mapView], {view: mapView}); // a new view choice resets the position; other controls keep it const gap = 16, two = width > 720; const w = Math.floor(two ? (Math.min(width, 1000) - gap) / 2 : Math.min(width, 900)), h = Math.round(w * 0.64); const coast = Plot.geo(land, {fill: palette.land, stroke: "grey", strokeWidth: 0.5}); const top = [...mapData.dots].sort((a, b) => b.staseis - a.staseis).slice(0, 6); const unknown = mapCells.filter(d => d.properties["r_" + key] == null); const projection = () => { const {cx, cy, half} = mapState, hh = half * 0.64; return {type: "reflect-y", domain: {type: "Polygon", coordinates: [[[cx - half, cy - hh], [cx + half, cy - hh], [cx + half, cy + hh], [cx - half, cy + hh], [cx - half, cy - hh]]]}}; }; const colorLeft = adj ? {type: "diverging", scheme: "PuOr", pivot: 0, domain: [-8, 8], clamp: true, label: "Observed − expected staseis (purple: fewer, orange: more)"} : {type: "sqrt", scheme: "YlOrRd", domain: [0, 20], range: [0.12, 1], clamp: true, ticks: [0, 1, 2, 5, 10, 20], label: "Attested staseis"}; const colorRight = {type: stats.log ? "symlog" : "linear", scheme: "Blues", domain: [v.lo, v.hi], range: [0.08, 0.95], clamp: true, unknown: "#d3d3d3", label: v.desc}; const drawLeft = () => Plot.plot({ width: w, height: h, projection: projection(), color: colorLeft, marks: [ coast, Plot.geo(mapCells, {fill: d => (adj ? d.properties.resid : d.properties.staseis), stroke: "white", strokeWidth: 0.4, ariaLabel: d => "polis " + d.properties.id}), Plot.text(top, {x: "x", y: "y", text: "t_name", dy: -9, fontSize: 11, fontWeight: 600, fill: "#111", stroke: "white", strokeWidth: 3, paintOrder: "stroke"}) ] }); const drawRight = () => Plot.plot({ width: w, height: h, projection: projection(), color: colorRight, marks: [ coast, Plot.geo(mapCells, {fill: d => d.properties["r_" + key], stroke: "white", strokeWidth: 0.4, ariaLabel: d => "polis " + d.properties.id}) // unknown values come out grey (color.unknown) ] }); const stageStyle = `position: relative; overflow: hidden; width: ${w}px; height: ${h}px; cursor: grab; touch-action: none; box-shadow: 0 0 0 1px #ddd; background: #fff;`; const leftStage = html`

