);
}
/* ── Funnel Stage ── */
function FunnelStage({ count, label, note, width, last }) {
return (
{count}
{label}
{note &&
{note}
}
);
}
/* ══════════ MAIN METHODOLOGY VIEW ══════════ */
function MethodologyView({ onOpenPerson }) {
var [weights, setWeights] = React.useState(window.SCORING.DEFAULT_WEIGHTS);
var result = React.useMemo(function () {
/* Normalize weights to sum 1.0 for compute */
var sum = Object.values(weights).reduce(function (a, b) { return a + b; }, 0) || 1;
var norm = {};
Object.keys(weights).forEach(function (k) { norm[k] = weights[k] / sum; });
return window.SCORING.compute(norm);
}, [weights]);
var rawSum = Object.values(weights).reduce(function (a, b) { return a + b; }, 0);
var rawPct = Math.round(rawSum * 100);
function setW(key, v) {
setWeights(function (p) { var n = Object.assign({}, p); n[key] = v; return n; });
}
function reset() { setWeights(window.SCORING.DEFAULT_WEIGHTS); }
var top30 = result.scored.slice(0, 30);
var defaultResult = window.SCORING.getDefault();
var defaultOverlap = defaultResult.overlap.inTop30;
var curOverlap = result.overlap.inTop30;
var overlapDelta = curOverlap - defaultOverlap;
var lastGen = new Date(window.COHORT.lastUpdated);
return (
{/* ── Hero ── */}
How we rank cohort members
A three-layer filter plus ML-inspired scoring, modeled on the multi-stage structure of X's open-source For You algorithm. Five interpretable signals, hand-tunable weights — not a black box.
{top30.map(function (s, i) {
var isExt = !!s.m.external;
return (
{i + 1}@{s.m.handle}{s.priorityScore.toFixed(2)}
);
})}
{/* ── Why These 5 ── */}
Why these five, not others
Each dimension answers one concrete question Howard asks when sizing up a target. We deliberately left out signals that look sophisticated but don't fit this problem:
{[
['Time-of-day decay', 'cohort posts ~94/day — too sparse and noisy for hourly weighting'],
["Personalized to Howard's history", "system limit — we don't know who Howard has replied to or read"],
['Policy / spam signals', "can't judge, and shouldn't predict block/mute — that's Howard's call"],
['Account age / seniority', 'xAI hired en masse in 2023–24, so signup date is uncorrelated with quality'],
].map(function (x) {
return (
✗{x[0]}{x[1]}
);
})}
{/* ── CANNOT do ── */}
What this score cannot do
{[
['Predict who will reply to Howard', 'engagement depends on his content, timing, network effects'],
['Guarantee high-scorers will hire', "it's an outreach-efficiency ranking, not a fit prediction"],
['Replace domain expertise', 'manual override is always allowed — bump anyone you know personally'],
['Stay accurate forever', 'cohort drifts — retune the weights roughly every 2 weeks'],
].map(function (x) {
return (
−{x[0]}{x[1]}
);
})}
Last generated: {lastGen.toLocaleString('sv-SE', { timeZone: 'Asia/Taipei', year: 'numeric', month: '2-digit', day: '2-digit', hour: '2-digit', minute: '2-digit' })} UTC+8 · Data freshness: 7d · {result.funnel.active} active · 2,825 tweets