免责声明 · 实验性项目。本文全部「明」分与结论,均由大语言模型自动生成,并非人工专家评定,亦无可对照的标准答案。分数可能包含事实错误,不构成对任何真实个人之品格、能力或价值的权威判断,可能与真实情况不符,仅供研究与探索之用。Disclaimer · Experimental project. Every lucidity score and conclusion here is generated automatically by a large language model — not assessed by human experts, and with no ground-truth answer key. Scores may contain factual errors, are not authoritative judgments of any real individual's character, ability, or worth, may diverge from reality, and are offered for research and exploration only.
Institute of Lucidity · Working Paper · 2026
明,可测:一把结局盲、免效标、跨领域的判断力之尺 Lucidity, Made Measurable: An Outcome-Blind, Criterion-Free Cross-Domain Scale of Judgment
给牛顿、拿破仑与苏格拉底同一把尺 One Ruler for Newton, Napoleon, and Socrates
√(理 × 玄) · 几何平均后归一到 0–100√(Pattern × Mystery) · geometric mean rescaled to 0–100
摘要Abstract
领导者的判断力,即其对现实的清醒程度,被上层梯队理论视为核心变量,却长期难以直接测量:领域内的硬指标(被引数、战功、市值)虽精确却无法跨域通兑;跨域代理量(名气)所测的是命运的回声而非心智;任何在知道结局之后所作的评估都与事后之明相纠缠。更根本的是,判断力没有标准答案(ground truth),这使"对效标计算准确率"这一传统验证路径整个失效。有鉴于此,本文的贡献是一把尺,而非一个预测。(一)构念:明 = 理⊗玄,分解为六条可操作的计分轴,可与智慧、元认知等相邻构念相判别。(二)仪器:评分由 LLM 仅凭公开传记、只据当时可得信息作出,受非道德防火墙与揭名前剥离身份的反光环条款两条铁律约束,从而使清醒结局盲、身份盲、且跨领域可算——牛顿与拿破仑得以落在同一把可通兑的尺上。(三)免效标验证,亦即方法论核心:在没有 ground truth 时,如何严谨地为一把尺辩护?本文示范一套不对答案的验证组合——覆盖度、结构(有效维数≈2)、信度(ICC 0.73–0.93 单评审,平均可达 0.98)、不变性(揭名与盲评各轴 Δ≤0.15)、判别(表面特征仅解释明的 9%)与信息(理、玄各留约 27–37% 独立方差)——另附三场预先设定实验。语料为 459 位跨领域领导者。本文旨在为上层梯队与领导者认知研究补上一件此前缺失的测量工具,使一批过去仅凭传记无从开展的纵向、跨域、控事后之明的研究成为可能。
Leaders' judgment — their lucidity about the situations they act in — is a core variable in upper-echelons theory, yet has resisted direct measurement: within-domain hard metrics (citations, victories, market capitalization) are precise but not portable; cross-domain proxies such as fame measure the echo of fate rather than the mind; and any assessment made after the outcome is known is entangled with hindsight. More fundamentally, judgment has no ground truth, which voids the conventional "score accuracy against a criterion" route to validation. This paper's contribution is accordingly a ruler, not a prediction. (1) Construct: lucidity is defined as Pattern ⊗ Mystery, decomposing into six operational axes, discriminable from adjacent constructs such as wisdom and metacognition. (2) Instrument: a large language model scores each figure from public biography using only then-available information, under a non-moral firewall and an anti-halo clause that strips identity before scoring, making lucidity outcome-blind, identity-blind, and cross-domain computable — so Newton and Napoleon land on one commensurable ruler. (3) Criterion-free validation, the methodological core: how does one defend a ruler with no ground truth? We demonstrate a suite that never scores against an answer key — coverage, structure (effective dimensionality ≈ 2), reliability (ICC 0.73–0.93 single-rater, up to 0.98 averaged), invariance (named − blind Δ ≤ 0.15 per axis), discriminant validity (surface features explain only 9% of the score), and information (the two sub-dimensions each retain 27–37% independent variance) — plus three pre-specified experiments. The corpus comprises 459 cross-domain leaders. For upper-echelons and leader-cognition research, the paper supplies a missing measurement instrument, enabling longitudinal, cross-domain, hindsight-controlled studies that biography alone could not support.
关键词: 领导者判断力 · 认知准确性 · 量表开发 · 免效标验证 · 结局盲测量 · 上层梯队理论 · LLM 评审 · 判别效度Keywords: leader judgment · cognitive accuracy · scale development · criterion-free validation · outcome-blind measurement · upper-echelons theory · LLM-as-judge · discriminant validity
AI 使用披露。构念、评分细则、方案、验证设计、结果解读与论证,均为作者之工作;作者审阅并核验产出,并对全部主张负责。大语言模型充当评审,依该方案自公开传记对各人物评分,并协助起草行文、表格、图示与分析代码。由此产生两项局限,均按第一等级对待。其一,由于评分现由单一模型族产出,验证证据所确立者为内部一致性,而非与人类评审或跨模型族之收敛性;弥合此缺口(跨模型族重评 + 人评 ICC)是研究议程的最高优先项(见 §7,R4)。其二,量化结果承袭底层模型自身所带的任何偏差。
AI-use disclosure. The construct, scoring rubric, protocol, validation design, interpretation, and argument are the authors' work; the authors reviewed and verified the outputs and are responsible for all claims. A large language model acts as the rater, scoring each figure from public biography under that protocol, and assisted in drafting prose, tables, figures, and analysis code. Two limitations follow and are treated as first-class. First, because a single model family currently produces the scores, the validation evidence establishes internal consistency rather than convergence with human raters or across model families; closing that gap (cross-family re-scoring and human-rater ICC) is the highest-priority item on the research agenda (§7, R4). Second, the quantitative results inherit whatever biases the underlying model carries.
核心发现Highlights
核心发现(先给结论)Highlights
本节把结论压缩到三分钟可读完。前三条是本文的贡献(构念 / 仪器 / 免效标验证);第四条是"这把尺行为合理"的旁证,非主张。The argument in brief. The first three points are the paper's contributions: construct, instrument, and criterion-free validation; the fourth is corroboration that the ruler behaves sensibly, and is deliberately not a claim.
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构念:判断力可被操作化,明 = 理⊗玄。 清醒并非一团模糊的"贤能",而是可分解为六条计分轴(理含见微知远、破执自知、去伪存真,玄含据实置信、知止有界、存玄留白),由此得到一个跨领域、且可与智慧、元认知等相邻构念相判别的判断力定义。有效维数约为 2,理与玄各留 27–37% 的独立方差,可见二者是两个真实而半独立的子维度,而非同一维度的两个名字。
The construct: judgment can be operationalized. Lucidity is not one blurry "merit." It decomposes into six scored axes (Pattern: Consequential Foresight, Ego Undistortion, Signal Discrimination; Mystery: Confidence Calibration, Boundedness Awareness, Irreducibility Reverence), giving a cross-domain definition of judgment discriminable from adjacent constructs such as wisdom and metacognition. Effective dimensionality is ≈ 2, and Pattern and Mystery each retain 27–37% independent variance, so the two are real, semi-independent sub-dimensions rather than two names for one.
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仪器:这把尺结局盲、身份盲、跨领域可算。 评分由 LLM 仅凭公开传记、只据当时可得信息作出,并受两条铁律约束(非道德防火墙,以及揭名前统一剥离身份的反光环条款)。牛顿与拿破仑由此首次落在同一把尺上。表面特征仅能解释明的 9%,揭名与盲评之间各轴漂移不超过 0.15 分,说明显性身份与光环线索基本未进入分数,而这正是一把"结局盲"尺得以成立的前提(据行为事实再识别是另一条尚未检验的通道,见议程 R-ID)。
The instrument: the ruler is outcome-blind, identity-blind, and cross-domain computable. A language model scores from public biography using only then-available information, under a non-moral firewall and an anti-halo clause that strips identity before scoring. Newton and Napoleon thus land on the same ruler at last. Surface features explain only 9% of the score and named-minus-blind drift is ≤ 0.15 points per axis, so explicit identity and halo cues essentially do not enter, which is the precondition for an outcome-blind ruler (re-identification from conduct facts is a separate, untested channel; agenda R-ID).
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免效标验证(方法论核心):无标准答案,仍能严谨立尺。 判断力没有 ground truth,一切"对效标算准确率"的路径由此失效。本文改用一套不对答案的验证组合,涵盖覆盖度、结构(有效维数≈2)、信度(ICC 0.73–0.93 单评审,平均可达 0.98)、不变性(揭名与盲评 Δ≤0.15)、判别(表面特征仅解释 9%)与信息(理、玄各留 27–37% 独立方差),另附三场预先设定实验。这套"无效标验证范式"对整个 LLM-as-judge 家族均有普适意义,是本文可移植性最强的贡献。
Criterion-free validation: with no answer key, a ruler can still be defended. Judgment has no ground truth, so every "score accuracy against a criterion" route fails. We use instead a suite that never scores against an answer key: coverage, structure (effective dimensionality ≈ 2), reliability (ICC 0.73–0.93 single-rater, up to 0.98 averaged), invariance (named − blind Δ ≤ 0.15), discriminant validity (surface features only 9%), and information (the sub-dimensions each retain 27–37% independent variance), plus three pre-specified experiments. This paradigm generalizes to the whole LLM-as-judge family and is the paper's most transferable contribution.
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(旁证,非主张)这把尺行为合理:与领导者结局呈结构化关联。 作为构念效度的 nomological 网,其结构主梁是建制力,对个人善终与事业存续两端皆最强;唯一承重的解离是术偏业,它在命名、盲评、及客观三种口径下一致。此外,一支"明偏个人终局"的倾向仅在结局盲重评下浮现(R2,附录 E),且不穿透纯客观结局代理(R3a,附录 F,只余方向性),故为后续工作的线索而非本文所倚仗者。这些关系仅佐证"尺量到了真东西",并不构成"明预测结局"的主张;完整回归见 §5、表 1、表 2 及附录 D、E、F。
(Corroboration, not a claim.) As a nomological net for construct validity, the structural spine is institution-building, strongest at both personal survival and organizational survival, and the one weight-bearing dissociation is that skill is enterprise-tilted across named, blind, and objective coding alike. A further tilt of lucidity toward personal fate appears only under the outcome-blind rescore (R2, App. E) and does not survive purely objective outcome proxies (R3a, App. F, directional only), so it is a lead for future work rather than a result relied on. These relations corroborate that the ruler measures something real; they do not amount to a claim that lucidity predicts outcomes (full regressions in §5, Tables 1 and 2, and Apps. D, E, F).
一句话概括: 本文造出并验证了一把测量"判断力/清醒"的尺,使一个公认关键、却历来只能借事后光环谈论的东西,变得可测、可比,且在没有标准答案时仍可验证;它与结局的关系只是旁证其行为合理,而非论点本身。
In a sentence. We build and validate a ruler for judgment, taking a thing everyone calls central, yet historically discussable only through the halo of hindsight, and making it measurable, comparable, and open to falsification even without an answer key. Its relationship to outcomes is a sanity check, not the thesis.
§1
问题:判断力人人称关键,却没有一把干净的尺The Problem: Everyone Calls Judgment Decisive, and No One Can Measure It
领导者的成败,人人归因于"判断力",然而判断力至今仍没有一把干净的尺。领域内的硬指标无法跨域,跨域的名气所测的是命运回声,任何在知道结局之后所作的评估又都与事后之明相纠缠,而判断力本身更没有标准答案。其结果是,判断力只能被"事后谈论",却不能被"事前测量"。下面两幅肖像并非要证明什么,而是要把这道缺口摆到台面上:才华与判断本是两样东西,要谈判断,须先有一把只量判断、而不偷看结局的尺。
拿破仑。 就纯粹才具而言,他几乎无人可比:他重构了法国的行政、法律与财政,《民法典》历两个世纪仍在欧洲大部运行,本文量表上他的术高达 89(峰值 90)。然而同一个人,却在 1812 年不顾谏阻远征俄国、六十万大军尽丧,继而在滑铁卢重蹈覆辙,两度退位,客死圣赫勒拿(个人善终 = 28)。图谱评注一语中的:那是"清醒的失败,而非能力的失败"。俄国与滑铁卢阶段他的术仍维持在 72 至 82,真正塌掉的是明(峰值约 79,俄国阶段一度跌至 16)。他所缔造的制度得以存续(事业存续 = 70),他本人却未能善终。
华盛顿。 他的才具远不及拿破仑,入池条目上其术仅为 58,史料称他"屡战屡败却保全军队,以耐力而非战术天才拖垮英军"。但他在能够称王之处主动交权、两届而止(明 ≈ 84),善终读数满格(个人善终 = 96),所立之事业亦得长存(事业存续 = 96)。图谱评注称:"全场最高的善终读数,属于那个权术不算顶尖、克制却顶格的人。"
这道缺口。 两人的才华判若云泥(89 对 58),而其明恰恰反向分野(约 64 对 84);本文所问的是,一把尺能否在不靠结局倒推的前提下,登记出这第二道落差。才具,终究担保不了一个人如何收场。问题在于,若没有一把不靠结局倒推的尺,"华盛顿比拿破仑清醒"这句话就永远只是一则事后感想,既无法被独立测量,也无法跨域比较或加以证伪。本文因此不去预测谁会成功,而是先造一把量判断力的尺,并证明它量到了真东西。两幅肖像只是动机,而非证据;它们与结局的关系(才华偏业、清醒偏命)留待 §5 作为"这把尺行为合理"的旁证,而非本文论点本身。
两幅肖像并非特例。 把镜头拉宽到横跨四域的十二人,同一模式依旧成立(图 1):声望把术压向高端(全样本术均 84.5、标准差 12.2、幅域 30–99,而明的散布更宽,均 62.3、标准差 18.2),而明则铺满整个量程。牛顿 43 与达尔文 84 同属一流科学家;亚历山大 28 与成吉思汗 73 同为不败之征服者。术只是入图的入场券,真正变化的是明,且它在科学、战争、治国、商业各域之间以同一根轴分野——这正是一把跨域尺的全部要义。
A leader's success or failure is universally attributed to "judgment," and yet judgment still has no clean ruler. Within-domain hard metrics are not portable, cross-domain fame measures the echo of fate rather than the mind, any assessment made after the outcome is known is entangled with hindsight, and judgment itself has no ground truth. Judgment, in short, can be discussed after the fact but not measured before it. The two portraits below are not evidence of anything; they simply put the gap on the table. Talent and judgment are different things, and to speak of judgment one first needs a ruler that measures judgment alone, without looking ahead to how the story ends.
Napoleon. In raw ability almost no one compares. He rebuilt France's administration, law, and finance, and the Code civil still runs across much of Europe two centuries later; on this paper's scale his skill is 89 (peak 90). Yet the same man marched on Russia in 1812 against all counsel, lost six hundred thousand men, repeated the error at Waterloo, abdicated twice, and died in exile on St. Helena with a great deal of time to reconsider (personal survival = 28). The atlas annotation puts it exactly: this was "a failure of lucidity, not a failure of ability." His skill was intact throughout, still 72–82 in the Russia and Waterloo phases; what collapsed was lucidity (peak ≈ 79, down to 16 in the Russia phase). The institutions he built survived (organizational survival = 70); he did not.
Washington. He was far less gifted: his pooled-entry skill is only 58, and the record describes a man who "lost battle after battle yet kept his army intact, wearing the British down through endurance rather than tactical genius." But he handed back power where he could have kept it, stopping at two terms (lucidity ≈ 84). His personal ending is at the ceiling (personal survival = 96), and his enterprise endures too (organizational survival = 96). As the annotation notes, the highest personal-survival reading in the whole field belongs to the man whose statecraft was not top-tier but whose restraint was.
The gap. The two men's talent diverges sharply (89 vs 58), while their lucidity diverges the other way (≈ 64 vs 84); the question this paper asks is whether a ruler can register that second gap without reasoning back from how each life ended. Talent, it turns out, guarantees nothing about how a life ends. The difficulty is that, without a ruler that does not reason backward from the outcome, "Washington was more lucid than Napoleon" is forever just hindsight: impossible to measure on its own terms, compare across domains, or falsify. This paper therefore does not try to predict who will succeed; it first builds a ruler for judgment and shows that the ruler measures something real. The portraits are motivation, not evidence; their relation to outcomes (skill enterprise-tilted, lucidity fate-tilted) is deferred to §5 as a sanity check on the ruler, not as the headline.
The two portraits are not a special case. Widen the lens to a dozen figures across four domains, and the pattern holds (Figure 1): eminence compresses skill toward the high end (the full corpus averages skill 84.5, SD 12.2, and runs 30–99, versus lucidity's wider spread at mean 62.3, SD 18.2), while lucidity fans out across the whole range. Newton at 43 and Darwin at 84 are both first-rank scientists; Alexander at 28 and Genghis at 73 are both undefeated conquerors. Skill is the threshold for entering the atlas at all; lucidity is what actually varies, and it varies across domains on one shared axis, which is the entire point of a cross-domain ruler.
§2
构念:清醒是什么(明 = 理 ⊗ 玄)The Construct: What Lucidity Is
定义。 明 = 理 Pattern(λ) ⊗ 玄 Mystery(ξ),取几何平均 √(理·玄)·100。其中理衡量世界模型的准确程度,玄衡量与不可知边界相处的准确程度,两支各含三条 0–5 计分轴:
Definition. Lucidity, written 明 in the source rubric, is the product of two capacities: Pattern (理), how accurately one models the world, and Mystery (玄), how well one keeps company with the parts of the world that cannot be modeled. Formally, lucidity is the geometric mean of the two, √(Pattern×Mystery) rescaled to 0–100, and each branch carries three axes scored 0–5:
- 理 Pattern: 见微知远(secondOrderSight,预见自身决策的连锁后果,只据当时推理)· 破执自知(egoUndistortion,对自身能力/边界评估的准确度,非谦逊)· 去伪存真(signalDiscrimination,从噪声辨真规律)。Pattern: Consequential Foresight (foreseeing the knock-on consequences of one's own decisions, reasoning only from contemporaneous information) · Ego Undistortion (accuracy of assessing one's own ability and limits, not modesty) · Signal Discrimination (telling real regularity from noise).
- 玄 Mystery: 据实置信(calibratedUncertainty,信心随证据)· 知止有界(boundednessAwareness,对框架适用边界的清醒)· 存玄留白(irreducibilityReverence,让不可化约的内核悬置而非伪收口)。Mystery: Confidence Calibration (confidence tracking evidence) · Boundedness Awareness (lucidity about the boundary of a framework's applicability) · Irreducibility Reverence (letting the irreducible core remain suspended rather than forcing a false closure).
乘积规则意味着,任一因子归零则明亦归零,正所谓"自以为看透一切者,恰恰不明"。故明并非六轴之和,而是"看得准"与"知道自己看不准之处"这两种能力的交积。
结构:不是一团,而是两个半独立的子维度。 有效维数约为 2;理与玄虽高度相关(r ≈ 0.80),却各自保留 27–37% 的相互独立方差。可见理与玄是两个真实而半独立的子维度,而非同一维度的两个名字。这一判断由附录 A 与 §4 的验证证据所支撑。
The product rule means that if either factor goes to zero, lucidity goes to zero, because "one who believes he sees through everything is precisely the one who is not lucid." Lucidity is thus not a sum of six axes but the product of two capacities: seeing accurately, and knowing where one cannot see.