`, rightStage = html`

`; const stages = [leftStage, rightStage]; let left = drawLeft(), right = drawRight(); leftStage.append(left); rightStage.append(right); // Panning and zooming. While you drag or scroll, both maps are moved and scaled with CSS so they follow your hand // instantly; a moment after you stop, both are redrawn at the new position so they stay sharp. let g = {tx: 0, ty: 0, k: 1}, timer = null, drag = null; const HALF_MIN = 15, HALF_MAX = 2560; // closest and farthest the maps can go, in km const show = () => { for (const s of stages) { const svg = s.firstElementChild; svg.style.transformOrigin = "0 0"; svg.style.transform = `translate(${g.tx}px, ${g.ty}px) scale(${g.k})`; } }; const render = () => { left = drawLeft(); right = drawRight(); leftStage.replaceChildren(left); rightStage.replaceChildren(right); }; const commit = () => { clearTimeout(timer); timer = null; if (g.k === 1 && g.tx === 0 && g.ty === 0) return; const scale = w / (2 * mapState.half); // pixels per km right now const dx = (-g.tx / g.k + w / (2 * g.k) - w / 2) / scale, dy = (-g.ty / g.k + h / (2 * g.k) - h / 2) / scale; mapState.cx += dx; mapState.cy -= dy; mapState.half /= g.k; g = {tx: 0, ty: 0, k: 1}; render(); }; const soon = () => { clearTimeout(timer); timer = setTimeout(commit, 180); }; // Linked hover: pointing at a cell on either map outlines that polis on both maps and names it. // Each cell is tagged with its polis id (aria-label "polis 12"); a map leaves out cells that are off screen, so we look cells up by id. const names = new Map(mapCells.map(d => [String(d.properties.id), d.properties.t_name])), lookup = new WeakMap(); const topIds = new Set(top.map(d => String(d.id))); // these six already have a standing name on the left map const cellPath = (stage, id) => { const svg = stage.firstElementChild; if (!lookup.has(svg)) lookup.set(svg, new Map([...svg.querySelectorAll('path[aria-label^="polis "]')].map(p => [p.getAttribute("aria-label").slice(6), p]))); return lookup.get(svg).get(String(id)); }; const clearHighlight = () => { for (const s of stages) s.firstElementChild.querySelector("g.highlight")?.remove(); }; const highlight = id => { clearHighlight(); stages.forEach((stage, i) => { const svg = stage.firstElementChild, cell = cellPath(stage, id); if (!cell) return; const ns = "http://www.w3.org/2000/svg", layer = document.createElementNS(ns, "g"); layer.setAttribute("class", "highlight"); layer.setAttribute("pointer-events", "none"); const box = cell.getBBox(); for (const [stroke, width] of [["white", 5], ["#111", 2]]) { const outline = document.createElementNS(ns, "path"); outline.setAttribute("d", cell.getAttribute("d")); outline.setAttribute("fill", "none"); outline.setAttribute("stroke", stroke); outline.setAttribute("stroke-width", width); outline.setAttribute("stroke-linejoin", "round"); layer.append(outline); } if (!(i === 0 && topIds.has(String(id)))) { // name the polis on both maps (the six on the left already have a standing label) const label = document.createElementNS(ns, "text"); label.textContent = names.get(String(id)); for (const [name, value] of Object.entries({x: box.x + box.width / 2, y: box.y - 5, "text-anchor": "middle", "font-size": 12, "font-weight": 700, fill: "#111", stroke: "white", "stroke-width": 3, "paint-order": "stroke"})) label.setAttribute(name, value); layer.append(label); } svg.append(layer); }); }; for (const stage of stages) { stage.addEventListener("pointerover", e => { if (drag || e.target.tagName === "text") return; const tag = e.target.getAttribute?.("aria-label"); if (tag && tag.startsWith("polis ")) highlight(tag.slice(6)); else clearHighlight(); }); stage.addEventListener("pointerleave", clearHighlight); } for (const stage of stages) { stage.addEventListener("wheel", e => { e.preventDefault(); clearHighlight(); const r = stage.getBoundingClientRect(), px = e.clientX - r.left, py = e.clientY - r.top; const k = Math.min(mapState.half / HALF_MIN, Math.max(mapState.half / HALF_MAX, g.k * Math.exp(-e.deltaY * 0.002))), f = k / g.k; g.tx = px - (px - g.tx) * f; g.ty = py - (py - g.ty) * f; g.k = k; show(); soon(); }, {passive: false}); stage.addEventListener("pointerdown", e => { if (e.button) return; clearHighlight(); drag = {x: e.clientX, y: e.clientY}; const move = ev => { g.tx += ev.clientX - drag.x; g.ty += ev.clientY - drag.y; drag = {x: ev.clientX, y: ev.clientY}; show(); soon(); }; const up = () => { removeEventListener("pointermove", move); removeEventListener("pointerup", up); removeEventListener("pointercancel", up); drag = null; commit(); }; addEventListener("pointermove", move); addEventListener("pointerup", up); addEventListener("pointercancel", up); }); } invalidation.then(() => clearTimeout(timer)); const reset = html``; reset.onclick = () => { Object.assign(mapState, presets[mapView]); g = {tx: 0, ty: 0, k: 1}; render(); }; const panel = (title, hint, legend, stage) => html`

${title}

${hint}

${legend} ${stage}

`; return html`

Drag either map to move it and scroll to zoom. The other map moves with it, and hovering a polis on one map highlights it on both. ${reset}

${panel(adj ? "Observed minus expected staseis" : "Attested staseis, 500–300 BCE", adj ? "Compared with the count documentation alone predicts. Hover a cell to find the polis on both maps." : "One cell per polis, labeled for the six poleis with the most. Hover a cell to find the polis on both maps.", left.legend("color"), leftStage)} ${panel(fname, `ρ = ${v.rho < 0 ? "−" : "+"}${Math.abs(v.rho).toFixed(2)} with staseis (${v.rho_kind === "controlled" ? "prominence removed" : "raw"}). Grey = unknown (${unknown.length} of ${mapCells.length}).`, right.legend("color"), rightStage)}