Structure: not one blob but two semi-independent sub-dimensions. Effective dimensionality is ≈ 2. Pattern and Mystery are highly correlated (r ≈ 0.80) yet each retains 27–37% mutually independent variance, so they are genuinely two sub-dimensions rather than two names for one, a claim supported by the validation evidence in App. A and §4.
2.1与相邻构念的关系(判别效度)Relation to Adjacent Constructs (Discriminant Validity)
明并非全新之物,其六轴各与既有构念高度相关。本文的楔子不在于"发现新维度",而在于测量方式:现有构念几乎都以自评或下属评分测得,因而受印象管理、社会赞许以及评估者已知结局的污染;明则从公开传记行为推断,且对身份与结局双盲。正是这一点,使它得以规避事后之明,并在牛顿与拿破仑之间实现跨域通兑。
Lucidity is not wholly new; each of its six axes correlates strongly with an existing construct. The wedge is not "a new dimension" but the mode of measurement. Existing constructs are almost all measured by self-report or subordinate rating, and are thereby contaminated by impression management, social desirability, and the rater's knowledge of the outcome. Lucidity, by contrast, is inferred from public biographical behavior and is blind to both identity and outcome, which is the source of its hindsight-resistance, and of its ability to put Newton and Napoleon on the same axis at all.
| 明轴(理/玄)Axis (branch) | 最近相邻构念Nearest construct | 既有测法Existing measurement | 明的判别性差异Lucidity's distinguishing move |
|---|---|---|---|
| 见微知远(理)Consequential Foresight secondOrderSight · Pattern |
战略预见 · 二阶思考(Tetlock 2005;Tetlock & Gardner 2015)Strategic foresight · second-order thinking (Tetlock 2005; Tetlock & Gardner 2015) | 预测赛绩效 · 自评Forecasting-tournament · self-report | 只据当时可得信息评"是否预见了自身决策的连锁后果",非以已知后果倒评Scores foresight of one's own decisions' knock-on effects from only what was knowable at the time, not backward from the known outcome |
| 破执自知(理)Ego Undistortion egoUndistortion · Pattern |
领导者谦逊(Owens & Hekman 2012);(反)过度自信(Malmendier & Tate 2005/2008)Leader humility (Owens & Hekman 2012); overconfidence (Malmendier & Tate 2005/2008) | 下属/自评 · 期权持有代理Subordinate/self · option-holding proxy | 测对自身能力与边界评估的准确度,非道德意义的谦卑;结局盲Measures accuracy of self-assessment of ability and limits, not moral modesty; outcome-blind |
| 去伪存真(理)Signal Discrimination signalDiscrimination · Pattern |
环境意会(Weick 1995)Sensemaking (Weick 1995) | 定性 · 自评Qualitative · self-report | 把"从噪声中辨出真规律"操作成可跨域打分的准确度轴Operationalizes "telling regularity from noise" as a cross-domain scorable accuracy axis |
| 据实置信(玄)Confidence Calibration calibratedUncertainty · Mystery |
校准 · 过度自信(Moore & Healy 2008)Calibration · overconfidence (Moore & Healy 2008) | 实验室校准任务Lab calibration tasks | 从传记行为推断信心与证据的动态匹配,而非实验室概率判断Infers confidence–evidence matching from biographical behavior, not lab probability judgments |
| 知止有界(玄)Boundedness Awareness boundednessAwareness · Mystery |
智识谦逊;实践智慧(Grossmann 2010;Sternberg 1998)Intellectual humility; practical wisdom (Grossmann 2010; Sternberg 1998) | 量表自评Self-report scales | 测对框架适用边界的清醒;其负向即可测的傲慢(接傲慢文献)Measures lucidity about a framework's boundary; its negative pole is measurable hubris |
| 存玄留白(玄)Irreducibility Reverence irreducibilityReverence · Mystery |
对模糊的容忍 · negative capabilityTolerance of ambiguity · negative capability | 量表自评Self-report scales | 让不可化约的内核悬置而非伪收口,此为玄轴独有,恰是现有构念覆盖最薄之处Lets the irreducible core remain suspended rather than forcing a false closure, the axis where existing constructs are thinnest |
表 3 · 逐轴判别效度(明六轴 × 最近相邻构念 × 差异)Table 3 · Per-axis discriminant validity (six lucidity axes × nearest adjacent construct × difference).
整体而言,明与实践智慧(Sternberg 1998;Grossmann 2010)最为接近,但在行为推断、结局盲与跨域通兑三点上与之相区别。判别效度的经验证据(理与玄各留约 27–37% 相互独立方差,表面特征仅解释 9%)见 §4。需要说明的是,玄轴中的"存玄留白"目前尚无成熟自评量表可供对标,这既是本文测量新意最集中之处,也是最需 R4 人类评审收敛加以佐证之处。
Overall, lucidity is closest to practical wisdom (Sternberg 1998; Grossmann 2010), from which it is distinguished on three counts: behavioral inference, outcome-blindness, and cross-domain commensurability. The empirical evidence for discriminant validity (the sub-dimensions each retain 27–37% independent variance; surface features explain only 9%) is in §4. One caveat: Irreducibility Reverence has no mature self-report scale to benchmark against, which is both where the measurement novelty is most concentrated and where human-rater convergence (R4) is most needed.
2.2与上层梯队理论的对位Positioning Against Upper-Echelons Theory
上层梯队理论(UET)既是这把尺最自然的归属,也正是它所要填补的缺口之源。Hambrick & Mason(1984)主张组织结局是高管认知、价值与知觉的"投影",却在同一文中承认这些心理构念难以直接观测,遂提出以可观测的人口统计特征(年龄、任期、职能背景、教育、社会出身)作为其底层认知的代理。正是这一步方法论选择,规定了此后四十年的实证纲领(综述见 Carpenter, Geletkanycz & Sanders 2004),也招致了同样持久的批评:人口统计是一只黑箱,它与结局相关,理论却看不进其内部之所以然(Lawrence 1997);Hambrick(2007)本人亦承认这一局限,呼吁采用"更贴近其所欲代表之心理构念"的度量。其后的管理者认知转向(Helfat & Peteraf 2015 之管理者认知能力;Eggers & Kaplan 2013)在概念上重新打开了黑箱,却仍缺一件对认知本身直接、跨域、且非事后的度量。
这把尺正是为这一空位而造。UET 以人口统计替代认知,明则直接为认知构念计分;其代理量受制于总体(CEO 任期变量无法通兑于将领或科学家),明却把牛顿与拿破仑放上同一根轴;其人口统计与声望代理吸收了本欲预测的结局,明的评分则结局盲、身份盲。表 4 将四种测量传统并置对照。
Upper-echelons theory (UET) is the natural home for this instrument, and also the source of the gap it fills. Hambrick & Mason (1984) argued that organizational outcomes are "reflections of" the cognitions, values, and perceptions of top executives, but conceded in the same paper that these psychological constructs are difficult to observe directly, and therefore proposed observable demographic characteristics (age, tenure, functional background, education, socioeconomic roots) as proxies for the underlying cognition. That single methodological move defined the empirical program for four decades (reviewed in Carpenter, Geletkanycz & Sanders 2004), and it drew an equally durable critique: demographics are a black box, correlated with outcomes for reasons the theory cannot see inside (Lawrence 1997), a limitation Hambrick (2007) himself acknowledged in calling for measures "closer to the psychological constructs they are meant to represent." The subsequent managerial-cognition turn (Helfat & Peteraf 2015 on managerial cognitive capabilities; Eggers & Kaplan 2013) reopened the box conceptually but still lacks a direct, cross-domain, hindsight-free measure of the cognition itself.
This is precisely the slot the ruler is built for. Where UET substitutes demographics for cognition, lucidity scores the cognitive construct directly; where its proxies are population-bound (a CEO tenure variable does not travel to generals or scientists), lucidity puts Newton and Napoleon on one axis; and where demographic and reputational proxies absorb the outcome they are meant to predict, lucidity is scored outcome- and identity-blind. Table 4 lays the four measurement traditions side by side.
| 测量传统Measurement tradition | 实际测到的是什么What it actually measures | 跨域?Cross-domain? | 免事后?Hindsight-immune? | 直接?Direct? |
|---|---|---|---|---|
| UET 人口统计代理(Hambrick & Mason 1984;Carpenter 等 2004)UET demographic proxies (Hambrick & Mason 1984; Carpenter et al. 2004) | 年龄、任期、职能/教育背景,用以替代认知Age, tenure, functional/educational background, standing in for cognition | 否No | 部分Partly | 否(代理)No (proxy) |
| 傲慢/过度自信代理(Roll 1986;Malmendier & Tate 2005/08;Hayward & Hambrick 1997)Hubris / overconfidence proxies (Roll 1986; Malmendier & Tate 2005/08; Hayward & Hambrick 1997) | 仅一负向切片(并购溢价、期权持有、媒体口吻)One negative slice (acquisition premia, option-holding, media tone) | 否No | 否No | 间接Indirect |
| 智慧/谦逊自评量表(Sternberg 1998;Grossmann 2010;Owens & Hekman 2012)Self-report wisdom / humility scales (Sternberg 1998; Grossmann 2010; Owens & Hekman 2012) | 直接测认知,经自评/下属评Cognition directly, via self/subordinate rating | 否No | 否(印象管理+事后)No (impression management + hindsight) | 是Yes |
| 明(本文)Lucidity (this paper) | 直接测判断力,六条行为轴Judgment directly, six behavioral axes | 是(同一把尺)Yes (one ruler) | 是(结局盲、身份盲)Yes (outcome- & identity-blind) | 是Yes |
表 4 · 明与三大主流"逼近领导者认知"传统之对照。其楔子不在于新构念,而在于一件同时做到直接、跨域、免事后的度量,这三性之并存,正是前三者皆未企及的。Table 4 · Lucidity versus the three dominant traditions for getting at leader cognition. The wedge is not a new construct but a measurement that is simultaneously direct, cross-domain, and hindsight-immune, the combination none of the prior three achieve.
与相邻文献合观,同一缺口反复出现:傲慢研究(Roll 1986;Hayward & Hambrick 1997;Hiller & Hambrick 2005)缺少盲评的纵向操作化;实践智慧缺少可自动计算的度量;接班与脱轨(McCall & Lombardo 1983;Shen & Cannella 2002;Finkelstein 2003)与组织存续(Stinchcombe 1965;Marquis & Tilcsik 2013)则从未在同一框架下被区分。贯穿其间的暗线是结局偏差(Fischhoff 1975;Baron & Hershey 1988):评估多在知道结局后进行,故清醒难以被干净地测量,而本文的结局盲设计正是为回应这一困难。本文的定位由此明确:它并非提出一个新的领导力理论,而是补上 UET 自 1984 年以来一直想要的那件测量工具,使上述文献中"想控制却无从测量"的认知变量,终于获得一件可操作、可跨域比较的测度。
Read together with the adjacent literatures, the same gap recurs: the hubris literature (Roll 1986; Hayward & Hambrick 1997; Hiller & Hambrick 2005) lacks a blind longitudinal operationalization; practical wisdom lacks an automatically computable measure; and succession and derailment (McCall & Lombardo 1983; Shen & Cannella 2002; Finkelstein 2003) have never been distinguished from organizational survival (Stinchcombe 1965; Marquis & Tilcsik 2013) inside one framework. The undercurrent throughout is outcome bias (Fischhoff 1975; Baron & Hershey 1988): assessment usually happens after the outcome is known, so lucidity is hard to measure cleanly, and the outcome-blind design here is meant to answer exactly that. The paper's position is therefore modest and specific: it does not propose a new theory of leadership but supplies the measurement instrument UET has wanted since 1984, so that cognitive variables the literature "wants to control but cannot measure" finally admit measurement, comparison, and falsification.
§3
仪器:怎么算(结局盲、身份盲、跨域可算)The Instrument: How It Is Computed
评分协议。 评分由 LLM 仅凭公开传记完成:先以时间线为每人编码 2 至 3 个有后果的阶段,逐阶段计算 明 = √(理·玄)·100 并按代价加权,术则取各阶段峰值。整个过程受两条铁律约束:
Scoring protocol. Scoring is done by a language model from public biography alone. Each life is coded as a timeline of two or three consequential phases; per-phase lucidity, √(Pattern×Mystery) rescaled to 0–100, is cost-weighted, and skill takes the peak across phases. Two hard rules hold throughout:
- 非道德防火墙。 评分只认看得准,不认人品;即便是病理性的崩溃,也仍按当时的利害计分,而不因结果"不道德"而扣分。 The amoral firewall. Scoring credits accuracy of sight, not character. A pathological breakdown is still scored by the stakes at the time, and is never docked merely because the result was monstrous.
- 反光环条款。 定稿前须自问"若不知这是谁,是否会给同一分数",并统一剥离身份信息。这一步是"结局盲"从口号落实为可执行程序的关键。须诚实划一条边界:该条款剥离的是显性身份线索(姓名、别名、头衔,及评价性/遗产段落),却无法保证模型不会据独特行为事实再识别出著名人物("1812 年率六十万大军进军莫斯科")。故"身份盲"应读作身份线索盲;红化后再识别是否仍可发生,是一项尚待检验的验证(议程 R-ID),在其跑通之前,不变性证据只能界定、而非消除潜在的身份泄漏。 The anti-halo clause. Before finalizing, the rater asks "if I did not know who this was, would I give the same score," and strips out identity information. This is the step that turns "outcome-blind" from a slogan into a procedure. One honest boundary: the clause removes explicit identity cues (name, aliases, titles, and evaluative/legacy sections); it cannot guarantee the model does not re-identify a famous figure from distinctive conduct facts ("marched on Moscow in 1812 with six hundred thousand men"). "Identity-blind" should therefore be read as identity-cue-blind; whether re-identification survives redaction is an open verification (agenda R-ID), and until it is run the invariance evidence bounds, but does not eliminate, latent-identity leakage.
结果可信度所系的关键性质。 明没有外部效标,因此不能以"对答案计算误差"来验证,那样只能测出趋同度。它是一件意见仪器,而非真相机器,其可信度来自 §4 的五道免答案验证与三场预先设定对抗实验。正文只需三个数字:表面特征仅解释明的 9%;揭名与盲评之间各轴漂移不超过 0.15 分;评审者间信度较高(ICC(2,1) 0.73–0.93 单评审,跨评审平均可达 0.98;完整区间见 §4),以上皆为模型评审之间的一致,而非与人类收敛(详见 R4)。"明是结局盲"是一项设计断言,因见微知远轴只据当时可得信息推理,其经验验证见 §4 与附录 E。
跨组标尺(已经代码审计)。 池化回归直接读取各群体手写的原始轴值,不作归一化。明在共享的固定量表上跨组一致,是本文最倚重、也是唯一完全干净的轴;术与建制力方向一致,但其单位随领域相对而变。朝向一轴则跨越了并不兼容的极点约定而被池化(统治者的"对内自保↔对外经略"对阵总统与 CEO 的"谋私↔受托",致使华盛顿同一交权行为在两套约定下分别记为 43 与 95),故其存续系数不能作单一构念解读;但该轴对善终的系数约为 0,且非本文核心,相关处理见议程 R0。就净判断而言,核心旁证(术偏业)所依赖的术与存续关系并不受朝向一轴的影响。
样本。 本文的语料是一个由手工编码与 LLM 评分共同构成的领导者面板:459 人带有明分,其中 404 人同时带有两个结局,横跨 20 个群体。科学家、艺术家等非组织领导者是否纳入主分析,取决于期刊定位(议程 S2),稳妥方案是将主分析限于政治、军事与商业领导者,而把非领导者移入泛化附录。两个虚构群体不进入回归。变量编码与回归全表见附录 D。
The properties on which credibility rests. Lucidity has no external criterion, so it is not validated by computing error against an answer key, which would only measure agreement. It is an opinion instrument, not a truth machine, and its credibility comes from the five criterion-free validations and three pre-specified experiments of §4. Only three numbers are needed here: surface features explain just 9% of the score; named-minus-blind drift is ≤ 0.15 points per axis; and inter-rater reliability is high (ICC(2,1) 0.73–0.93 single-rater, up to 0.98 averaged across raters; full ranges in §4), all between model raters, not convergence with humans (see R4). That "lucidity is outcome-blind" is a design claim (the Consequential Foresight axis reasons only from contemporaneous information), and its empirical verification is in §4 and App. E.
Cross-cohort scale (code-audited). The pooled regression reads each cohort's hand-authored raw axis values, with no normalization. Lucidity is consistent across cohorts on a shared fixed rubric, the axis the paper leans on most, and the only fully clean one. Skill and institution-building are directionally consistent but domain-relative in unit. Orientation is the problematic axis. It is pooled across incompatible pole conventions — rulers' "inward self-preservation ↔ outward projection" versus presidents' and CEOs' "self-dealing ↔ stewardship." The conventions disagree so sharply that Washington's single act of stepping down scores 43 under one and 95 under the other, so its organizational-survival coefficient cannot be read as a single construct. It is ≈ 0 on personal survival and non-core, with handling deferred to R0. The net judgment is that the skill/organizational-survival relation on which the core corroboration depends is unaffected by orientation.
Sample. The corpus is a hand-coded and model-scored panel of leaders: 459 carry lucidity, of whom 404 carry both outcomes, spanning twenty cohorts. Whether non-organizational leaders such as scientists and artists enter the main analysis depends on journal placement (agenda S2); the conservative option restricts the main analysis to political, military, and business leaders and moves the rest to a generalization appendix. Two fictional cohorts are excluded from the regressions. Variable coding and the full regression tables are in App. D.
3.1构造与透明:模型是如何被使用的Construction and Transparency: How the Model Is Used
本仪器是一套由人撰写、再由大语言模型施用的量表;讲清哪部分由人、哪部分由模型,是信任这些数字的前提。构念、六轴及其锚点、两条铁律与聚合公式,全部由人预先撰写并固定。模型的职责很窄:读一份传记,依量表给出轴分。三道处理跑在同一份公开源文本上(图 3)。图谱道在身份可见下逐阶段评十二个量表分量;R2 盲评道先脱敏身份与结局,再由独立评审重评六轴;R3a 客观道则完全撇开量表,抽取基于记录、引证锚定、且盲于预测分的事实。
The instrument is a human-authored rubric applied by a large language model; being explicit about which is which is a precondition for trusting the numbers. The construct, the six axes, their anchors, the two hard rules, and the aggregation formula are all authored by hand and fixed in advance. The model's job is narrow: read a biography and return an axis score, following the rubric. Three passes run over the same public source text (Figure 3). The atlas pass scores each phase on the twelve rubric components with the figure's identity visible; the R2 blind pass first redacts identity and outcome, then an independent judge re-scores the six axes; the R3a objective pass ignores the rubric entirely and extracts records-based facts, quote-anchored and blind to the predictor scores.
| 阶段Stage | 模型做什么What the model does | 由人固定Fixed by hand | 关键局限Key limitation |
|---|---|---|---|
| 量表设计Rubric design | 无(由研究者撰写)nothing (authored by researchers) | 构念、六轴、锚点、极点、公式construct, 6 axes, anchors, poles, formula | 构念选择系作者判断the construct choices are the authors' |
| 图谱评分(命名)Atlas scoring (named) | 读传记,逐阶段评 12 轴reads biography, scores 12 axes per phase | 量表 + 锚例rubric + anchor exemplars | 身份与结局可见 → 光环风险(引出 R2)identity & outcome visible → halo risk (motivates R2) |
| 盲评复评(R2)Blind rescore (R2) | 脱敏后重评六轴redacts text, re-scores 6 axes blind | 脱敏与评审协议redaction & judging protocol | 单评审、单模型族、盲化不完美single rater, one model family, imperfect blinding |
| 客观抽取(R3a)Objective extraction (R3a) | 引证锚定死法与存续年pulls death-manner & survival years, quote-anchored | 0–4 死法量表(全体);存续年(仅建制者)0–4 fate scale (all); survival years (builders only) | 死法粗粒(n=449 / 136)manner-of-death is coarse (n=449 / 136) |
| 聚合Aggregation | 无(确定性)nothing (deterministic) | 几何均、代价加权geometric mean, stakes-weighting | 权重的研究者自由度researcher degrees of freedom in weights |
表 5 · 由人撰写的量表与模型之间的分工。数据集中每个值都是模型对一件固定仪器的读数,而非模型的自由发挥;全程模型族为 Claude(Anthropic)、单评审,这正是 R4 所要弥合的局限。Table 5 · Division of labor between the human-authored rubric and the model. Every value in the dataset is a model reading of a fixed instrument, not a free-form model opinion; the model family throughout is Claude (Anthropic), single-rater, which is exactly the limitation R4 is designed to close.
3.2语料的量化描述The Corpus in Numbers
语料一览。 459 人,20 个群体,跨 723 BCE 至 1985 CE。明均值 62.3(SD 18.2,范围 10–91),呈长下尾(均值低于众数,后者约在 72)。结局盲重评在重打的 400 人中回收 397 个有效分;客观善终编码 449 人,客观制度存续限 136 位建制者。156 人为建制者。客观记录 88% 源自维基、85% 高置信。
The corpus at a glance. 459 figures across 20 cohorts, spanning 723 BCE to 1985 CE. Lucidity has mean 62.3 (SD 18.2, range 10–91), with a long lower tail (the mean sits below the mode near 72). The outcome-blind rescore returns a valid score for 397 of the 400 re-scored figures; objective fate is coded for 449 and objective institution-survival for 136 builders. 156 figures are institution-builders. The objective records are 88% Wikipedia-sourced and 85% high-confidence.
§4
免效标验证:无标准答案,如何为一把尺辩护(方法论核心)Criterion-Free Validation: Defending a Ruler With No Answer Key
本节是本文可移植性最强的贡献。判断力没有 ground truth,一切"对效标算准确率"的路径都整个失效:人们无法将明"对答案"来验证,因为根本不存在答案。为此,本文改用一套不对答案的验证逻辑,不追问"分数对不对",而追问"这套分数是否具备一件可信测量工具所应有的一切内部性质"。
测量哲学:不对答案,故不设答案。 明没有外部效标;手工参照集只是"第 R+1 位评审",而绝非答案键;"对 gold 计算 MAE 或 ρ"一律作废,因为那只测趋同,不测正确。这里须区分两个层次:测量层指本节的免效标内部验证;而明作为自变量预测真实结局,则是一项有效标的经验主张,须以 R2、R4 及样本外预测另行辩护,不得沿用免效标的豁免。正是这一区分,构成 §5 将结局关系严格限定为"旁证"的理由。
This is the paper's most transferable contribution. Judgment has no ground truth, so every "score accuracy against a criterion" route fails outright: one cannot validate lucidity against an answer key, because there isn't one. We therefore change the question. Instead of asking "are the scores correct," we ask "does this set of scores have every internal property a credible measurement instrument should have."
Measurement philosophy: no answer key, so none is invented. Lucidity has no external criterion; the hand-authored reference set is merely "the R+1-th rater," never an answer key; and computing MAE or ρ against "gold" is void, since it measures agreement rather than correctness. A distinction must be kept. The measurement layer (the criterion-free internal validation of this section) is one thing; lucidity as an independent variable predicting real outcomes is another, a criterion-bearing empirical claim to be defended separately via R2, R4, and out-of-sample prediction, and not under the criterion-free exemption. This is exactly why §5 keeps the outcome relations to corroboration and nothing more.
4.1五道免答案验证Five Criterion-Free Validations
本文的成套测验为 20 人 × 3 评审 × {揭名, 盲评},共 120 次评分,横跨知识、结局、信仰三域,但尚未覆盖 CEO、央行家等回归主力群体(见 R6);另含 12 篇合成传记。以下五道验证各回答一件"好尺"应当具备的性质:
The depth battery comprises 20 subjects × 3 raters × {named, blind}, for 120 scorings, spanning the knowledge, outcome, and faith domains (though not yet the regression's workhorse cohorts such as CEOs and central bankers; see R6), alongside 12 synthetic biographies. Each of the five validations answers one property a good ruler should have:
- (1) 覆盖度。 κ 作为一等输出,表明施测语料对目标领域的覆盖是充分的。 (1) Coverage. κ is a first-class output and confirms that the corpus covers the target domains adequately.
- (2) 结构。 有效维数约为 2(各法 1.7–2.0):从 12 轴收敛到 6 轴、再收敛到理与玄两支,是数据所支持的,而非人为设定。 (2) Structure. Effective dimensionality is ≈ 2 (1.7–2.0 across methods): the reduction from 12 axes to 6, and then to the two-branch structure, is data-supported rather than imposed.
- (3) 信度。 ICC(2,1) 介于 0.73 至 0.93,ICC(2,3) 介于 0.89 至 0.98。须强调,这是模型评审之间的自洽,而非与人类收敛,后者属于 R4。 (3) Reliability. ICC(2,1) ranges 0.73–0.93 and ICC(2,3) ranges 0.89–0.98, a self-consistency between model raters, not convergence with humans, which is R4's job.
- (4) 不变性。 揭名与盲评之间各轴的 Δ 不超过 0.15 分(基于 20 人深度测验、0–5 轴量纲):显性身份线索基本不撼动分数,这是"结局盲、身份线索盲"最直接的经验证据。(此逐轴不变性与附录 B,B.8 中 397 人全池、0–100 聚合量纲下约 11 分的揭名−盲评均差并不矛盾:两者样本与量纲皆异——少数高共识人物的 0–5 逐轴分,对阵含低共识人物的全池重标聚合分——且聚合量纲会把细小的逐轴位移在算术上放大。) (4) Invariance. Named − blind Δ ≤ 0.15 per axis (on the 20-subject depth battery, 0–5 axis scale): explicit identity cues essentially do not move the score, the most direct evidence of outcome- and identity-cue-blindness. (This per-axis invariance is not in tension with the ≈ 11-point mean named−blind gap on the full 397-figure pool at 0–100 aggregate scale in App. B, B.8: the two are different samples and scales — a handful of high-consensus subjects scored per-axis at 0–5 versus the whole pool, including low-consensus figures, on the rescaled aggregate — and the aggregate arithmetically magnifies small per-axis shifts.)
- (5) 信息。 理与玄虽高度相关(r ≈ 0.80),却各留约 27–37% 的独立方差:二者并非同一维度的两个名字。 (5) Information. The two sub-dimensions are highly correlated (r ≈ 0.80) yet each retains 27–37% independent variance, so they are not two names for one.
4.2三场预先设定对抗实验Three Pre-specified Adversarial Experiments
在免答案验证之外,本文再以三场预先设定实验,主动证伪"这把尺其实在量别的东西"这一假说(此处预先设定指:实验设计、失败线与分析方案在看到分数之前即以文字固定,但未登记于公开注册库,故不称"预注册"):
Beyond the criterion-free checks, three pre-specified experiments actively try to catch the ruler measuring something other than what it claims (pre-specified = the design, failure line, and analysis were fixed in writing before the scores were seen; they are not lodged in a public registry, so we do not call them pre-registered):
- E3 混淆回归。 以表面特征(时代、领域、名气、文本长度等)回归明,R² 仅为 0.09,远低于预设的失败线 0.50:明无法由表面特征重构,身份与光环并未进入分数。 E3, confound regression. Regressing the score on surface features (era, domain, fame, text length) yields R² = 0.09, far below the pre-set failure line of 0.50: the score cannot be reconstructed from surface features, and identity and halo did not enter.
- E5 合成剖面。 对 12 篇按理/玄象限预设的合成传记进行盲评,回收得 ρ理 = 0.82、ρ玄 = 0.87,象限命中 10/12:这把尺能够分辨被刻意设计出来的理玄差异。其软肋在于出题与评分同属一个模型族。 E5, synthetic profiles. Twelve biographies pre-designed by Pattern–Mystery quadrant are blind-scored back at ρ = 0.82 (Pattern) and 0.87 (Mystery), with a quadrant hit of 10/12: the ruler resolves engineered differences. Its weakness: item-writing and scoring share a model family.
- E1 盲化阶梯。 从 L1 到 L2 逐步去除身份线索,偏差并不增长;仅在 L3 的极端重写下,最软的两轴才越线;未测偏差不超过 0.5 分(满分 5)。 E1, blinding ladder. From L1 to L2 the bias does not grow; only under the L3 extreme rewrite do the two softest axes cross the line; unmeasured bias is ≤ 0.5 points out of 5.
这一节为何是核心。 任何 LLM-as-judge 打分工具都面临同一诘问:"你没有标准答案,凭什么说你的分数可信?"本文的答复不是"我们对得准",而是一套在没有答案键时仍能严谨立尺的验证范式,即覆盖、结构、信度、不变性、信息五项内部性质,辅以预先设定的对抗实验。这套范式对整个 LLM 评审家族均适用,是本文超出"明"这一具体构念的方法论贡献。
Why this matters beyond the present construct: any LLM-as-judge tool faces the same challenge: "you have no answer key, so why should your scores be believed?" The answer offered here is not "we score accurately" but a validation paradigm that defends a ruler rigorously without an answer key: coverage, structure, reliability, invariance, and information, together with pre-specified adversarial experiments. That paradigm generalizes to the entire LLM-judge family, beyond the present construct.
§5
这把尺让你看见什么:描述性与 nomological 旁证What the Ruler Lets You See: Descriptives and Nomological Corroboration
本节把这把尺"接到世界上",考察它与领导者真实结局的关系是否合乎理论预期。以下一切仅为构念效度的旁证,用以证明尺量到了真东西,而不构成"明预测结局"的主张。完整回归见附录 D、E、F。This section connects the ruler to the world and asks whether its relation to real outcomes matches theory. Everything below is corroboration of construct validity, evidence that the ruler measures something real, and not a claim that lucidity predicts outcomes. Full regressions in Apps. D, E, F.
将明接到近四百位领导者的两个结局(个人善终与事业存续)之上,一把行为合理的尺应当呈现出结构化、可解释的关联,而非一团噪声。结果确实如此,且其模式与理论相一致。
先看组内。 在池化回归之前,先把领域固定住。在美国总统这一群体内,术与明于同一职位内即显著分离(图 6):林登·约翰逊(术 95)与安德鲁·杰克逊(术 88)跻身史上最能干的主政者之列,明分却很低(33 与 23);艾森豪威尔两端皆高;而"术高明低"之角人物云集,其镜像却近乎空置。这把两幅肖像的对照复制到了单一群体之内——领域、时代、角色大体恒定——因此不可能是"拿将领比 CEO"式的假象。
Connect lucidity to the two outcomes (personal survival and organizational survival) of nearly four hundred leaders, and a sensibly behaving ruler should show structured, interpretable relations rather than noise. It does, and the pattern is the one theory would predict.
First, a within-cohort look. Before the pooled regressions, hold the domain fixed. Among US presidents, skill and lucidity come apart sharply within the single office (Figure 6): Lyndon Johnson (skill 95) and Andrew Jackson (skill 88) are among the most capable operators ever to hold the office, yet score low on lucidity (33 and 23); Eisenhower sits high on both; and the high-skill / low-lucidity corner is populated while its mirror is nearly empty. This is the two-portrait contrast reproduced inside one cohort, where domain, era, and role are held roughly constant, so it cannot be an artifact of comparing generals with CEOs.
| 预测子Predictor | → 个人善终 β (t) [ΔR²]→ Personal survival β (t) [ΔR²] | → 事业存续 β (t) [ΔR²]→ Org. survival β (t) [ΔR²] |
|---|---|---|
| 建制力Institution-building | +0.49 (11.1) [.167] | +0.51 (16.1) [.183] |
| 术Skill | −0.03 (−0.7, ns) [.001] | +0.22 (6.9) [.034] |
| 明Lucidity | +0.27 (5.6) [.043] | +0.21 (5.9) [.025] |
| 朝向Orientation | +0.02 (0.5, ns) [.000] | +0.14 (4.3) [.013] |
| 难度Difficulty | −0.15 (−3.9) [.021] | −0.09 (−3.5) [.009] |
| 模型 R²Model R² | 0.457 | 0.719 |
表 1 · 逐结局 OLS(n=404,标准化 β;t;独有 ΔR²)。表 1 为命名(图谱)分;结局盲重评后明的系数见表 2 下半;其余四项预测子不被重评,其系数仅有微小位移。Table 1 · Per-outcome OLS (n = 404; standardized β; t; unique ΔR²). Table 1 uses named (atlas) scores; after the outcome-blind rescore, lucidity's coefficients move as in the lower rows of Table 2, while the other four predictors are not rescored (their coefficients shift only slightly).
| 能力Capacity | 善终 βPers. β | 存续 βOrg. β | 差Diff | z(主体)z(subj) | z(群体)z(coh) | p | 判定Verdict |
|---|---|---|---|---|---|---|---|
| 术Skill | −0.03 | +0.22 | +0.25 | 5.46 | 3.37 | <.001 | 偏业(命名/盲皆稳健)Enterprise-tilted (robust) |
| 建制力Institution-building | +0.49 | +0.51 | +0.02 | 0.37 | n/a | .71 | 两端等强(最大预测子)Equal both ends (largest) |
| 明 · 命名Lucidity · named | +0.27 | +0.21 | −0.07 | −1.24 | n/a | .21 | 方向性(遗产光环污染)Directional (halo-contaminated) |
| 明 · 结局盲Lucidity · blind | +0.34 | +0.08 | −0.26 | −4.66 | −3.77 | <.001 | 偏命(去事后之明后浮现)Fate-tilted (emerges) |
表 2 · 能力对结局的差异检验(堆叠 SUR,差=存续−善终,由未舍入系数算得;明分命名 vs 结局盲重评)。命名→盲的位移是理论一致、非随机:明与存续的虚高关联坍缩,与善终的关联增强。Table 2 · Capability–outcome differential test (stacked SUR, diff = org − personal, computed from unrounded coefficients; lucidity shown named vs outcome-blind rescore). The named → blind shift is theory-consistent, not random: lucidity's inflated organizational-survival link collapses while its personal-fate link strengthens.
旁证一(命名与盲评皆稳健):术只偏业。 术对事业存续的系数为 β = +0.22(t = 6.9),对个人善终则为 β = −0.03(不显著);二者之差 Δ = 0.25(主体聚类 z = 5.46,p < 0.001),在四种 SE 与设定下均一致,且在主体聚类检验下,盲重评后更强(z = 5.5 → 6.0)。可谓才华筑起组织,却不筑其自身。
旁证二(经结局盲重评揭示):明偏命,但存在口径边界。 在命名分下,明对两端皆显著,偏命之差却不显著(Δ = −0.07,p = 0.21),这是受遗产光环污染后的保守读法;且在 16 种设定构成的设定曲线上,命名偏命之差的中位约为 0、仅约半数保持其(负)号(附录 D),故在盲化之前,它根本不是一个稳定效应。施行结局盲重评(删去身份与结局线索、对全池独立重打)之后,明对善终的系数升至 β = +0.34(t = 8.3),对存续的系数降至 β = +0.08(t = 2.4),偏命之差随之变为 Δ = −0.26(主体聚类 z = −4.7,群体聚类 z = −3.8,p < .001);逐一剔除任一群体,主体聚类 z 稳定在 −4.0 至 −5.0 之间。这一位移并非从噪声中挑出:若盲重评只是叠加了测量误差,理应把所有系数一致地拉向零;此处的情形恰恰相反,明与存续的关联坍缩、与善终的关联增强,正是去掉了"大遗产名人→明被读高"这一特定光环后的签名。然而口径依赖必须讲死:R3a 将结局替换为纯客观事实(死法序数加制度存续年数,盲抽 459 人)之后,明偏命并不复现:明对客观善终的系数仅为 β = +0.08(t = 1.50;在世者剔除后 t = 0.99),偏命之差 z = −1.37、p = .17,只余方向性。因此,明偏命仅限于命名与盲评这类专家式结局编码,而不外推到粗粒度的客观死法代理(方法与全表见附录 F,成因见 §6)。
整体坐标:建制力主导两端,且系数最大。 建制力对善终与存续的系数均约为 0.5,二者之差不显著(z = 0.37);优势分析中其占比分别为 56% 与 48%,在两端皆列第一。术与明构成解离的两翼(术稳健,明依口径而定,见 §7),建制力则在两端托底,是撑起整个结构的主梁。在 R3a 的客观结局代理下,这根主梁被证实并非共源(建制力对客观存续 t = 3.7,对客观善终 t = 8.5);而两翼之中,只有术偏业随建制力一同穿透到客观口径,明偏命则不穿透(详见 §7 与附录 F)。
共线性并非问题。 全部 VIF 均落在 [1.03, 1.71] 区间内,因此术在善终端的"约等于 0"与盲分下明在存续端的"约等于 0"都是真实信号,而非共线性造成的假象。
Corroboration one (robust across named and blind): skill is enterprise-tilted only. Skill's coefficient is β = +0.22 (t = 6.9) on organizational survival and β = −0.03 (n.s.) on personal survival; the difference, Δ = 0.25 (subject-clustered z = 5.46, p < 0.001), is consistent across four SE specifications and, on the subject-clustered test, strengthens after the rescore (z = 5.5 → 6.0). Skill builds the organization but not the self.
Corroboration two (revealed by the blind rescore): lucidity is fate-tilted, within a coding boundary. With named scores lucidity is significant at both ends and the fate-tilt is not significant (Δ = −0.07, p = 0.21), the halo-contaminated, conservative reading; and across 16 specifications the named fate-tilt sits at a median of ≈ 0 and keeps its (negative) sign in only about half of them (App. D), so before blinding it is not a stable effect at all. After the outcome-blind rescore (identity and outcome cues deleted, the whole pool independently re-scored), lucidity's personal β rises to +0.34 (t = 8.3), its organizational β falls to +0.08 (t = 2.4), and the fate-tilt becomes Δ = −0.26 (subject-clustered z = −4.7, cohort-clustered z = −3.8, p < .001); drop any single cohort and the subject-clustered z stays between −4.0 and −5.0. This is not an artifact: had the rescore merely added measurement error, it would have pulled every coefficient uniformly toward zero, whereas here the opposite happened: lucidity's link to organizational survival collapsed and its link to personal survival strengthened, the signature of removing a specific confound (the "famous, large legacy, therefore surely lucid" halo). But the coding-dependence must be stated flatly: when outcomes are replaced with purely objective facts (a manner-of-death ordinal plus institution-survival years, 459 figures blind-extracted), R3a finds that the fate-tilt does not replicate: lucidity on objective fate is β = +0.08 (t = 1.50; t = 0.99 dropping the still-living), and the tilt difference is z = −1.37, p = .17, directional only. Corroboration two is therefore confined to named and blind (expert-style) coding and does not extrapolate to the coarse objective proxy (method and full table in App. F; mechanism in §6).