`; }4f:T50c,{ const c = key => correlations.find(d => d.key === key); const r = key => c(key).controlled.toFixed(2); const walls = c("walls"), democracy = c("democracy"); return md`## Data Conclusion Finally, after looking at the ranking, the one-feature scatter plots and the map, the features that go with more staseis once documentation is held constant are **${c("colonies").name.toLowerCase()}** (ρ = ${r("colonies")}), **${c("victors").name.toLowerCase()}** (${r("victors")}), **${democracy.name.toLowerCase()}** (${r("democracy")}), **${c("proxenoi").name.toLowerCase()}** (${r("proxenoi")}) and **${c("silver").name.toLowerCase()}** (${r("silver")}). Those are the outward-facing, well-connected poleis. City walls, which looked related in the raw numbers (ρ = ${walls.raw.toFixed(2)}), drop to ${r("walls")}, and the places where it is doubtful that a polis existed at all (higher polisity codes) have slightly fewer staseis (${r("polisity")}). It is fairly important to note that these are moderate rank correlations, which describe an association and not a cause. Democracy is known for only ${democracy.n} poleis, and "no stasis" means none is attested, not that none happened. The expected-staseis model also shows that documentation explains a lot of the pattern by itself.`; } 50:Te18,features = [ // key matches the column names in polis.csv; the scale (log) and jitter for each feature come from Ben's FEATURES in analysis.json {key: "prom_1", name: "Prominence: HN text", axis: "Prominence: columns of text in HN", gloss: "Columns of text the Hansen–Nielsen inventory gives the polis (by 1/8 column), a proxy for how much evidence survives."}, {key: "prom_2", name: "Prominence: LGPN names", axis: "Named individuals in the LGPN", gloss: "Individuals the Lexicon of Greek Personal Names links to the polis. Known for a selection of 263 poleis."}, {key: "prom_3", name: "Prominence: histories", axis: "Mentions in ten political histories", gloss: "Times the city-ethnic appears in ten political and military histories. Known for a selection of 263 poleis."}, {key: "democracy", name: "Democracy", axis: "Democracy (1 none attested, 2 attested)", gloss: "Regime history: 1 = no evidence for democracy, 2 = democracy attested. Regime unknown (0) is treated as missing."}, {key: "colonies", name: "Colonies founded", axis: "Colonies founded", gloss: "Colonial foundations in which the polis was a founder or co-founder."}, {key: "victors", name: "Panhellenic victories", axis: "Panhellenic festivals won (0–4)", gloss: "Number of the four panhellenic festivals at which a citizen is known to have won."}, {key: "proxenoi", name: "Proxenoi", axis: "Proxenoi (0 none … 3 gave and received)", gloss: "Proxeny ties with other poleis: 0 none, 1 received, 2 granted, 3 both."}, {key: "area_1", name: "Territory size", axis: "Territory size (1 small … 7 large)", gloss: "Territory class from 1 (under 25 km²) to 7 (over 2,000 km²). Unknown (0) is treated as missing."}, {key: "area_2", name: "Intramural area", axis: "Intramural area (hectares)", gloss: "Area inside the walls in hectares, the usual population proxy. Known for about one polis in five."}, {key: "silver", name: "Silver coinage", axis: "Silver coinage (0 none … 3 by 500 BCE)", gloss: "When silver coins were first issued: 0 never, 1 in 399–300, 2 in 499–400, 3 by 500 BCE."}, {key: "bronze", name: "Bronze coinage", axis: "Bronze coinage (0 none … 3 by 500 BCE)", gloss: "When bronze coins were first issued, coded like silver."}, {key: "grid", name: "Grid plan", axis: "Grid plan (0 none … 4 by 7th c.)", gloss: "Grid-pattern city planning: 0 none, rising to 4 for plans attested by the 7th century BCE."}, {key: "walls", name: "City walls", axis: "City walls (0 / 1)", gloss: "1 = evidence the site was fortified."}, {key: "delian_l", name: "Delian League", axis: "Delian League member (0 / 1)", gloss: "1 = attested member of the 5th-century Athenian-led Delian League."