The overall coordinate: institution-building dominates both ends. Its coefficients are ≈ .5 at each end, the difference is not significant (z = 0.37), and its dominance shares are 56% and 48%, first at both ends. Skill and lucidity are the two wings of a dissociation — robust for skill, coding-dependent for lucidity (§7) — while institution-building carries both, the master beam spanning the structure. R3a shows the master beam is not common-source (institution-building scores t = 3.7 on objective survival and t = 8.5 on objective fate); of the two wings, only the skill-tilt carries through to the objective operationalization, while the fate-tilt does not (see §7 and App. F).
Collinearity is not the culprit. All VIF fall in [1.03, 1.71], so skill's near-zero coefficient on personal survival and blind-lucidity's near-zero coefficient on legacy are real signals, not artifacts.
读法与红线。 上述关系合起来说明,这把尺接到真实世界之后,行为合理、模式可解释,且经得起去光环的检验。有一条区分须讲清,因两翼的稳固程度并不对等:术偏业是稳健的锚——在命名、盲评、及客观三种口径下同号且显著;明偏命则是脆弱的一翼——在命名设定曲线上缺席,仅在命名→盲评重评下浮现,又在客观代理下收敛为零(R3a)。故明偏命是留待后续工作的方向性线索,而非本文所倚仗的发现;真正承重的经验结果是术的解离。但它们全都是构念效度的旁证,而非"明预测结局"的主张:命名到盲评的位移,同时混合了"去光环"与"换评审方法"两件事,干净的因果读法尚须由 R4(跨模型族复评加人类评审 ICC)加以锁定。本文只主张测量层的构念效度。
Taken together, these relations show that the ruler, once connected to the world, behaves sensibly, with an interpretable pattern that survives halo-removal. One distinction should be kept sharp, because the two wings are not equally secure: the skill→enterprise tilt is the robust anchor — identical in sign and significance across named, blind, and objective coding — whereas the lucidity→fate tilt is the fragile one, absent from the named specification curve, emerging only under the named→blind rescore, and converging to a null under objective proxies (R3a). The fate-tilt is therefore a directional lead for future work, not a finding the paper rests on; the weight-bearing empirical result is the skill dissociation. That is worth having, but even it is corroboration of construct validity, not a claim that lucidity predicts outcomes. The named-to-blind shift conflates halo-removal with a rater-and-method change, and a clean causal reading must wait for R4 (cross-model-family re-scoring plus human-rater ICC). The paper's claim stays at the measurement layer.
§6
讨论:一件测量工具为上层梯队研究打开了什么Discussion: What a Measurement Instrument Opens Up
主贡献:把"不可测"变成"可测"。 领导者认知,包括判断力、清醒度与傲慢,在上层梯队与傲慢文献中被反复援引为关键变量,却始终缺少一件直接、跨域、且非事后的度量工具。本文提供的正是这件工具:一把结局盲、身份盲、跨领域可算、且在无标准答案时仍可验证的判断力量表。它的意义不在于"又发现一个预测因子",而在于把一整类此前只能事后追认的问题,转成可以事前测量的问题。
由此使能的研究问题(举隅)。 有了可算的清醒度,以下这些此前只能定性谈论的问题,如今可以纵向、跨域、盲评地加以实证:董事会以才华下注与以清醒下注,其接班结局有何系统差异?领导者傲慢(即破执自知与知止有界的负轴)能否在危机之前被读出,而非事后追认?清醒是否可训练,其轨迹又如何演化?这些问题共享同一前提,即判断力必须先可测。
方法论外溢:去掉事后之明,结构反而更清晰。 这里有一个对整个"评估领导者"研究传统都成立的发现:判断力的度量长期受困于结局偏差,因为评估多在知道结局之后进行。本文表明,结局盲重评不但没有削弱信号,反而将其锐化(明与存续的关联坍缩,与善终的关联增强,正是"驱动前者的是光环而非构念"时所应预期的模式)。由此可得一条可复用的验证逻辑:去掉事后之明若使信号减弱,说明该信号本就是事后之明;此处它反而增强,说明所测的是心智本身。这条逻辑并不依赖"明"这一具体构念,可移植到任何需要与事后之明切割的领导者认知度量。
对因变量构建的提醒。 作为旁证,这把尺也顺带照出上层梯队研究中一个易被忽略的建构问题:将"个人是否善终"与"组织是否存续"合并为笼统的"绩效",会同时抹去才华(偏业)与清醒(偏命)各自不同的回报剖面。拿破仑即是极端一例:才华顶尖,《民法典》长存,本人却客死孤岛。但须重申,这是旁证而非主张,其因果的强形式系于 R4。
The main contribution: turning "unmeasurable" into "measurable." Leader cognition (judgment, lucidity, hubris) is invoked constantly in the upper-echelons and hubris literatures, and has always lacked a direct, cross-domain, non-hindsight measure. This paper supplies one: a scale of judgment that is blind to outcome and identity, computable across domains, and defensible without a criterion. Its significance is not that one more predictor has been found, but that it opens a body of research that biography alone could never support.
Enabled questions. With computable lucidity, questions that could only be discussed qualitatively can now be tested longitudinally, cross-domain, and blind. Do boards betting on talent versus on lucidity get systematically different succession outcomes? Can leader hubris (the negative pole of Ego Undistortion and Boundedness Awareness) be read before a crisis rather than diagnosed after? Is lucidity trainable, and along what trajectory? Each of these shares one prerequisite: that judgment be measurable at all.
Methodological spillover: removing hindsight sharpens the picture. A finding here holds for the whole tradition of assessing leaders. Measuring judgment is trapped by outcome bias, because assessment usually happens after the outcome is known. The outcome-blind rescore does not weaken the signal but sharpens it: lucidity's link to organizational survival collapses while its link to personal survival strengthens, the pattern expected if a halo, not the construct, drove the former. That yields a reusable test: if removing hindsight weakens the signal, the signal was hindsight; if it strengthens, the instrument is measuring the mind. The logic does not depend on this particular construct and transfers to any leader-cognition measure that must be cut loose from hindsight.
A reminder on dependent variables. The ruler also exposes a construction problem easy to miss in upper-echelons work: folding "did the person end well" and "did the organization survive" into a single "performance" erases, in one stroke, the distinct payoff profiles of talent (enterprise-tilted) and lucidity (fate-tilted). Napoleon is the limiting case: top talent, an enduring legal code, and death in island exile. But this is corroboration, not a claim; its strong causal form rests on R4.
§7
局限与稳健性(即研究议程对应威胁)Limitations and Robustness
- 盲重评的残余混淆(当前的关键约束)。 R2 已经落地(附录 E):删去身份与结局线索后,对全池重新评分。但命名到盲评的位移混合了两件事,即去光环与换评审方法(盲分由 LLM 子代理单评审、同模型族、且盲化并不完美)。因此,"明偏命"目前只是一种去偏之后的关联;要将其坐实为免于事后之明的因果,尚须推进至议程 R4,并辅以 R3b。
- 共源方差(R3a 已部分解除,并界定了明偏命的边界)。 建制力、术与结局原本均为手工编码,与明(出自 LLM)并非同源。R3a(附录 F)以客观结局代理重新检验:建制力对客观存续仍有 t = 3.7、对客观善终有 t = 8.5,其主导地位并非纯粹共源,主梁经受住了客观化。但同一检验也界定了明偏命的边界:在客观结局下,明对善终并不显著(t = 1.5,在世者剔除后 t = 1.0),偏命之差 z = −1.37、p = .17,只余方向性。故明偏命应严格读作命名与盲评口径下的方向性偏斜,而非穿透到客观事实的强断言。此处尚有两点残余:客观死法代理较为粗粒,且对建制者略含机械成分;客观存续仅限建制者(n ≈ 136),功效偏低。预测子端(术与建制力)的独立盲编码仍有待推进至议程 R3b。
- 单一评审模型族,且缺人类收敛。 应对之道是议程 R4,即跨模型族复评加人类评审 ICC;这也是把 §4 的"模型评审间自洽"升级为"人类收敛"的必需步骤。
- 效度外推。 需将 20 人成套测验的效度外推至 404 人全池,对应议程 R6。
- 选择偏差构成对撞子。 名气部分由"能力 × 戏剧性结局"共同致成,以名气选样可能人为制造出关联;这一点须作为内部效度威胁予以明确讨论,并刻画 459 至 404 的缺失。
- 朝向标尺不一致。 详见 §3 与议程 R0(统一极点或将其剔出);此项对核心旁证(术偏业)没有影响。
- 聚合环节的研究者自由度。 明取加权几何均、术取峰值;不同的聚合规则应进一步做稳健性检验(议程 R7)。
- 源文本层的事后之明(评分指令无法抬起的地板)。 评分指令把见微知远轴限定于当时可得信息,但源文本本身是知道结局的编者所撰的传记,故哪些行为事实被记录、以何种框架呈现,已被事后之明筛选。红化剔除的是评价性形容词与遗产段落,而非这层筛选。因此结局盲是评分层的性质,而非源文本的性质;E1 中的 L3 极端改写臂是唯一触及源文本层的探针,宜读作源层残余事后之明的上界,而非其消除。
- 术的范围限制。 入图需以声望为门槛,故术被压向高端(均 84.5、标准差 12.2,相较总体应更窄)。范围限制会衰减术的系数,故其对个人善终近乎为零的载荷是一种保守读法,而非术无关的证据;经范围限制校正的估计(议程 R7)只会放大、而非缩小术的解离。
- Residual confounding in the blind rescore (the key current constraint). R2 has landed (App. E): deleting identity and outcome cues and re-scoring the whole pool made the fate-tilt significant. But the named-to-blind shift conflates two things: halo-removal and a rater-and-method change (single-rater model subagents, one model family, imperfectly blinded). The fate-tilt is thus currently a de-biased association; establishing it as hindsight-immune causation requires agenda R4, together with R3b.
- Common-source variance (R3a partly resolves it, and also bounds the fate-tilt). Institution-building, skill, and outcomes were hand-coded, and so are not the same source as the model-scored lucidity. R3a (App. F) re-tests with objective outcome proxies: institution-building still holds on objective survival (t = 3.7) and objective fate (t = 8.5), so its dominance is not pure common-source and the master beam survives objectification. But the same test bounds the fate-tilt: on objective outcomes lucidity is insignificant on fate (t = 1.5; t = 1.0 dropping the still-living) and the tilt difference is z = −1.37, p = .17, directional only. So "lucidity saves the person" reads strictly as a named/blind-coding directional tilt, not a claim that carries through to objective facts. Two residuals remain: the objective manner-of-death proxy is coarse and partly mechanical for builders, and objective survival is builders-only (n ≈ 136, low power); independent blind coding of the predictors is still outstanding, at agenda R3b.
- A single rater model-family, and no human convergence. The remedy is agenda R4 (cross-model-family re-scoring plus human-rater ICC), the step that upgrades §4's self-consistency between model raters into convergence with humans.
- Validity extrapolation. The 20-subject battery's validity must be extrapolated to the 404-subject full pool, at agenda R6.
- Selection bias as a collider. Fame is produced partly by ability and partly by dramatic outcome, so sampling on fame can manufacture an association; this must be treated as an internal-validity threat, with the 459-to-404 attrition characterized.
- Orientation scale inconsistency. See §3 and agenda R0 (unify the poles or drop the axis); it has no bearing on the core corroboration.
- Researcher degrees of freedom in aggregation. Lucidity takes the weighted geometric mean and skill takes the peak; alternative aggregation rules should be tested for robustness (agenda R7).
- Source-level hindsight (a floor that scoring instructions cannot lift). The scoring instruction confines the Consequential Foresight axis to contemporaneous information, but the source text is a biography written by editors who knew the outcome, so which conduct facts are recorded, and how they are framed, is already hindsight-selected. Redaction removes evaluative adjectives and legacy sections but not this selection. Outcome-blindness is thus a property of the scoring layer, not of the source; the L3 extreme-rewrite arm of E1 is the only probe that reaches the source layer, and it is best read as an upper bound on residual source-hindsight, not as its elimination.
- Range restriction on skill. Entry to the atlas requires eminence, so skill is compressed high (mean 84.5, SD 12.2, versus a presumably wider general-population range). Restriction of range attenuates skill's coefficients, so its near-zero loading on personal survival is a conservative reading, not evidence that skill is inert; a range-restriction-corrected estimate (agenda R7) would if anything widen, not close, the skill dissociation.
结语Conclusion
结语Conclusion
判断力被人人视为领导成败的关键,却长期只能凭事后光环谈论,原因正在于缺少一把不靠结局倒推的尺。本文造出并验证了这样一把尺:明 = 理⊗玄,将清醒分解为可操作的六轴,并做到结局盲、身份盲、跨领域可算;同时,本文示范了在没有标准答案时应如何严谨地为它辩护,即以覆盖、结构、信度、不变性、信息五项内部性质,辅以三场预先设定对抗实验。这把尺使一个公认关键、却历来不可测的东西,终于变得可算、可比、可证伪。
将这把尺接到近四百位领导者身上,它的行为是合理的:结构主梁是建制力,一支"明偏个人终局"的倾向在去掉事后之明后浮现。但这只是旁证,且带有一条必须讲死的口径边界:一旦换成纯客观事实,明偏命便让位于建制力。本文的主张始终停留在测量层面,即造出一把量判断力的尺,而非一个预测结局的模型。它的价值在于,让上层梯队与领导者认知研究中一批"想测却无从测"的问题,从此有了可用的工具。
Judgment is universally treated as decisive to a leader's fate, and yet has long been discussable only through the halo of hindsight, because there was no ruler that refused to reason backward from the outcome. This paper builds and validates such a ruler: lucidity, decomposed as Pattern ⊗ Mystery into six operational axes, outcome-blind, identity-blind, and computable across domains. It then shows how to defend the ruler when there is no ground truth: through coverage, structure, reliability, invariance, and information, plus three pre-specified adversarial experiments. The ruler takes a thing everyone calls central, yet historically unmeasurable, and makes it computable, comparable, and falsifiable.
Connected to nearly four hundred leaders, the ruler behaves sensibly: the structural spine is institution-building, and a tilt of lucidity toward personal fate appears once hindsight is removed. But this is a sanity check, not a claim, and it carries one boundary worth stating plainly: replace the outcomes with purely objective facts and the fate-tilt yields to institution-building. The claim throughout is a measurement one: a ruler for judgment, not a model that predicts fate. Its value is that a whole class of "we wanted to measure it but couldn't" questions in upper-echelons and leader-cognition research now has an instrument to reach for.
研究议程Research Agenda
稳健性检验与研究议程Robustness Checks and Research Agenda
| 编号No. | 任务Analysis | 状态Status | 结果/产出Result / deliverable |
|---|---|---|---|
| R0 | 快照刷新到 n=404;方法论论述迁移到 理⊗玄Refresh snapshot to n = 404; migrate methodology prose to the Pattern ⊗ Mystery formulation | 已完成done | 快照 --write 已落地;论述已双语迁移(朝向统一暂缓)Snapshot --write landed; prose migrated (orientation unification deferred) |
| R1 | 堆叠 SUR + 差异 Wald;群体 FE + 聚类稳健 SE + 自助Stacked SUR + differential Wald; cohort FE + cluster-robust SE + bootstrap | 已完成done | 表 2:命名分 术偏业 z=5.46;明偏命 z=−1.24 p=.21Table 2: named skill-tilt z = 5.46; lucidity fate-tilt z = −1.24, p = .21 |
| R2 | 结局盲重评(删身份/结局线索、对全池独立重打;397 有效)Outcome-blind rescore (delete identity/outcome cues, re-score the full pool; 397 valid) | 已完成done | 表 2、附录 E:明偏命 变为 z=−3.8 p<.001;解离浮现Table 2 and App. E: fate-tilt becomes z = −3.8, p < .001; dissociation emerges |
| R5 | VIF/相关矩阵 + 优势分析 + 设定曲线VIF / correlation matrix + dominance analysis + specification curve | 已完成done | VIF≤1.71;优势见附录 DVIF ≤ 1.71; dominance in App. D |
| R3a | 客观结局代理(死法序数 + 制度存续年数,盲抽 459 人)Objective outcome proxies (manner-of-death ordinal + survival years, 459) | 已完成done | 建制力对客观存续 t=3.7(主梁非共源);明偏命不复现(客观 Δ z=−1.37 p=.17)Institution-building t = 3.7 on objective survival (master beam not common-source); fate-tilt does not replicate (objective Δ z = −1.37, p = .17) |
| R3b | 预测子(术/建制力)独立盲编码Independent blind coding of the predictors (skill/institution) | 待做planned | 消除术/建制力手工编码端残余共源Removes residual hand-coding common source |
| R4 | 跨模型族复评 + 人类评审 ICCCross-model-family re-scoring + human-rater ICC | 待做planned | 锁定因果读法(当前为去偏关联)Locks the causal reading (currently a de-biased association) |
| R6 | 分层复验 20→404 效度Stratified re-run of validity, 20 → 404 | 待做planned | 效度外推区间Validity extrapolation interval |
| R-ID | 再识别探针:盲评 agent 能否说出被红化的主体是谁,置信几何?Re-identification probe: can a blind agent name the redacted subject, and at what confidence? | 待做planned | 把"身份盲"从设计断言变为受检断言;界定潜在身份泄漏Converts "identity-blind" from a design claim into a tested one; bounds latent-identity leakage |
| R7 | 聚合稳健性(算术均对几何均、峰值术对均值术)+ 范围限制校正之术Aggregation robustness (arithmetic vs geometric mean, peak vs mean skill) + range-restriction-corrected skill | 待做planned | 确认术的解离非聚合或范围限制的伪迹Confirms the skill dissociation is not an aggregation or range artifact |
附录 AAppendix A
测量体系全貌The Full Measurement System
A.1 六条计分轴。 理 Pattern:见微知远(secondOrderSight,预见自身决策的连锁后果,只据当时推理)· 破执自知(egoUndistortion,对自身能力/边界的评估准确度,非谦逊)· 去伪存真(signalDiscrimination,从噪声辨真规律)。玄 Mystery:据实置信(calibratedUncertainty,信心随证据)· 知止有界(boundednessAwareness,对框架适用边界的清醒)· 存玄留白(irreducibilityReverence,让不可化约的内核悬置而非伪收口)。另有六条脚手架透镜(破教条/纳逆耳/破情蔽/知他心/待未知/纳偶然)只辅助推理、不计分;由 12 轴收敛到 6 轴,依据有效维数≈2。
A.2 两条铁律。 非道德防火墙(只认认知准确度;病理性崩溃仍按当时利害计)· 反光环条款(统一交换检验剔除身份信息)。
A.3 四项辅助输出。 覆盖率 κ · 记录类型 · evidentialBasis · 代价加权。
A.4 测量哲学。 明无外部效标;手工参照集只是"第 R+1 位评审";"对 gold 算 MAE/ρ"一律作废。须区分:测量层为免效标内部验证;明作为自变量预测真实结局,是有效标的经验主张,须以 R2/R4 及样本外预测另行辩护,不沿用免效标豁免。
A.1 The six scored axes (canonical names as displayed in the LucidiAtlas; machine keys in italics). Pattern (理): Consequential Foresight (secondOrderSight — foreseeing the knock-on consequences of one's own decisions, reasoning only from contemporaneous information) · Ego Undistortion (egoUndistortion — accuracy of assessing one's own ability and limits, not modesty) · Signal Discrimination (signalDiscrimination — telling real regularity from noise). Mystery (玄): Confidence Calibration (calibratedUncertainty — confidence tracking evidence) · Boundedness Awareness (boundednessAwareness — lucidity about a framework's boundary) · Irreducibility Reverence (irreducibilityReverence — letting the irreducible core remain suspended rather than forcing a false closure). Six scaffold lenses (Doctrinal Non-Capture / Dissent Permeability / Affect Undistortion / Other-Mind Accuracy / Frontier Openness / Contingency Acknowledgment) only aid reasoning and are not scored; the reduction from 12 to 6 axes is justified by effective dimensionality ≈ 2.
A.2 The two hard rules. The amoral firewall (credit only cognitive accuracy; a pathological breakdown is still scored by the stakes at the time) · the anti-halo clause (a uniform exchange test strips out identity information).
A.3 Four auxiliary outputs. Coverage κ · record type · evidentialBasis · cost-weighting.
A.4 Measurement philosophy. Lucidity has no external criterion; the hand-authored reference set is only "the R+1-th rater"; computing MAE or ρ against "gold" is void. The distinction to keep: the measurement layer is criterion-free internal validation; lucidity as an independent variable predicting real outcomes is a criterion-bearing empirical claim, defended separately via R2/R4 and out-of-sample prediction, not under the criterion-free exemption.
A.5 高分群体的清醒范例。 一份剖面比一条定义更易读。表 6 列出取自五个均分最高群体的八位人物的六轴分(0–5)与聚合明(0–100),所有数值均为开放数据集分数(axes_long.csv)。两条规律尤为醒目。其一,在术几近相等时,明仍大幅分化:费曼与海森堡同为一流物理学家(术 97 与 95),明却为 88 与 57。其二,哪一条轴让位,恰恰诊断出清醒是如何失落的。图 9 并置两位术近乎相等的物理学家:伽利略的去伪存真近乎满分(他把科学读对了),但见微知远与破执自知偏低(那场他既未预见、也不肯抽身的对峙),而费曼六轴皆高。清醒不是一个人"拥有"的标量,而是一幅剖面的形状,聚合分只是对它的概括。
A.5 Worked exemplars from the top cohorts. A profile reads more plainly than a definition. Table 6 lists the six axis scores (0–5) and the aggregate lucidity (0–100) for eight figures drawn from the five highest-scoring cohorts; every value is an open-dataset score (axes_long.csv). Two regularities stand out. First, at near-equal skill lucidity still varies widely: Feynman and Heisenberg are both first-rank physicists (skill 97 and 95), yet score lucidity 88 and 57. Second, which axis gives way is diagnostic of how the lucidity was lost. Figure 9 sets two physicists of near-equal skill side by side: Galileo's Signal Discrimination is near the ceiling (he read the science correctly), yet his Consequential Foresight and Ego Undistortion sit low (the confrontation he neither foresaw nor stepped back from), whereas Feynman is high on all six. Lucidity is not a scalar a figure "has"; it is the shape of a profile, and the aggregate only summarizes it.
| 理 PatternPattern | 玄 MysteryMystery | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 人物Figure | 群体Cohort | 术Skill | 明Luc. | 见微Fore. | 破执Ego | 去伪Sig. | 据实Cal. | 知止Bnd. | 存玄Irr. |
| 费曼Richard Feynman | 物理学家physicists | 97 | 88 | 4.1 | 4.3 | 4.5 | 4.1 | 3.7 | 4.6 |
| 海森堡Werner Heisenberg | 物理学家physicists | 95 | 57 | 2.8 | 3.3 | 3.2 | 3.3 | 2.9 | 3.7 |
| 庞加莱Henri Poincaré | 数学家mathematicians | 96 | 88 | 4.0 | 4.0 | 4.6 | 5.0 | 4.6 | 5.0 |
| 高斯Carl F. Gauss | 数学家mathematicians | 99 | 77 | 3.3 | 3.3 | 5.0 | 4.3 | 4.5 | 3.7 |
| 塞尚Paul Cézanne | 艺术家artists | 93 | 84 | 3.4 | 3.7 | 3.4 | 3.7 | 4.0 | 4.6 |
| 瓦格纳Richard Wagner | 艺术家artists | 97 | 55 | 2.4 | 2.0 | 2.7 | 2.0 | 2.6 | 1.7 |
| 释迦牟尼Buddha | 立教者founders-of-faith | 98 | 91 | 4.6 | 4.4 | 3.3 | 3.7 | 3.8 | 4.0 |
| 苏格拉底Socrates | 哲学家philosophers | 92 | 91 | 3.6 | 3.4 | 3.6 | 4.6 | 4.0 | 4.6 |
Table 6取自五个均分最高群体的清醒范例(群体均分:物理学家 79.8,艺术家 78.2,数学家 75.2,立教者 73.7,哲学家 66.2)。轴分 0–5(axes_long.csv);明为聚合 0–100。列名简写——见微=见微知远,破执=破执自知,去伪=去伪存真(理);据实=据实置信,知止=知止有界,存玄=存玄留白(玄)。苏格拉底与庞加莱的玄重型剖面(据实置信与存玄留白近满分)对照瓦格纳在一流术之上的全面塌陷。聚合明为逐阶段 √(理×玄) 的代价加权均值,故不必等于表中跨阶段轴均值之 √,后者仅用以展示剖面形状。Worked exemplars from the five highest-scoring cohorts (mean lucidity: physicists 79.8, artists 78.2, mathematicians 75.2, founders-of-faith 73.7, philosophers 66.2). Axis scores 0–5 (axes_long.csv); lucidity is the aggregate 0–100. Keys — Fore.=Consequential Foresight, Ego=Ego Undistortion, Sig.=Signal Discrimination (Pattern); Cal.=Confidence Calibration, Bnd.=Boundedness Awareness, Irr.=Irreducibility Reverence (Mystery). The Mystery-heavy profiles of Socrates and Poincaré (calibration and reverence for the irreducible near ceiling) contrast with Wagner's uniform collapse at first-rank skill. The aggregate lucidity is the cost-weighted mean of per-phase √(Pattern×Mystery), so it need not equal √ of the tabulated cross-phase axis means, which are shown only to convey profile shape.
附录 BAppendix B
图集:图谱的多重横切The Atlas in Cross-Section: Additional Views
这四幅视图以交互式图谱的方式呈现开放数据集,使读者得见回归所概括的分布。全篇配色一致:图 10 中的金色等明带为明的等值线;图 11–12 的红→琥珀→青标度即图谱的善终色语(红=坍缩,青=存续善终)。
B.1 明的两个坐标:理 Pattern × 玄 Mystery。 明是一对坐标,而非一个标量。图 10 就构成明的两因子作图——理(读取世界的准确度)对玄(把握不可知之界的准确度)——所绘为按完整构念评分的 317 位人物。淡金等高线为等明带:因明 = √(理·玄),等明线即双曲线 理·玄 = c²,阴影向右上方(两因子俱高处)加深。虚线对角线为均衡线 理 = 玄;其右下方(理胜玄)即锐察而封闭者——目光锐利,敬畏稀薄。
These four views render the open dataset the way the interactive atlas does, so a reader can see the distributions the regressions summarize. Colour is used the same way throughout: the gold iso-lucidity bands in Figure 10 are lines of constant lucidity; the red→amber→teal scale in Figures 11–12 is the atlas's ending language (red = collapse, teal = a durable end).
B.1 The two coordinates of lucidity: Pattern × Mystery. Lucidity is a pair, not a scalar. Figure 10 plots the two factors it is built from — Pattern (how accurately the world is read) against Mystery (how accurately the limits of the knowable are held) — for the 317 figures scored on the full construct. The faint gold contours are iso-lucidity bands: because lucidity = √(Pattern·Mystery), a line of constant lucidity is the hyperbola Pattern·Mystery = c², and the shading deepens toward the top-right where both factors are high. The dashed diagonal is the balance line Pattern = Mystery; the region below-right of it (Pattern outruns Mystery) is the brilliant-but-closed reader — sharp sight, thin reverence.
axes_long.csv,每族三轴均值缩放至 0–100)。金色等高线为等明带(理·玄 = c²),阴影向高明加深。红色虚对角线为 理 = 玄。苏格拉底与庞加莱在玄上居高(线上方);瓦格纳两者俱塌。Pattern × Mystery for the 317 fully-scored figures (axes_long.csv, means of each triad rescaled to 0–100). Gold contours are iso-lucidity bands (Pattern·Mystery = c²); shading deepens toward high lucidity. The red dashed diagonal is Pattern = Mystery. Socrates and Poincaré sit high on Mystery (above the line); Wagner collapses on both.B.2 两条能力轴:术 × 建制力,按善终着色。 图 11 将两个手工编码的能力变量对置,并按每点的善终(图谱红→青标度)着色。右上角——高术且高建制力——正是善终(青)聚集处;有术而无建制托底(右下)则常坍缩为红。这是"建制力而非术方为主梁"这一回归结论的描述性投影。
B.2 The two capability axes: Skill × Institution-building, coloured by ending. Figure 11 places the two hand-coded capability variables against each other and colours every point by its ending (the atlas's red→teal scale). The upper-right — high skill and high institution-building — is where the durable (teal) endings concentrate; raw skill without an institution behind it (lower-right) collapses to red as often as not. This is the descriptive shadow of the regression result that institution-building, not skill, is the master beam.
figures.csv);点色=善终,按图谱红(坍缩)→琥珀→青(存续)标度。善终聚于高术/高建制角;高术而建制薄弱(右下)正是红点云集处。Skill × Institution-building for 135 real leaders (figures.csv); point colour = ending on the atlas's red (collapse) → amber → teal (durable) scale. Durable endings cluster in the high-skill/high-institution corner; high skill with a weak institution (lower-right) is where the reds gather.B.3 明 × 善终,并绘出结局色带。 图 12 即 §5 用作 nomological 旁证的那一关系:明对个人与事业善终。水平色带为图谱的结局区(坍缩/中平/存续)。关系真实但松(r ≈ 0.50):高明鲜少落入红带,然散布甚广——尺所测者为判断,而非命运,恰如测量优先的立场所坚持。
B.3 Lucidity × ending, with the outcome bands drawn in. Figure 12 is the single relation §5 leans on for nomological corroboration: lucidity against personal-and-organizational ending. The horizontal bands are the atlas's outcome zones (collapse / mixed / durable). The relation is real but loose (r ≈ 0.50): high lucidity rarely ends in the red band, but the spread is wide — the ruler measures judgment, not fate, exactly as the measurement-first framing insists.
figures.csv);水平色带为图谱结局区。红色引导线为最小二乘拟合(r ≈ 0.50):真实的正向关系但散布宽,正是"判断之尺,而非命运预测器"的视觉佐证。Lucidity × ending for 404 figures (figures.csv); horizontal bands are the atlas outcome zones. The red guide line is the least-squares fit (r ≈ 0.50): a real positive relation with wide scatter, the visual case for "a ruler of judgment, not a predictor of fate."B.4 多群体同轴:术 × 明。 图 13 在共享的术–明平面上叠置四个迥异群体。它们在高术边缘近乎垂直堆叠,却占据不同的明带:物理学家居高(均明 80)、统帅居中(66)、革命者偏低(48),金融家横向散布。术几乎不能将其分开,而明能——这正是跨域通兑之说,示之而非断言。
B.4 Mixed cohorts on one axis: Skill × Lucidity. Figure 13 overlays four very different cohorts on the shared skill–lucidity plane. They stack almost vertically at the high-skill edge, yet occupy different lucidity bands: physicists sit high (mean lucidity 80), commanders in the middle (66), revolutionaries low (48), with financiers spread across. Skill barely separates them; lucidity does — the cross-domain commensurability claim, shown rather than asserted.
figures.csv):物理学家(蓝,均明 80)、统帅(金,66)、金融家(青,62,散布宽)、革命者(砖红,48)。在高术边缘,群体几乎完全沿明而非术分离。Four cohorts on the skill–lucidity plane (figures.csv): physicists (blue, mean lucidity 80), commanders (gold, 66), financiers (teal, 62, wide spread), revolutionaries (brick, 48). At the high-skill edge the cohorts separate almost entirely along lucidity, not skill.B.5 十六领域的清醒之巅:一处峰顶,离散的结局。 图 14 取十六个群体中各自最清醒者——因艺术一域独有两位臻于顶棚的人物(贝多芬与巴赫),故共十七人——同置于术–明平面,并一举编码两个附加变量:标记形状表示大类领域(思想、艺术、权力与治国、企业与金融),标记颜色表示该人的善终,落在图谱红→琥珀→青标度上。两点一望即知。其一,各领域之冠皆挤入一处狭窄的顶棚——术 72–99、明 81–91——不分领域:一位立教者、一位数学家、一位央行家与一位解放者,共处平面一隅,此即跨域通兑之说最强的视觉形式。其二,恰与"以明预测命运"的诱惑相反,他们的结局在同一隅内铺满全域:达尔文与释迦牟尼终于深青(95、90),而苏格拉底——明与全图谱并列最高者——终于 5,那杯毒堇。形状示判断力可跨域通行,颜色示其买不来善终。
B.5 The lucid elite of sixteen fields: one summit, scattered fates. Figure 14 takes the most lucid figure from each of sixteen cohorts — seventeen in all, since the arts, uniquely, contribute two ceiling-level figures (Beethoven and Bach) — and places them on the same skill–lucidity plane, encoding two further variables at once: marker shape is the broad domain family (thought, arts, power & state, enterprise & finance), and marker colour is the figure's ending on the atlas's red→amber→teal scale. Two things read at a glance. First, the field-toppers pack into a narrow ceiling — skill 72–99, lucidity 81–91 — regardless of domain, which is the cross-domain commensurability claim in its strongest visual form: a founder of a religion, a mathematician, a central banker, and a liberator occupy one small corner of the plane. Second, and against any temptation to read lucidity as a fate-predictor, their endings fan across the entire range within that same corner: Darwin and Buddha end in the deep teal (95, 90), while Socrates — tied for the highest lucidity in the whole atlas — ends at 5, the hemlock. Shape shows judgment travels across domains; colour shows it does not buy a soft landing.
figures.csv):物理学家(费曼)、数学家(庞加莱)、立教者(释迦牟尼)、哲学家(苏格拉底)、科学家(达尔文)、经济学家(密尔)、艺术家(贝多芬、巴赫)、统帅(李舜臣)、革命者(圣马丁)、君主(曼德拉)、总统(艾森豪威尔)、政治家(莫内)、外交家(塔列朗)、金融家(芒格)、CEO(沃尔顿)、央行家(沃尔克)。标记形状编码大类领域,颜色编码善终(红=坍缩 → 青=存续)。各领域之冠同处一处高术高明的顶棚(跨域通兑),其结局却在此隅内铺满全域(明是判断之尺,而非命运之预测器)。The most lucid figure from each of sixteen cohorts — seventeen figures, the arts contributing two (figures.csv): physicists (Feynman), mathematicians (Poincaré), founders-of-faith (Buddha), philosophers (Socrates), scientists (Darwin), economists (Mill), artists (Beethoven, Bach), commanders (Yi Sun-sin), revolutionaries (San Martín), sovereigns (Mandela), presidents (Eisenhower), statesmen (Monnet), diplomats (Talleyrand), financiers (Munger), CEOs (Walton), central-bankers (Volcker). Marker shape encodes domain family; marker colour encodes ending (red = collapse → teal = durable). The field-toppers occupy one narrow high-skill/high-lucidity corner (commensurability across domains), yet their endings span the full range within it (lucidity is a ruler of judgment, not a predictor of fate).B.6 撑起结构的两种能力:建制力 × 明。 图 15 将主梁(建制力)对置于偏命之翼(明),绘出全部 404 位领导者,并按善终着色。二者正相关,却仅松散耦合(r ≈ 0.46,共享方差约五分之一):高建制力既不要求、也不蕴含高明。两个非对角象限均有人居——79 人建起长存之制却无相称之明(右下,如瓦格纳),70 人极清醒却少有建制留存(左上,如苏格拉底与费曼)。这正是"应将二者视为两种独立能力"的判别效度依据,也是 §5"解离加主梁"结构的视觉根源:恰因二者半独立地变化,才能在两个结局上给出不同载荷。
B.6 The two capacities that carry the structure: Institution-building × Lucidity. Figure 15 plots the master beam (institution-building) against the fate-tilted wing (lucidity) for all 404 leaders, coloured by ending. The two are positively but only loosely related (r ≈ 0.46, about a fifth of the variance shared): high institution-building neither requires nor implies high lucidity. Both off-diagonal quadrants are populated — 79 leaders build lasting institutions without commensurate lucidity (lower-right, e.g. Wagner), and 70 are highly lucid yet leave little institution behind (upper-left, e.g. Socrates and Feynman). This is the discriminant-validity case for treating the two as separate capacities, and the visual root of the dissociation-and-master-beam structure of §5: precisely because they vary semi-independently, they can load differently on the two outcomes.
figures.csv);点色 = 善终(红=坍缩 → 青=存续)。两种能力仅中度相关(r = 0.46);虚线标出中位数(建制 72,明 64)。两个非对角象限皆有填充:高建制而低明者(右下,如瓦格纳),与高明却少有建制者(左上,如苏格拉底——明为全图谱并列最高,善终却以红色标于毒堇)。建制力与明是两种独立能力,正因如此,它们在 §5 中承载不同的结局。Institution-building × Lucidity for 404 leaders (figures.csv); point colour = ending (red = collapse → teal = durable). The two capacities correlate only moderately (r = 0.46); dashed lines mark the medians (institution 72, lucidity 64). Both off-diagonal quadrants fill in: institution-builders low on lucidity (lower-right, e.g. Wagner) and highly lucid figures who built little (upper-left, e.g. Socrates — the atlas's joint-highest lucidity, yet an ending, in red, at the hemlock). That institution-building and lucidity are distinct capacities is why they can carry different outcomes in §5.B.7 二十个群体一览。 表 7 将整座图谱压缩为每群一行,按明均值降序排列。其中两列以图谱自身的色阶热力着色——明走白→金的清醒色阶,终局走红→琥珀→青的善终色阶——使跨群结构一目了然。明自物理学家(80)递降至革命者(48);而术在几乎所有群体皆高企且近乎持平,这恰是术无法承担区分之责的缘由。
B.7 The twenty cohorts at a glance. Table 7 collapses the whole atlas to one row per cohort, sorted by mean lucidity. Two columns are heat-shaded on the atlas's own scales — Luc on the white→gold lucidity ramp, End on the red→amber→teal ending ramp — so the cross-cohort structure reads at a glance. Lucidity ranges from physicists (80) down to revolutionaries (48); skill is high and nearly flat across almost all cohorts, which is precisely why skill cannot be doing the discriminating work.
| 群体Cohort | nn | 术Sk | 建制In | 朝向Or | 明Luc | 难Df | 终局End | 遗产Leg |
|---|---|---|---|---|---|---|---|---|
| 物理学家Physicists | 20 | 94 | 72 | 81 | 80 | 62 | 71 | 95 |
| 艺术家Artists | 13 | 97 | 79 | 75 | 78 | 60 | 56 | 97 |
| 数学家Mathematicians | 21 | 95 | 76 | 74 | 75 | 63 | 49 | 96 |
| 立教者Founders of faith | 10 | 94 | 85 | 81 | 74 | 67 | 65 | 94 |
| 哲学家Philosophers | 35 | 89 | 76 | 71 | 66 | 63 | 62 | 90 |
| 统帅Commanders | 27 | 91 | 62 | 65 | 66 | 74 | 59 | 64 |
| 创投Venture | 6 | 85 | 80 | 64 | 65 | 65 | 81 | 84 |
| 先秦诸子Pre-Qin thinkers | 41 | 84 | 45 | 62 | 62 | 72 | 47 | 60 |
| 金融家Financiers | 48 | 86 | 65 | 54 | 62 | 59 | 65 | 62 |
| 外交家Diplomats | 9 | 82 | 69 | 65 | 62 | 80 | 65 | 67 |
| 政治家Statesmen | 16 | 84 | 77 | 75 | 61 | 72 | 77 | 78 |
| 科学家Scientists | 14 | 88 | 66 | 65 | 60 | 60 | 71 | 81 |
| 企业家CEOs | 32 | 87 | 72 | 56 | 60 | 62 | 67 | 69 |
| 经济学家Economists | 15 | 86 | 71 | 76 | 60 | 54 | 78 | 77 |
| 君主Sovereigns | 59 | 83 | 74 | 65 | 59 | 73 | 63 | 70 |
| 教育家Educators | 9 | 75 | 76 | 76 | 58 | 59 | 76 | 78 |
| 罗马Rome | 19 | 78 | 47 | 62 | 58 | 68 | 41 | 53 |
| 央行行长Central bankers | 9 | 74 | 71 | 67 | 57 | 73 | 56 | 58 |
| 总统Presidents | 40 | 68 | 58 | 60 | 52 | 66 | 51 | 56 |
| 革命者Revolutionaries | 16 | 80 | 58 | 61 | 48 | 79 | 40 | 56 |
| 全样本All figures | 459 | 85 | 67 | 66 | 62 | 67 | 60 | 72 |
Table 7各群体均值(figures.csv,n=459;朝向、难度、终局、遗产)。明与终局单元格按图谱的清醒与善终色阶着色。群体按明均值降序,末行汇总全样本。Per-cohort means (figures.csv, n=459; Or = orientation, Df = difficulty, End = ending, Leg = legacy). Luc and End cells are shaded on the atlas's lucidity and ending scales. Cohorts sorted by mean lucidity; the final row pools all figures.