}, {key: "koinon", name: "Koinon member", axis: "Koinon member (0 / 1)", gloss: "1 = member of a koinon (federal state) before 300 BCE."}, {key: "polisity", name: "Polisity", axis: "Polisity (1 certain … 3 doubtful)", gloss: "How certain it is that the place was a polis: 1 most certain, 3 least."}, {key: "hellenicity", name: "Hellenicity", axis: "Hellenicity (1 Greek … 3 non-Greek)", gloss: "How Greek the population was: 1 most Greek, 3 most 'barbarian'. Unknown (0) is treated as missing."}, {key: "elevation_m", name: "Elevation", axis: "Elevation (m)", gloss: "Elevation at the recorded location, in metres."}, {key: "latitude", name: "Latitude", axis: "Latitude (°N)", gloss: "Latitude of the recorded location."}, {key: "longitude", name: "Longitude", axis: "Longitude (°E)", gloss: "Longitude of the recorded location."} ] 51:T918,function scatterPlot(f, {width: w = 800, height = 480, small = false, seed = 11, title} = {}) { const tx = v => (f.log ? Math.log1p(v) : v); const unif = d3.randomUniform.source(d3.randomLcg(seed)); // seeded, so the jitter never changes const jitterX = f.jitter ? unif(-f.jitter, f.jitter) : () => 0, jitterY = unif(-0.04, 0.04); const pts = polis.filter(d => d[f.key] != null).map(d => { const x = tx(d[f.key]), y = Math.log1p(d.staseis); return {name: d.name, region: d.region, staseis: d.staseis, value: d[f.key], x, y, xj: x + jitterX(), yj: y + jitterY()}; }); const values = [...new Set(pts.map(p => p.value))].sort(d3.ascending); const discrete = values.length <= 8; const [x0, x1] = d3.extent(pts, p => p.xj), pad = (x1 - x0) * 0.04 || 0.5; const logTicks = (small ? [0, 1, 10, 100, 1000] : [0, 1, 2, 5, 10, 20, 50, 100, 200, 500, 1000, 2000, 5000]).map(tx); const ticks = discrete ? values.map(tx) : f.log ? logTicks.filter(t => t >= x0 - pad && t <= x1 + pad) : undefined; const top = [...pts].sort((a, b) => b.staseis - a.staseis).slice(0, 6); return Plot.plot({ title, width: w, height, marginTop: small ? 8 : 20, marginRight: 14, marginBottom: small ? 42 : 52, marginLeft: small ? 34 : 56, style: {fontWeight: 600, fontSize: small ? "10.5px" : "13px"}, x: {label: f.axis, domain: [x0 - pad, x1 + pad], ticks, tickFormat: f.log ? t => (Math.round(Math.expm1(t) * 100) / 100).toLocaleString("en") : undefined}, y: {label: small ? null : "↑ Attested staseis", domain: [-0.2, Math.log1p(23)], ticks: [0, 1, 2, 5, 10, 20].map(v => Math.log1p(v)), tickFormat: t => Math.round(Math.expm1(t)), grid: true}, marks: [ Plot.dot(pts, {x: "xj", y: "yj", r: small ? 2.3 : 3.5, fill: palette.blue, fillOpacity: small ? 0.4 : 0.45}), Plot.linearRegressionY(pts, {x: "x", y: "y", ci: 0.95, stroke: palette.red, strokeWidth: small ? 2 : 2.5}), small ? null : Plot.text(top, {x: "xj", y: "yj", text: "name", dy: -9, fontSize: 11}), small ? null : Plot.text([`r = ${f.r.toFixed(2)} · n = ${f.n}`], {text: d => d, frameAnchor: "top-left", dx: 8, dy: 6, fontSize: 13}), Plot.tip(pts, Plot.pointer({x: "xj", y: "yj", title: d => `${d.name}\n${d.region}\n${f.name}: ${d.value}\nStaseis: ${d.staseis}`})) ].filter(Boolean) }); } 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47:{"id":"62c60bff0a551b55","slug":"polis-data","title":"What Drives Stasis Among the Greek Poleis?","thumbnail":"8412f703cc201bd4f0df2ab24911cab76336ceaeb6bf816ac0848b5dc1ad64b2","access_level":"public","create_time":"$D2026-10-26T04:39:47.176Z","update_time":"$D2026-10-26T17:16:50.745Z","view_time":null,"first_public_time":"$D2026-10-26T16:28:22.988Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"6892435a406ffad9","login":"thomas-butcher","name":"Thomas Butcher","avatar_url":"https://avatars-next.observableusercontent.com/29c8bc8df0eb2be218365ecfea2a967467e030183be3eb4ad91ce9ce087ae457","tier":"starter_2024","bio":"","followed_by_you":false,"follows_you":false},"version":227,"publish_version":227,"role":null,"authored":false,"authors":[{"type":"individual","id":"5279211d076af583","login":"thomas-butcher","name":"Thomas