B.8 身份信号:先量出,再剥除——具名 vs 匿名 明。 图 16 将每人的具名明(可见姓名时的评分)对置于其结局盲明(据脱敏传记的评分),覆盖 397 位完成重打者。两桩事实并存:二者均值相等——皆为 61.1,故揭名并不带来总体虚高——但逐人平均相差约 11 分(r = 0.68),且拟合线(斜率 0.49,较虚线 45° 恒等线更平缓)显示盲评分向均值收缩:揭名拉伸了两端。这便是被显影并量化的光环——正是 §5 与表 2 改用盲分、而非具名分来做命运分析的缘由。
B.8 The identity signal, measured then removed: named vs blind lucidity. Figure 16 plots each figure's named lucidity (scored with the name visible) against its outcome-blind lucidity (scored from a redacted biography) for the 397 fully re-scored figures. Two facts sit together. The two agree on average — both means are 61.1, so naming adds no aggregate inflation — yet they disagree per figure by about 11 points on average (r = 0.68), and the fit line (slope 0.49, flatter than the dashed 45°) shows the blind scores shrink toward the mean: naming stretches the tails. This is the halo made visible and quantified — the reason §5 and Table 2 run the fate analysis on the blind scores rather than the named ones.
figures.csv);点色 = 善终。均值重合(61.1 对 61.1);逐人 r = 0.68,平均 |Δ| ≈ 11。拟合线(砖红)较恒等线(虚线)更平缓,故盲评把两端向中间回归——此即盲重评所剥除的光环。Named vs outcome-blind lucidity for 397 figures (figures.csv); point colour = ending. Means coincide (61.1 vs 61.1); per-figure r = 0.68, mean |Δ| ≈ 11. The fit (brick) is flatter than the identity (dashed), so blind scoring regresses the extremes toward the middle — the halo the blind rescore removes.B.9 声名并非软着陆:遗产 vs 终局。 图 17 将身后遗产(世人对其事功的最终评价)对置于个人与事业的终局。二者正相关(r ≈ 0.58),却远非同一:每一遗产水平上的纵向散布都很宽,左上角——声名巍然而终局艰难——填得颇满。被后世铭记与善终而终,是相关却可分的两件事,这正是图谱将其编为两个变量而非一个的缘由。
B.9 Reputation is not a soft landing: legacy vs ending. Figure 17 plots posthumous legacy (how the world came to rate the work) against personal-and-organizational ending. They are positively related (r ≈ 0.58) but far from identical: the vertical scatter at every legacy level is wide, and the upper-left — towering legacy, hard ending — is well populated. Being remembered well and ending well are correlated, separable things, which is why the atlas scores them as two variables rather than one.
figures.csv);砖红线为最小二乘拟合(r ≈ 0.58,终局 = 13.9 + 0.63 遗产)。宽阔的纵向散布——尤以填满的高遗产/低终局区为甚——正是将声名与个人命运分作两个结局的缘由。Legacy × ending for 404 figures (figures.csv); the brick line is the least-squares fit (r ≈ 0.58, ending = 13.9 + 0.63 legacy). The wide vertical spread — especially the well-filled high-legacy/low-ending region — is why reputation and personal fate are kept as distinct outcomes.B.10 明的形状:六轴剖面。 图 18 将六条轴的均值绘于雷达——三条理轴居右上,三条玄轴居左下。汇总剖面并不浑圆:理(5 分制均值 3.2–3.3)始终高出玄(2.5–3.0),而全语料最低的一轴是存玄留白(2.54)——这批人物平均而言,读得懂世界胜过守得住其边界。两位范例令此不对称具象:苏格拉底(青)在玄一侧鼓胀;拿破仑(砖红,虚线)则为镜像——理强而玄薄,即那位明察却封闭的读者。
B.10 The shape of lucidity: a six-axis profile. Figure 18 draws the mean of each of the six axes on a radar — the three Pattern (理) axes on the upper-right, the three Mystery (玄) axes on the lower-left. The pooled profile is not round: Pattern (mean 3.2–3.3 of 5) consistently outreaches Mystery (2.5–3.0), and the single lowest axis across the whole corpus is Irreducibility Reverence (2.54) — these figures, on average, read the world better than they hold its limits. Two exemplars make the asymmetry concrete: Socrates (teal) balloons on the Mystery side; Napoleon (brick, dashed) is the mirror image — strong on Pattern, thin on Mystery, the brilliant-but-closed reader.
axes_long.csv,轴均值 0–5)。理(见微知远/破执自知/去伪存真):3.25 / 3.14 / 3.31。玄(据实置信/知止有界/存玄留白):2.89 / 3.00 / 2.54。汇总剖面偏理;苏格拉底偏玄,拿破仑相反。Six-axis radar (axes_long.csv, axis means on 0–5). Pattern (理, slate labels): 3.25 / 3.14 / 3.31. Mystery (玄, gold labels): 2.89 / 3.00 / 2.54. The pooled profile leans to Pattern; Socrates leans to Mystery, Napoleon the reverse.附录 CAppendix C
图谱索引:全 459 人速览The Atlas Index: All 459 Figures at a Glance
表 8 是整座图谱压缩成的一张密排索引——459 人无一遗漏,各附完整指标行,按群体分组(群体按明均值排序,群内按明排序)。两列承载图谱的色彩语言:明按白→金的清醒色阶着色(愈深金愈清醒),终按红→琥珀→青的善终色阶着色(红=坍缩,青=存续)。并读这两条热力列,便是本文论点的一图之现:清醒之金与善终之青彼此相关,却肉眼可辨地各自独立——苏格拉底及其余深金之名,散落于每一种终局之色,红色亦在其列。列名:群群体,世世纪(负号为公元前),术技艺,建建制力,朝朝向,明清醒,难难度,终终局,遗遗产。
Table 8 is the complete atlas in one compact index — every one of the 459 figures with its full metric line, grouped by cohort (cohorts ordered by mean lucidity, figures within each cohort by lucidity). Two columns carry the atlas's colour language: Luc is shaded on the white→gold lucidity ramp (deeper gold = more lucid), and End on the red→amber→teal ending ramp (red = collapse, teal = a durable end). Reading down the two heat columns together is the paper's thesis in one view: the gold of lucidity and the teal of a good ending are correlated but visibly independent — Socrates and the other deep-gold names are scattered across every ending colour, red included. Column keys: Coh cohort, C century (negative = BCE), Sk skill, In institution-building, Or orientation, Luc lucidity, Df difficulty, End ending, Leg legacy.
| 姓名Name | 群Coh | 世C | 术Sk | 建In | 朝Or | 明Luc | 难Df | 终End | 遗Leg |
|---|---|---|---|---|---|---|---|---|---|
| 物理学家 · n=20 · 明 80 · 终 71Physicists · n=20 · Luc 80 · End 71 | |||||||||
| 恩里科·费米Enrico Fermi | Phys | 20 | 96 | 88 | 72 | 88 | 64 | 68 | 95 |
| 莉泽·迈特纳Lise Meitner | Phys | 19 | 90 | 62 | 89 | 88 | 74 | 66 | 94 |
| 理查德·费曼Richard Feynman | Phys | 20 | 97 | 65 | 85 | 88 | 60 | 82 | 95 |
| 苏布拉马尼扬·钱德拉塞卡Subrahmanyan Chandrasekhar | Phys | 20 | 93 | 80 | 86 | 88 | 68 | 88 | 95 |
| 詹姆斯·克拉克·麦克斯韦James Clerk Maxwell | Phys | 19 | 97 | 72 | 85 | 86 | 52 | 58 | 98 |
| 路德维希·玻尔兹曼Ludwig Boltzmann | Phys | 19 | 95 | 58 | 85 | 86 | 60 | 20 | 97 |
| 迈克尔·法拉第Michael Faraday | Phys | 18 | 94 | 72 | 89 | 86 | 53 | 85 | 96 |
| 尼尔斯·玻尔Niels Bohr | Phys | 19 | 92 | 90 | 88 | 86 | 66 | 88 | 90 |
| 吴健雄Chien-Shiung Wu | Phys | 20 | 93 | 66 | 83 | 84 | 64 | 82 | 94 |
| 列夫·朗道Lev Landau | Phys | 20 | 95 | 90 | 81 | 84 | 76 | 42 | 96 |
| 马克斯·玻恩Max Born | Phys | 19 | 94 | 82 | 86 | 84 | 61 | 82 | 94 |
| 亨德里克·洛伦兹Hendrik Lorentz | Phys | 19 | 92 | 72 | 83 | 83 | 58 | 92 | 94 |
| 沃尔夫冈·泡利Wolfgang Pauli | Phys | 19 | 94 | 50 | 86 | 83 | 59 | 78 | 95 |
| 欧内斯特·卢瑟福Ernest Rutherford | Phys | 19 | 96 | 88 | 82 | 78 | 54 | 88 | 96 |
| 埃尔温·薛定谔Erwin Schrödinger | Phys | 19 | 94 | 45 | 80 | 77 | 66 | 72 | 94 |
| 马克斯·普朗克Max Planck | Phys | 19 | 92 | 76 | 80 | 75 | 71 | 58 | 96 |
| 约瑟夫·约翰·汤姆孙J. J. Thomson | Phys | 19 | 93 | 92 | 83 | 72 | 54 | 90 | 94 |
| 保罗·狄拉克Paul Dirac | Phys | 20 | 97 | 55 | 79 | 70 | 43 | 85 | 96 |
| 维尔纳·海森堡Werner Heisenberg | Phys | 20 | 95 | 72 | 52 | 57 | 66 | 62 | 90 |
| 伽利略·伽利雷Galileo Galilei | Phys | 16 | 96 | 55 | 70 | 53 | 67 | 34 | 95 |
| 艺术家 · n=13 · 明 78 · 终 56Artists · n=13 · Luc 78 · End 56 | |||||||||
| 路德维希·凡·贝多芬Ludwig van Beethoven | Art | 18 | 99 | 82 | 84 | 89 | 65 | 52 | 99 |
| 约翰·塞巴斯蒂安·巴赫Johann Sebastian Bach | Art | 17 | 99 | 88 | 83 | 85 | 54 | 70 | 99 |
| 保罗·塞尚Paul Cézanne | Art | 19 | 93 | 86 | 86 | 84 | 63 | 60 | 97 |
| 伦勃朗·凡·莱因Rembrandt van Rijn | Art | 17 | 96 | 88 | 82 | 83 | 68 | 30 | 96 |
| 沃尔夫冈·阿马德乌斯·莫扎特Wolfgang Amadeus Mozart | Art | 18 | 99 | 72 | 78 | 82 | 56 | 14 | 99 |
| 伊戈尔·斯特拉文斯基Igor Stravinsky | Art | 19 | 95 | 78 | 80 | 81 | 55 | 82 | 95 |
| 米开朗基罗·梅里西·达·卡拉瓦乔Caravaggio | Art | 16 | 96 | 80 | 77 | 80 | 69 | 15 | 96 |
| 弗朗西斯科·戈雅Francisco Goya | Art | 18 | 96 | 62 | 72 | 77 | 54 | 60 | 96 |
| 列奥纳多·达·芬奇Leonardo da Vinci | Art | 15 | 99 | 60 | 77 | 77 | 52 | 88 | 99 |
| 巴勃罗·毕加索Pablo Picasso | Art | 19 | 97 | 96 | 60 | 75 | 58 | 88 | 98 |
| 米开朗基罗Michelangelo | Art | 15 | 99 | 78 | 75 | 74 | 61 | 92 | 99 |
| 文森特·梵高Vincent van Gogh | Art | 19 | 97 | 58 | 79 | 74 | 71 | 8 | 98 |
| 理查德·瓦格纳Richard Wagner | Art | 19 | 97 | 96 | 41 | 55 | 54 | 66 | 96 |
| 数学家 · n=21 · 明 75 · 终 49Mathematicians · n=21 · Luc 75 · End 49 | |||||||||
| 埃米·诺特Emmy Noether | Math | 19 | 96 | 90 | 89 | 88 | 62 | 42 | 96 |
| 亨利·庞加莱Henri Poincaré | Math | 19 | 96 | 80 | 83 | 88 | 70 | 80 | 95 |
| 约翰·冯·诺伊曼John von Neumann | Math | 20 | 97 | 92 | 71 | 86 | 66 | 38 | 95 |
| 安德雷·科尔莫哥洛夫Andrey Kolmogorov | Math | 20 | 98 | 93 | 83 | 85 | 54 | 88 | 97 |
| 波恩哈德·黎曼Bernhard Riemann | Math | 19 | 97 | 85 | 82 | 85 | 66 | 32 | 96 |
| 阿基米德Archimedes | Math | −3 | 97 | 60 | 73 | 80 | 53 | 15 | 97 |
| 莱昂哈德·欧拉Leonhard Euler | Math | 18 | 97 | 88 | 86 | 80 | 56 | 86 | 96 |
| 皮埃尔·德·费马Pierre de Fermat | Math | 17 | 90 | 62 | 68 | 80 | 55 | 78 | 96 |
| 约瑟夫-路易·拉格朗日Joseph-Louis Lagrange | Math | 18 | 95 | 85 | 78 | 79 | 57 | 90 | 96 |
| 尼尔斯·亨里克·阿贝尔Niels Henrik Abel | Math | 19 | 95 | 38 | 80 | 79 | 62 | 12 | 96 |
| 卡尔·弗里德里希·高斯Carl Friedrich Gauss | Math | 18 | 99 | 82 | 51 | 77 | 43 | 88 | 96 |
| 大卫·希尔伯特David Hilbert | Math | 19 | 95 | 96 | 81 | 76 | 76 | 30 | 96 |
| 斯里尼瓦瑟·拉马努金Srinivasa Ramanujan | Math | 19 | 95 | 40 | 79 | 74 | 84 | 25 | 90 |
| 埃瓦里斯特·伽罗瓦Évariste Galois | Math | 19 | 96 | 30 | 70 | 72 | 66 | 8 | 97 |
| 欧几里得Euclid | Math | −4 | 88 | 90 | 78 | 70 | 42 | 68 | 98 |
| 约瑟夫·傅里叶Joseph Fourier | Math | 18 | 90 | 72 | 65 | 69 | 64 | 62 | 94 |
| 皮埃尔-西蒙·拉普拉斯Pierre-Simon Laplace | Math | 18 | 96 | 82 | 56 | 68 | 59 | 85 | 95 |
| 戈特弗里德·威廉·莱布尼茨Gottfried Wilhelm Leibniz | Math | 17 | 96 | 88 | 65 | 67 | 55 | 42 | 95 |
| 亚历山大·格罗滕迪克Alexander Grothendieck | Math | 20 | 99 | 95 | 80 | 65 | 72 | 35 | 98 |
| 格奥尔格·康托尔Georg Cantor | Math | 19 | 93 | 85 | 66 | 56 | 81 | 20 | 93 |
| 库尔特·哥德尔Kurt Gödel | Math | 20 | 96 | 60 | 69 | 56 | 70 | 15 | 96 |
| 立教者 · n=10 · 明 74 · 终 65Founders of faith · n=10 · Luc 74 · End 65 | |||||||||
| 释迦牟尼Buddha (Siddhartha Gautama) | Faith | −6 | 98 | 90 | 94 | 91 | 55 | 90 | 98 |
| 奥古斯丁Augustine of Hippo | Faith | 4 | 96 | 85 | 85 | 84 | 70 | 72 | 97 |
| 龙树Nagarjuna | Faith | 2 | 96 | 78 | 83 | 84 | 59 | 60 | 92 |
| 慧能Huineng | Faith | 7 | 95 | 82 | 87 | 81 | 62 | 88 | 95 |
| 玄奘Xuanzang | Faith | 7 | 95 | 82 | 90 | 80 | 70 | 90 | 86 |
| 阿育王Ashoka the Great | Faith | −4 | 82 | 88 | 68 | 73 | 60 | 66 | 86 |
| 保罗Paul the Apostle | Faith | 1 | 95 | 92 | 83 | 71 | 79 | 12 | 98 |
| 君士坦丁Constantine the Great | Faith | 3 | 90 | 90 | 53 | 60 | 70 | 84 | 92 |
| 马丁·路德Martin Luther | Faith | 15 | 92 | 88 | 69 | 59 | 68 | 84 | 96 |
| 耶稣Jesus of Nazareth | Faith | −1 | 96 | 72 | 96 | 54 | 80 | 5 | 100 |
| 哲学家 · n=35 · 明 66 · 终 62Philosophers · n=35 · Luc 66 · End 62 | |||||||||
| 苏格拉底Socrates | Phil | −5 | 92 | 60 | 92 | 91 | 83 | 5 | 100 |
| 休谟David Hume | Phil | 18 | 90 | 65 | 86 | 89 | 40 | 90 | 88 |
| 庄子Zhuangzi | Phil | −4 | 88 | 62 | 79 | 89 | 46 | 65 | 88 |
| 罗素Bertrand Russell | Phil | 19 | 90 | 82 | 83 | 80 | 79 | 82 | 90 |
| 罗尔斯John Rawls | Phil | 20 | 88 | 88 | 88 | 80 | 83 | 88 | 90 |
| 老子Laozi | Phil | −6 | 85 | 72 | 76 | 79 | 45 | 58 | 92 |
| 龙树Nāgārjuna | Phil | 2 | 92 | 85 | 77 | 78 | 53 | 55 | 95 |
| 维特根斯坦Ludwig Wittgenstein | Phil | 20 | 93 | 82 | 83 | 77 | 84 | 60 | 92 |
| 洛克John Locke | Phil | 17 | 88 | 82 | 76 | 75 | 53 | 82 | 90 |
| 孟德斯鸠Montesquieu | Phil | 17 | 84 | 78 | 81 | 75 | 51 | 72 | 90 |
| 阿伦特Hannah Arendt | Phil | 20 | 86 | 66 | 79 | 73 | 76 | 72 | 86 |
| 迈蒙尼德Maimonides | Phil | 12 | 88 | 78 | 66 | 72 | 67 | 78 | 90 |
| 亚里士多德Aristotle | Phil | −4 | 97 | 85 | 80 | 71 | 51 | 66 | 100 |
| 伊壁鸠鲁Epicurus | Phil | −4 | 82 | 78 | 72 | 71 | 50 | 72 | 82 |
| 培根Francis Bacon | Phil | 16 | 88 | 88 | 79 | 71 | 77 | 40 | 90 |
| 孔子Confucius | Phil | −6 | 88 | 90 | 69 | 69 | 66 | 60 | 100 |
| 狄德罗Denis Diderot | Phil | 18 | 88 | 68 | 87 | 68 | 73 | 66 | 82 |
| 斯宾诺莎Baruch Spinoza | Phil | 17 | 92 | 60 | 83 | 65 | 72 | 40 | 90 |
| 王阳明Wang Yangming | Phil | 15 | 86 | 78 | 71 | 65 | 69 | 70 | 88 |
| 奥古斯丁Augustine of Hippo | Phil | 4 | 90 | 82 | 52 | 63 | 66 | 55 | 98 |
| 康德Immanuel Kant | Phil | 18 | 96 | 82 | 68 | 63 | 38 | 90 | 95 |
| 伏尔泰Voltaire | Phil | 17 | 90 | 72 | 77 | 63 | 66 | 78 | 88 |
| 波普尔Karl Popper | Phil | 20 | 90 | 80 | 63 | 62 | 73 | 88 | 82 |
| 阿威罗伊(伊本·鲁世德)Averroes | Phil | 12 | 88 | 65 | 68 | 61 | 70 | 35 | 82 |
| 笛卡尔René Descartes | Phil | 16 | 90 | 72 | 71 | 59 | 51 | 48 | 92 |
| 孟子Mencius | Phil | −4 | 84 | 75 | 70 | 57 | 62 | 68 | 90 |
| 商羯罗Adi Shankara | Phil | 8 | 92 | 88 | 55 | 56 | 54 | 55 | 92 |
| 霍布斯Thomas Hobbes | Phil | 17 | 84 | 68 | 44 | 56 | 70 | 72 | 88 |
| 柏拉图Plato | Phil | −5 | 96 | 88 | 62 | 54 | 53 | 80 | 100 |
| 尼采Friedrich Nietzsche | Phil | 19 | 92 | 55 | 72 | 53 | 66 | 10 | 90 |
| 芝诺(斯多亚)Zeno of Citium | Phil | −4 | 80 | 84 | 78 | 51 | 51 | 74 | 85 |
| 塞内加Seneca | Phil | −1 | 78 | 55 | 52 | 50 | 85 | 10 | 80 |
| 萨特Jean-Paul Sartre | Phil | 20 | 85 | 82 | 43 | 48 | 68 | 58 | 72 |
| 卢梭Jean-Jacques Rousseau | Phil | 18 | 90 | 82 | 39 | 47 | 75 | 34 | 94 |
| 黑格尔G. W. F. Hegel | Phil | 18 | 92 | 85 | 55 | 37 | 49 | 82 | 88 |
| 统帅 · n=27 · 明 66 · 终 59Commanders · n=27 · Luc 66 · End 59 | |||||||||
| 李舜臣Yi Sun-sin | Cmdr | 16 | 95 | 60 | 92 | 89 | 93 | 72 | 85 |
| 李靖Li Jing | Cmdr | 6 | 95 | 72 | 80 | 82 | 74 | 92 | 85 |
| 速不台Subutai | Cmdr | 12 | 96 | 65 | 58 | 81 | 56 | 78 | 60 |
| 亚历山大·苏沃洛夫Alexander Suvorov | Cmdr | 18 | 96 | 83 | 77 | 79 | 81 | 68 | 80 |
| 哈立德·伊本·瓦利德Khalid ibn al-Walid | Cmdr | 6 | 96 | 58 | 74 | 79 | 76 | 72 | 90 |
| 徐达Xu Da | Cmdr | 14 | 92 | 62 | 85 | 78 | 80 | 92 | 88 |
| 威灵顿公爵Duke of Wellington | Cmdr | 18 | 96 | 68 | 85 | 74 | 75 | 97 | 85 |
| 埃里希·冯·曼施坦因Erich von Manstein | Cmdr | 19 | 92 | 65 | 27 | 74 | 69 | 60 | 58 |
| 罗伯特·E·李Robert E. Lee | Cmdr | 19 | 92 | 55 | 78 | 74 | 63 | 72 | 32 |
| 米哈伊尔·图哈切夫斯基Mikhail Tukhachevsky | Cmdr | 19 | 88 | 85 | 60 | 71 | 84 | 10 | 80 |
| 大西庇阿Scipio Africanus | Cmdr | −3 | 92 | 60 | 74 | 68 | 77 | 70 | 90 |
| 斯坦利·麦克里斯特尔Stanley McChrystal | Cmdr | 20 | 82 | 68 | 64 | 68 | 52 | · | |
| 霍去病Huo Qubing | Cmdr | −2 | 97 | 48 | 81 | 67 | 88 | 80 | 75 |
| 伯纳德·蒙哥马利Bernard Montgomery | Cmdr | 19 | 84 | 68 | 72 | 66 | 60 | 82 | 72 |
| 古斯塔夫二世·阿道夫Gustavus Adolphus | Cmdr | 16 | 92 | 90 | 59 | 66 | 81 | 33 | 82 |
| 岳飞Yue Fei | Cmdr | 12 | 99 | 50 | 83 | 66 | 80 | 8 | 30 |
| 乔治·巴顿George S. Patton | Cmdr | 19 | 93 | 52 | 62 | 65 | 62 | 42 | 72 |
| 戴维·彼得雷乌斯David Petraeus | Cmdr | 20 | 85 | 72 | 58 | 64 | 49 | · | |
| 马尔博罗公爵Duke of Marlborough | Cmdr | 17 | 95 | 58 | 53 | 63 | 80 | 62 | 70 |
| 贝利撒留Belisarius | Cmdr | 6 | 92 | 55 | 84 | 62 | 83 | 55 | 30 |
| 海因茨·古德里安Heinz Guderian | Cmdr | 19 | 90 | 68 | 29 | 61 | 55 | 68 | 60 |
| 霍雷肖·纳尔逊Horatio Nelson | Cmdr | 18 | 94 | 62 | 72 | 61 | 84 | 80 | 90 |
| 格奥尔基·朱可夫Georgy Zhukov | Cmdr | 19 | 92 | 72 | 60 | 58 | 88 | 65 | 80 |
| 埃尔温·隆美尔Erwin Rommel | Cmdr | 19 | 90 | 50 | 54 | 53 | 81 | 55 | 10 |
| 汉尼拔·巴卡Hannibal Barca | Cmdr | −3 | 97 | 45 | 58 | 47 | 94 | 35 | 15 |
| 韩信Han Xin | Cmdr | −3 | 95 | 45 | 48 | 46 | 83 | 8 | 80 |
| 昆克蒂利乌斯·瓦鲁斯Publius Quinctilius Varus | Cmdr | −1 | 42 | 30 | 41 | 15 | 56 | 8 | 10 |
| 创投 · n=6 · 明 65 · 终 81Venture · n=6 · Luc 65 · End 81 | |||||||||
| 乔治·多里奥Georges Doriot | VC | 19 | 82 | 85 | 79 | 72 | 79 | 85 | 88 |
| 维诺德·科斯拉Vinod Khosla | VC | 20 | 84 | 72 | 59 | 67 | 65 | · | |
| 唐·瓦伦丁Don Valentine | VC | 20 | 90 | 90 | 69 | 66 | 60 | 90 | 90 |
| 尤金·克莱纳Eugene Kleiner | VC | 20 | 85 | 80 | 64 | 66 | 63 | 80 | 80 |
| 马克·安德森Marc Andreessen | VC | 20 | 85 | 80 | 57 | 64 | 64 | · | |
| 汤姆·帕金斯Tom Perkins | VC | 20 | 85 | 72 | 57 | 55 | 57 | 68 | 78 |
| 先秦诸子 · n=41 · 明 62 · 终 47Pre-Qin thinkers · n=41 · Luc 62 · End 47 | |||||||||
| 范蠡Fan Li | PreQ | −6 | 95 | 55 | 65 | 90 | 60 | 97 | 65 |
| 孙武Sun Tzu (Sun Wu) | PreQ | −6 | 97 | 80 | 61 | 89 | 39 | 90 | 99 |
| 蔺相如Lin Xiangru | PreQ | −4 | 90 | 38 | 86 | 87 | 78 | 82 | 65 |
| 乐毅Yue Yi | PreQ | −3 | 96 | 35 | 68 | 84 | 70 | 78 | 70 |
| 孙膑Sun Bin | PreQ | −4 | 92 | 38 | 59 | 79 | 61 | 72 | 86 |
| 子产Zichan | PreQ | −6 | 85 | 88 | 77 | 79 | 67 | 85 | 88 |
| 晋文公Duke Wen of Jin | PreQ | −7 | 92 | 75 | 61 | 78 | 84 | 85 | 72 |
| 孙叔敖Sunshu Ao | PreQ | −7 | 84 | 88 | 82 | 78 | 69 | 78 | 88 |
| 王翦Wang Jian | PreQ | −3 | 93 | 45 | 63 | 78 | 71 | 85 | 70 |
| 晏婴Yan Ying | PreQ | −6 | 83 | 38 | 81 | 77 | 62 | 82 | 70 |
| 李牧Li Mu | PreQ | −3 | 90 | 20 | 77 | 74 | 81 | 8 | 32 |
| 楚庄王King Zhuang of Chu | PreQ | −7 | 84 | 63 | 71 | 73 | 80 | 88 | 72 |
| 白起Bai Qi | PreQ | −4 | 97 | 25 | 64 | 72 | 82 | 10 | 55 |
| 燕昭王King Zhao of Yan | PreQ | −4 | 85 | 50 | 87 | 72 | 80 | 88 | 62 |
| 管仲Guan Zhong | PreQ | −8 | 95 | 82 | 63 | 71 | 59 | 88 | 85 |
| 百里奚Baili Xi | PreQ | −7 | 82 | 68 | 76 | 69 | 73 | 88 | 80 |
| 信陵君Lord Xinling | PreQ | −3 | 84 | 22 | 72 | 69 | 79 | 22 | 52 |
| 田单Tian Dan | PreQ | −3 | 90 | 25 | 69 | 69 | 78 | 72 | 58 |
| 赵武灵王King Wuling of Zhao | PreQ | −4 | 88 | 70 | 71 | 67 | 66 | 2 | 68 |
| 李悝Li Kui | PreQ | −5 | 82 | 92 | 84 | 67 | 73 | 88 | 90 |
| 张仪Zhang Yi | PreQ | −4 | 95 | 20 | 17 | 67 | 68 | 55 | 45 |
| 勾践Goujian, King of Yue | PreQ | −6 | 88 | 50 | 54 | 64 | 67 | 80 | 48 |
| 齐桓公Duke Huan of Qi | PreQ | −8 | 80 | 45 | 62 | 63 | 65 | 3 | 50 |
| 秦穆公Duke Mu of Qin | PreQ | −7 | 80 | 38 | 65 | 63 | 64 | 82 | 62 |
| 廉颇Lian Po | PreQ | −4 | 88 | 20 | 64 | 60 | 69 | 28 | 48 |
| 伍子胥Wu Zixu | PreQ | −6 | 90 | 45 | 44 | 60 | 89 | 8 | 48 |
| 屈原Qu Yuan | PreQ | −4 | 74 | 28 | 88 | 57 | 79 | 8 | 74 |
| 平原君Lord Pingyuan | PreQ | −3 | 70 | 30 | 59 | 56 | 52 | 82 | 58 |
| 孟尝君Lord Mengchang | PreQ | −4 | 72 | 16 | 33 | 54 | 63 | 45 | 30 |
| 吕不韦Lü Buwei | PreQ | −3 | 85 | 45 | 34 | 54 | 81 | 12 | 62 |
| 范雎Fan Ju | PreQ | −3 | 88 | 52 | 45 | 53 | 76 | 60 | 68 |
| 李斯Li Si | PreQ | −3 | 92 | 90 | 62 | 52 | 82 | 5 | 88 |
| 商鞅Shang Yang | PreQ | −4 | 95 | 92 | 70 | 48 | 81 | 3 | 95 |
| 文种Wen Zhong | PreQ | −5 | 90 | 58 | 77 | 48 | 82 | 10 | 55 |
| 春申君Lord Chunshen | PreQ | −3 | 74 | 44 | 50 | 47 | 73 | 8 | 46 |
| 吴起Wu Qi | PreQ | −5 | 97 | 42 | 61 | 43 | 79 | 8 | 50 |
| 荆轲Jing Ke | PreQ | −3 | 42 | 5 | 54 | 38 | 74 | 8 | 35 |
| 苏秦Su Qin | PreQ | −4 | 92 | 15 | 23 | 35 | 80 | 8 | 35 |
| 庞涓Pang Juan | PreQ | −4 | 70 | 8 | 46 | 29 | 69 | 5 | 8 |
| 宋襄公Duke Xiang of Song | PreQ | −7 | 35 | 15 | 47 | 24 | 75 | 32 | 20 |
| 赵括Zhao Kuo | PreQ | −3 | 50 | 10 | 69 | 24 | 62 | 6 | 8 |
| 金融家 · n=48 · 明 62 · 终 65Financiers · n=48 · Luc 62 · End 65 | |||||||||
| 查理·芒格Charlie Munger | Fin | 20 | 90 | 78 | 76 | 87 | 57 | 85 | 82 |
| 沃伦·巴菲特Warren Buffett | Fin | 20 | 95 | 80 | 83 | 85 | 51 | · | |
| 约翰·邓普顿John Templeton | Fin | 20 | 88 | 70 | 78 | 84 | 62 | 85 | 85 |
| 阿马迪奥·贾尼尼Amadeo Giannini | Fin | 19 | 88 | 92 | 81 | 82 | 77 | 88 | 90 |
| 约翰·博格尔John Bogle | Fin | 20 | 82 | 92 | 85 | 82 | 66 | 90 | 92 |
| 斯坦利·德鲁肯米勒Stanley Druckenmiller | Fin | 20 | 90 | 55 | 59 | 81 | 59 | · | |
| 亚当·斯密Adam Smith | Fin | 18 | 90 | 72 | 75 | 80 | 32 | 92 | 92 |
| 本杰明·格雷厄姆Benjamin Graham | Fin | 19 | 90 | 72 | 77 | 80 | 66 | 90 | 88 |
| 伯纳德·巴鲁克Bernard Baruch | Fin | 19 | 88 | 40 | 65 | 80 | 61 | 65 | 40 |
| 霍华德·马克斯Howard Marks | Fin | 20 | 85 | 70 | 62 | 80 | 52 | · | |
| 詹姆斯·德·罗斯柴尔德James de Rothschild | Fin | 18 | 90 | 90 | 56 | 79 | 62 | 88 | 88 |
| 乔治·索罗斯George Soros | Fin | 20 | 90 | 55 | 53 | 77 | 62 | · | |
| 大卫·泰珀David Tepper | Fin | 20 | 86 | 58 | 54 | 76 | 51 | · | |
| 约翰·梅纳德·凯恩斯John Maynard Keynes | Fin | 19 | 92 | 72 | 68 | 73 | 62 | 88 | 85 |
| 斯蒂芬·吉拉德Stephen Girard | Fin | 18 | 88 | 75 | 70 | 72 | 75 | 85 | 72 |
| 保罗·沃伯格Paul Warburg | Fin | 19 | 85 | 88 | 75 | 71 | 68 | 82 | 90 |
| 亨利·克拉维斯Henry Kravis | Fin | 20 | 85 | 78 | 57 | 70 | 55 | · | |
| 杰米·戴蒙Jamie Dimon | Fin | 20 | 85 | 78 | 60 | 70 | 51 | · | |
| 肯·格里芬Ken Griffin | Fin | 20 | 88 | 70 | 49 | 70 | 57 | · | |
| 阿比盖尔·约翰逊Abigail Johnson | Fin | 20 | 78 | 80 | 60 | 69 | 51 | · | |
| 大卫·李嘉图David Ricardo | Fin | 18 | 92 | 65 | 60 | 69 | 61 | 88 | 85 |
| 拉里·芬克Larry Fink | Fin | 20 | 86 | 82 | 57 | 69 | 54 | · | |
| 内森·梅耶·罗斯柴尔德Nathan Mayer Rothschild | Fin | 18 | 95 | 92 | 50 | 69 | 69 | 90 | 90 |
| 乔治·皮博迪George Peabody | Fin | 18 | 82 | 84 | 71 | 67 | 66 | 85 | 90 |
| 卡尔·伊坎Carl Icahn | Fin | 20 | 85 | 55 | 48 | 66 | 57 | · | |
| 梅耶·阿姆谢尔·罗斯柴尔德Mayer Amschel Rothschild | Fin | 18 | 88 | 97 | 54 | 66 | 81 | 92 | 93 |
| 雷·达利欧Ray Dalio | Fin | 20 | 85 | 68 | 60 | 66 | 56 | · | |
| 史蒂夫·科恩Steve Cohen | Fin | 20 | 88 | 66 | 46 | 66 | 60 | · | |
| 科尼利厄斯·范德比尔特Cornelius Vanderbilt | Fin | 18 | 92 | 70 | 40 | 65 | 76 | 72 | 38 |
| J·P·摩根J. P. Morgan | Fin | 19 | 96 | 90 | 62 | 64 | 57 | 92 | 92 |
| 杰伊·古尔德Jay Gould | Fin | 19 | 95 | 55 | 22 | 63 | 74 | 38 | 30 |
| 米尔顿·弗里德曼Milton Friedman | Fin | 20 | 90 | 75 | 63 | 63 | 40 | 85 | 85 |