Butcher","avatar_url":"https://avatars-next.observableusercontent.com/29c8bc8df0eb2be218365ecfea2a967467e030183be3eb4ad91ce9ce087ae457","tier":null,"bio":"","followed_by_you":false,"follows_you":false}],"members":[{"type":"team","id":"6892435a406ffad9","login":"thomas-butcher","name":"Thomas Butcher","avatar_url":"https://avatars-next.observableusercontent.com/29c8bc8df0eb2be218365ecfea2a967467e030183be3eb4ad91ce9ce087ae457","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"What Drives Stasis Among the Greek Poleis?","cells":[{"id":2,"value":"# What Drives Stasis Among the Greek Poleis?\n\nAuthors: Thomas Butcher and Benjamin Barlog","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3,"value":"$4b","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4,"value":"# Final Plots\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"### Which features go with stasis?\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":6,"value":"$4c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":8,"value":"{\n const [a, b, c] = correlations;\n const walls = correlations.find(d => d.key === \"walls\");\n const democracy = correlations.find(d => d.key === \"democracy\");\n const r = d => d.controlled.toFixed(2);\n return md`This plot shows how strongly each feature tracks attested staseis. Each row is one feature. The orange dot is its raw rank correlation, and the blue dot is the same correlation after removing how well documented the polis is (the number of columns of text it gets in Hansen and Nielsen, \\`prom 1\\`). The line between them shows how much that adjustment matters. With documentation held constant, **${a.name}** (ρ = ${r(a)}), **${b.name}** (${r(b)}) and **${c.name}** (${r(c)}) are the strongest. City walls look related in the raw numbers (ρ = ${walls.raw.toFixed(2)}) but fall to ${r(walls)} once documentation is removed, so walls mostly reflect how well documented a polis is. Democracy is known for only ${democracy.n} of the ${polis.length.toLocaleString()} poleis, so read its row with care.`;\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":10,"value":"### One feature at a time\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":11,"value":"viewof featureChoice = Inputs.select(\n [...featureStats].sort((a, b) => d3.descending(a.r, b.r)),\n {\n label: \"Plot staseis against\",\n format: f => `${f.name} (r ${f.r < 0 ? \"−\" : \"+\"}${Math.abs(f.r).toFixed(2)})`,\n value: featureStats.find(f => f.key === \"democracy\")\n }\n)\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":12,"value":"explorer = scatterPlot(featureChoice, {\n width: Math.min(width, 900),\n height: 480,\n title: `Attested staseis against ${featureChoice.name}`\n})\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":13,"value":"md`This plot shows every polis with a known value for **${featureChoice.name}** (${featureChoice.n} of ${polis.length.toLocaleString()}) against its attested staseis. ${featureChoice.gloss} The red line is the least-squares fit of log(1 + staseis) with a 95% band, and r = ${featureChoice.r.toFixed(2)} is the Pearson correlation. The y axis is log-scaled but labeled in raw counts. Dots are nudged apart slightly so stacked whole numbers stay visible, while the line is fitted to the true values. Hover a dot for the polis; the six poleis with the most staseis are labeled.`\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":15,"value":"### Every feature at a glance\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":16,"value":"gallery = {\n const cols = width > 900 ? 4 : width > 640 ? 3 : 2, gap = 14;\n const w = (Math.min(width, 1000) - gap * (cols - 1)) / cols;\n const ranked = [...featureStats].sort((a, b) => d3.descending(a.r, b.r));\n const panel = f => html`

${f.name}

r = ${f.r.toFixed(2)} · n = ${f.n}

\n ${scatterPlot(f, {width: w, height: 200, small: true})}\n

`;\n return html`

${ranked.map(panel)}

`;\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":18,"value":"This plot shows all twenty features against attested staseis in one view, with the most positively correlated first. Each panel is the same chart as above, so you can scan for a clear upward slope, a narrow band and a large n.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":19,"value":"### How much stasis would documentation alone predict?\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":20,"value":"$4d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":21,"value":"{\n const {coef, aic} = analysis.model;\n return md`This plot shows every polis as a dot, with the orange line marking the number of staseis a polis would be expected to have from its documentation alone. A polis above the line has more attested staseis than its documentation would lead us to expect; a polis below it has fewer. The line is a Poisson regression of staseis on log(prom 1) and its square (the squared term stops the model from predicting about 31 staseis for Athens), fitted on all ${polis.length.toLocaleString()} poleis: log(expected) = ${coef.c} + ${coef.lp}·log(prom 1) − ${Math.abs(coef.lp2)}·log(prom 1)², AIC ${aic}. Both axes are log-scaled and labeled in raw counts. The map's second dot mode shows this same gap.`;\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":22,"value":"### Where does stasis cluster?\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":49,"value":"viewof mapFeature = Inputs.select(mapData.meta.order, {\n label: \"Right map shows\",\n value: mapData.meta.default,\n format: k => {\n const rho = mapData.meta.vars[k].rho;\n return `${features.find(f => f.key === k)?.name ?? mapData.meta.vars[k].col} (ρ ${rho < 0 ? \"−\" : \"+\"}${Math.abs(rho).toFixed(2)})`;\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":50,"value":"viewof mapMode = Inputs.radio([\"Attested staseis\", \"Observed − expected staseis\"], {label: \"Left map shows\", value: \"Attested staseis\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":51,"value":"viewof mapView = Inputs.radio([\"Greek world\", \"Aegean\", \"Everything\"], {label: \"View\", value: \"Greek world\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":52,"value":"$4e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":24,"value":"These two maps show the same polis cells side by side. The left map is colored by attested staseis (or, with the other choice, by how far each polis sits above or below the count its documentation predicts). The right map is colored by whichever feature you pick, so you can look for places where the two maps light up together. Drag either map to move it and scroll to zoom: the other map always moves with it, so the same place stays side by side. Hovering a polis on either map outlines and names it on both, so you can find the same place on the other map. Each map shows one thing, and grey on the right map means the value is unknown, not low. A cell is only the land nearer to that polis than to any other, capped at 60 km from its site, so it shows where the polis is and not the extent of its real territory. The cells, colors and expected counts come from Ben's `build_map.py`.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":25,"value":"### Look up a polis\n\nSearch by name or region, and sort any column. A blank means the value is unknown in the dataset.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":26,"value":"viewof polisQuery = Inputs.search(polis, {placeholder: \"Find a polis or region…\", columns: [\"name\", \"region\"], spellcheck: false})\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":27,"value":"Inputs.table(polisQuery, {\n columns: [\"name\", \"region\", \"staseis\", \"expected\", \"prom_1\", \"democracy\", \"colonies\", \"area_2\"],\n header: {name: \"Polis\", region: \"Region\", staseis: \"Staseis\", expected: \"Expected\", prom_1: \"Prominence\", democracy: \"Democracy\", colonies: \"Colonies\", area_2: \"Area (ha)\"},\n format: {expected: d => (d == null ? \"\" : d.toFixed(1)), prom_1: d => (d == null ? \"\" : d.toFixed(2))},\n sort: \"staseis\",\n reverse: true,\n rows: 14,\n maxWidth: 900\n})\n","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":28,"value":"$4f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":40,"value":"## Data and helpers\n\nEverything below this line loads the data and defines the helpers the plots above use. The files come from Ben's Python code through `export_observable_data.py`, which calls his functions and does not change them. His cleaning follows the codebook: a `0` that means \"unknown\" (Hellenicity, Democracy, area 1) becomes missing; a blank that means \"never issued\" (Silver, Bronze, Grid, Koinon) becomes `0`; the century codes for coinage and grid plans are re-ranked so each step is one rung; and a Grid code of 1, which the codebook does not define, is treated as unknown.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":41,"value":"polis = FileAttachment(\"polis.csv\").csv({typed: true})\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":42,"value":"analysis = FileAttachment(\"analysis.json\").json()\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":43,"value":"mapData = FileAttachment(\"map.json\").json()\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":44,"value":"palette = ({\n blue: \"#4e79a7\", // the blue used for points in my other notebooks\n orange: \"#f28e2b\",\n red: \"#e15759\",\n green: \"#59a14f\",\n grey: \"#bbb\",\n land: \"#eeeae3\" // the land color from the Alaska gas price map\n})\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":45,"value":"$50","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":46,"value":"featureStats = features.map(f => ({...f, ...analysis.features[f.key]})) // adds Ben's r, n, log and jitter for each feature\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":47,"value":"correlations = analysis.correlations.map(c => ({...c, name: features.find(f => f.key === c.key).name})) // Ben's ranking, strongest first\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":48,"value":"$51","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":53,"value":"mapCells = {\n // Ben's Voronoi cells (km, clipped to land and to 60 km), each carrying that polis's row from build_map.py\n const byId = new Map(mapData.dots.map(d => [d.id, d]));\n return mapData.cells.features.map(f => ({...f, properties: byId.get(f.properties.id)}));\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":54,"value":"mapState = ({view: null, cx: 0, cy: 0, half: 2050}) // where both maps are looking: center in km and half the width shown (the map cell updates it as you pan and zoom)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W52","stdlib":"2"}} 24:null