| 雅各布·富格尔Jacob Fugger | Fin | 15 | 94 | 80 | 45 | 62 | 57 | 82 | 55 |
| 赫蒂·格林Hetty Green | Fin | 19 | 88 | 30 | 37 | 59 | 57 | 60 | 35 |
| 马库斯·高德曼Marcus Goldman | Fin | 19 | 80 | 85 | 54 | 59 | 63 | 88 | 90 |
| 比尔·阿克曼Bill Ackman | Fin | 20 | 82 | 62 | 50 | 57 | 64 | · | |
| 孙正义Masayoshi Son | Fin | 20 | 82 | 60 | 53 | 56 | 64 | · | |
| 苏世民Stephen Schwarzman | Fin | 20 | 84 | 75 | 47 | 55 | 53 | · | |
| 丹尼尔·德鲁Daniel Drew | Fin | 18 | 78 | 25 | 23 | 45 | 68 | 20 | 15 |
| 杰西·利弗莫尔Jesse Livermore | Fin | 19 | 90 | 10 | 25 | 41 | 79 | 15 | 18 |
| 杰伊·库克Jay Cooke | Fin | 19 | 84 | 60 | 54 | 38 | 69 | 55 | 40 |
| 安德鲁·梅隆Andrew Mellon | Fin | 19 | 90 | 85 | 54 | 36 | 53 | 80 | 82 |
| 尼古拉斯·比德尔Nicholas Biddle | Fin | 18 | 85 | 45 | 55 | 35 | 60 | 30 | 22 |
| 欧文·费雪Irving Fisher | Fin | 19 | 88 | 45 | 55 | 30 | 38 | 30 | 70 |
| 伯纳德·麦道夫Bernie Madoff | Fin | 20 | 55 | 8 | 7 | 21 | 37 | 6 | 6 |
| 约翰·劳John Law | Fin | 17 | 80 | 45 | 36 | 17 | 58 | 12 | 15 |
| 查尔斯·庞兹Charles Ponzi | Fin | 19 | 45 | 10 | 12 | 16 | 43 | 8 | 8 |
| 伊瓦尔·克罗伊格Ivar Kreuger | Fin | 19 | 82 | 30 | 32 | 16 | 60 | 10 | 12 |
| 外交家 · n=9 · 明 62 · 终 65Diplomats · n=9 · Luc 62 · End 65 | |||||||||
| 夏尔-莫里斯·德·塔列朗Charles Maurice de Talleyrand | Dipl | 18 | 95 | 55 | 45 | 85 | 86 | 65 | 52 |
| 乔治·马歇尔George C. Marshall | Dipl | 19 | 85 | 88 | 84 | 83 | 87 | 88 | 90 |
| 詹姆斯·贝克James A. Baker III | Dipl | 20 | 85 | 72 | 68 | 77 | 64 | · | |
| 达格·哈马舍尔德Dag Hammarskjöld | Dipl | 20 | 82 | 80 | 83 | 70 | 78 | 78 | 85 |
| 康多莉扎·赖斯Condoleezza Rice | Dipl | 20 | 78 | 62 | 62 | 61 | 83 | · | |
| 亨利·基辛格Henry Kissinger | Dipl | 20 | 90 | 65 | 48 | 58 | 81 | 60 | 80 |
| 科菲·安南Kofi Annan | Dipl | 20 | 80 | 78 | 79 | 50 | 73 | 75 | 72 |
| 克莱门斯·冯·梅特涅Klemens von Metternich | Dipl | 18 | 90 | 82 | 51 | 48 | 90 | 68 | 80 |
| 内维尔·张伯伦Neville Chamberlain | Dipl | 19 | 55 | 40 | 63 | 26 | 80 | 20 | 12 |
| 政治家 · n=16 · 明 61 · 终 77Statesmen · n=16 · Luc 61 · End 77 | |||||||||
| 让·莫内Jean Monnet | Stat | 19 | 72 | 92 | 87 | 83 | 62 | 88 | 90 |
| 安格拉·默克尔Angela Merkel | Stat | 20 | 84 | 72 | 74 | 79 | 60 | · | |
| 罗伯特·皮尔Robert Peel | Stat | 18 | 85 | 72 | 84 | 76 | 62 | 74 | 78 |
| 克莱门特·艾德礼Clement Attlee | Stat | 19 | 78 | 88 | 84 | 72 | 73 | 88 | 90 |
| 加富尔Camillo Cavour | Stat | 19 | 90 | 78 | 76 | 70 | 75 | 82 | 82 |
| 威廉·格莱斯顿William Gladstone | Stat | 19 | 90 | 78 | 84 | 68 | 56 | 78 | 80 |
| 大卫·本-古里安David Ben-Gurion | Stat | 19 | 85 | 85 | 69 | 65 | 81 | 82 | 82 |
| 本杰明·迪斯雷利Benjamin Disraeli | Stat | 19 | 88 | 80 | 57 | 62 | 53 | 76 | 78 |
| 周恩来Zhou Enlai | Stat | 19 | 88 | 72 | 61 | 61 | 85 | 72 | 72 |
| 贝尼托·胡亚雷斯Benito Juárez | Stat | 19 | 80 | 72 | 76 | 60 | 80 | 76 | 74 |
| 夏尔·戴高乐Charles de Gaulle | Stat | 19 | 88 | 90 | 80 | 60 | 84 | 88 | 90 |
| 乔治·克列孟梭Georges Clemenceau | Stat | 19 | 86 | 62 | 63 | 57 | 79 | 60 | 55 |
| 莫罕达斯·甘地Mohandas Gandhi | Stat | 19 | 85 | 72 | 88 | 50 | 82 | 82 | 82 |
| 朱利叶斯·尼雷尔Julius Nyerere | Stat | 20 | 72 | 60 | 82 | 47 | 71 | 55 | 52 |
| 贾瓦哈拉尔·尼赫鲁Jawaharlal Nehru | Stat | 19 | 82 | 85 | 80 | 34 | 83 | 84 | 85 |
| 玛格丽特·撒切尔Margaret Thatcher | Stat | 20 | 88 | 75 | 58 | 29 | 72 | 72 | 75 |
| 科学家 · n=14 · 明 60 · 终 71Scientists · n=14 · Luc 60 · End 71 | |||||||||
| 查尔斯·达尔文Charles Darwin | Sci | 19 | 95 | 72 | 80 | 84 | 51 | 95 | 96 |
| 杰弗里·辛顿Geoffrey Hinton | Sci | 20 | 90 | 70 | 75 | 83 | 50 | · | |
| 卡塔琳·卡里科Katalin Karikó | Sci | 20 | 88 | 60 | 80 | 83 | 61 | · | |
| 詹妮弗·杜德纳Jennifer Doudna | Sci | 20 | 90 | 75 | 76 | 81 | 48 | · | |
| 文基·拉马克里希南Venki Ramakrishnan | Sci | 20 | 88 | 74 | 75 | 81 | 46 | · | |
| 艾伦·图灵Alan Turing | Sci | 20 | 96 | 55 | 78 | 75 | 81 | 88 | 95 |
| 阿尔伯特·爱因斯坦Albert Einstein | Sci | 19 | 98 | 65 | 80 | 68 | 83 | 92 | 95 |
| J·罗伯特·奥本海默J. Robert Oppenheimer | Sci | 20 | 92 | 78 | 60 | 63 | 69 | 62 | 70 |
| 玛丽·居里Marie Curie | Sci | 19 | 92 | 75 | 81 | 63 | 72 | 92 | 90 |
| 路易·巴斯德Louis Pasteur | Sci | 19 | 92 | 82 | 71 | 53 | 58 | 90 | 92 |
| 艾萨克·牛顿Isaac Newton | Sci | 17 | 99 | 80 | 48 | 43 | 38 | 95 | 97 |
| 尼古拉·特斯拉Nikola Tesla | Sci | 19 | 90 | 35 | 56 | 33 | 69 | 55 | 82 |
| 弗里茨·哈伯Fritz Haber | Sci | 19 | 90 | 65 | 38 | 25 | 76 | 40 | 88 |
| 特罗菲姆·李森科Trofim Lysenko | Sci | 19 | 30 | 40 | 15 | 10 | 31 | 5 | 5 |
| 企业家 · n=32 · 明 60 · 终 67CEOs · n=32 · Luc 60 · End 67 | |||||||||
| 安迪·格鲁夫Andrew Grove | CEO | 20 | 90 | 82 | 62 | 87 | 69 | 72 | 78 |
| 苏姿丰Lisa Su | CEO | 20 | 88 | 76 | 65 | 82 | 52 | · | |
| 山姆·沃尔顿Sam Walton | CEO | 20 | 92 | 88 | 57 | 82 | 57 | 90 | 95 |
| 阿尔弗雷德·斯隆Alfred P. Sloan | CEO | 19 | 88 | 95 | 56 | 79 | 58 | 74 | 72 |
| 里德·哈斯廷斯Reed Hastings | CEO | 20 | 86 | 80 | 61 | 79 | 55 | · | |
| 桑达尔·皮查伊Sundar Pichai | CEO | 20 | 82 | 78 | 65 | 77 | 63 | · | |
| 戴密斯·哈萨比斯Demis Hassabis | CEO | 20 | 90 | 74 | 66 | 75 | 53 | · | |
| 蒂姆·库克Tim Cook | CEO | 20 | 82 | 80 | 65 | 75 | 61 | · | |
| 安迪·贾西Andy Jassy | CEO | 20 | 80 | 72 | 63 | 74 | 51 | · | |
| 杰夫·贝索斯Jeff Bezos | CEO | 20 | 90 | 82 | 54 | 74 | 64 | · | |
| 黄仁勋Jensen Huang | CEO | 20 | 92 | 78 | 61 | 74 | 77 | · | |
| 松下幸之助Konosuke Matsushita | CEO | 19 | 88 | 90 | 78 | 74 | 74 | 85 | 82 |
| 萨提亚·纳德拉Satya Nadella | CEO | 20 | 84 | 80 | 65 | 74 | 60 | · | |
| 比尔·盖茨Bill Gates | CEO | 20 | 92 | 85 | 64 | 73 | 53 | · | |
| 马克·贝尼奥夫Marc Benioff | CEO | 20 | 82 | 76 | 61 | 70 | 51 | · | |
| 贝尔纳·阿尔诺Bernard Arnault | CEO | 20 | 90 | 84 | 50 | 68 | 50 | · | |
| 鲍勃·艾格Bob Iger | CEO | 20 | 84 | 78 | 58 | 68 | 48 | · | |
| 约翰·D·洛克菲勒John D. Rockefeller | CEO | 19 | 97 | 85 | 52 | 66 | 67 | 85 | 88 |
| 山姆·奥特曼Sam Altman | CEO | 20 | 82 | 55 | 51 | 60 | 69 | · | |
| 盛田昭夫Akio Morita | CEO | 20 | 90 | 72 | 62 | 55 | 69 | 72 | 74 |
| 王安An Wang | CEO | 20 | 85 | 35 | 57 | 54 | 63 | 15 | 12 |
| 马克·扎克伯格Mark Zuckerberg | CEO | 20 | 84 | 70 | 44 | 52 | 73 | · | |
| 雷·克罗克Ray Kroc | CEO | 20 | 88 | 85 | 43 | 51 | 55 | 90 | 92 |
| 埃隆·马斯克Elon Musk | CEO | 20 | 88 | 55 | 46 | 50 | 78 | · | |
| 史蒂夫·乔布斯Steve Jobs | CEO | 20 | 96 | 80 | 58 | 49 | 76 | 90 | 92 |
| 安德鲁·卡内基Andrew Carnegie | CEO | 19 | 90 | 70 | 53 | 45 | 63 | 78 | 80 |
| 沃尔特·迪士尼Walt Disney | CEO | 20 | 95 | 78 | 64 | 38 | 75 | 88 | 88 |
| 埃德温·兰德Edwin Land | CEO | 20 | 95 | 45 | 73 | 33 | 57 | 25 | 22 |
| 老托马斯·沃森Thomas J. Watson Sr. | CEO | 19 | 85 | 92 | 49 | 33 | 65 | 85 | 85 |
| 霍华德·休斯Howard Hughes | CEO | 20 | 80 | 40 | 34 | 19 | 52 | 45 | 55 |
| 肯尼斯·莱Kenneth Lay | CEO | 20 | 55 | 30 | 29 | 18 | 50 | 5 | 5 |
| 亨利·福特Henry Ford | CEO | 19 | 90 | 50 | 34 | 17 | 60 | 68 | 82 |
| 经济学家 · n=15 · 明 60 · 终 78Economists · n=15 · Luc 60 · End 78 | |||||||||
| 约翰·斯图尔特·穆勒John Stuart Mill | Econ | 19 | 85 | 65 | 85 | 82 | 48 | 80 | 78 |
| 阿马蒂亚·森Amartya Sen | Econ | 20 | 90 | 75 | 88 | 79 | 42 | · | |
| 达龙·阿西莫格鲁Daron Acemoglu | Econ | 20 | 90 | 72 | 83 | 78 | 49 | · | |
| 弗里德里希·哈耶克Friedrich Hayek | Econ | 19 | 88 | 80 | 72 | 69 | 60 | 85 | 82 |
| 约瑟夫·熊彼特Joseph Schumpeter | Econ | 19 | 90 | 70 | 77 | 65 | 59 | 85 | 82 |
| 托尔斯坦·凡勃伦Thorstein Veblen | Econ | 19 | 80 | 55 | 80 | 65 | 65 | 65 | 62 |
| 阿尔弗雷德·马歇尔Alfred Marshall | Econ | 19 | 88 | 85 | 85 | 64 | 44 | 90 | 90 |
| 保罗·萨缪尔森Paul Samuelson | Econ | 20 | 95 | 88 | 85 | 59 | 43 | 92 | 92 |
| 卡尔·门格尔Carl Menger | Econ | 19 | 85 | 82 | 82 | 58 | 52 | 85 | 85 |
| 里昂·瓦尔拉斯Léon Walras | Econ | 19 | 90 | 65 | 77 | 57 | 55 | 88 | 85 |
| 弗里德里希·李斯特Friedrich List | Econ | 18 | 75 | 62 | 55 | 54 | 77 | 68 | 70 |
| 托马斯·马尔萨斯Thomas Malthus | Econ | 18 | 78 | 60 | 73 | 51 | 45 | 72 | 65 |
| 约翰·肯尼思·加尔布雷思John Kenneth Galbraith | Econ | 20 | 78 | 55 | 75 | 48 | 44 | 50 | 52 |
| 琼·罗宾逊Joan Robinson | Econ | 20 | 88 | 65 | 61 | 39 | 53 | 68 | 65 |
| 卡尔·马克思Karl Marx | Econ | 19 | 90 | 80 | 68 | 29 | 80 | 92 | 90 |
| 君主 · n=59 · 明 59 · 终 63Sovereigns · n=59 · Luc 59 · End 63 | |||||||||
| 林肯Abraham Lincoln | Sov | 19 | 85 | 85 | 41 | 86 | 82 | 82 | 90 |
| 曼德拉Nelson Mandela | Sov | 20 | 78 | 82 | 49 | 86 | 85 | 92 | 78 |
| 华盛顿George Washington | Sov | 18 | 58 | 90 | 43 | 84 | 82 | 96 | 96 |
| 德川家康Tokugawa Ieyasu | Sov | 16 | 88 | 95 | 44 | 84 | 77 | 90 | 92 |
| 赵匡胤Zhao Kuangyin | Sov | 10 | 80 | 78 | 33 | 84 | 70 | 68 | 85 |
| 世宗大王Sejong the Great | Sov | 14 | 70 | 85 | 53 | 83 | 48 | 82 | 90 |
| 欧麦尔Umar ibn al-Khattab | Sov | 6 | 85 | 85 | 73 | 82 | 74 | 72 | 82 |
| 屋大维Augustus | Sov | −1 | 93 | 98 | 68 | 81 | 77 | 92 | 95 |
| 刘邦Liu Bang | Sov | −3 | 88 | 85 | 54 | 81 | 83 | 85 | 92 |
| 雍正Yongzheng | Sov | 17 | 88 | 80 | 23 | 80 | 75 | 68 | 82 |
| 邓小平Deng Xiaoping | Sov | 20 | 88 | 82 | 59 | 78 | 75 | 78 | 88 |
| 彼得大帝Peter the Great | Sov | 17 | 68 | 84 | 78 | 77 | 79 | 70 | 85 |
| 伊丽莎白一世Elizabeth I | Sov | 16 | 85 | 70 | 55 | 76 | 77 | 75 | 68 |
| 李世民Li Shimin | Sov | 6 | 87 | 82 | 69 | 76 | 75 | 78 | 88 |
| 成吉思汗Genghis Khan | Sov | 12 | 96 | 72 | 87 | 73 | 91 | 68 | 78 |
| 阿克巴Akbar | Sov | 16 | 84 | 88 | 68 | 72 | 72 | 80 | 78 |
| 马可·奥勒留Marcus Aurelius | Sov | 2 | 72 | 70 | 58 | 72 | 63 | 56 | 55 |
| 俾斯麦Otto von Bismarck | Sov | 19 | 92 | 75 | 65 | 72 | 66 | 52 | 72 |
| 叶卡捷琳娜Catherine the Great | Sov | 18 | 85 | 72 | 78 | 70 | 70 | 75 | 72 |
| 李光耀Lee Kuan Yew | Sov | 20 | 85 | 90 | 56 | 70 | 59 | 85 | 90 |
| 康熙Kangxi | Sov | 17 | 72 | 75 | 64 | 69 | 73 | 60 | 82 |
| 阿登纳Konrad Adenauer | Sov | 19 | 78 | 88 | 56 | 68 | 78 | 88 | 90 |
| 戴克里先Diocletian | Sov | 3 | 80 | 78 | 40 | 67 | 84 | 70 | 55 |
| 拿破仑Napoleon | Sov | 18 | 90 | 72 | 91 | 64 | 79 | 28 | 70 |
| 居鲁士大帝Cyrus the Great | Sov | −6 | 88 | 85 | 78 | 62 | 81 | 80 | 85 |
| 武则天Wu Zetian | Sov | 7 | 92 | 70 | 39 | 62 | 72 | 68 | 50 |
| 凯末尔Atatürk | Sov | 19 | 86 | 88 | 54 | 61 | 83 | 85 | 85 |
| 查理五世Charles V | Sov | 15 | 72 | 72 | 70 | 61 | 77 | 68 | 78 |
| 大流士一世Darius I | Sov | −6 | 82 | 88 | 72 | 59 | 72 | 76 | 85 |
| 腓特烈大帝Frederick the Great | Sov | 18 | 82 | 80 | 75 | 59 | 74 | 72 | 82 |
| 查理曼Charlemagne | Sov | 8 | 85 | 78 | 84 | 57 | 78 | 68 | 60 |
| 穆罕默德二世Mehmed II | Sov | 15 | 88 | 82 | 85 | 56 | 73 | 76 | 85 |
| 阿育王Ashoka | Sov | −4 | 78 | 72 | 49 | 55 | 65 | 66 | 50 |
| 伯里克利Pericles | Sov | −5 | 80 | 70 | 65 | 55 | 66 | 55 | 50 |
| 富兰克林·罗斯福Franklin D. Roosevelt | Sov | 19 | 86 | 90 | 61 | 54 | 87 | 82 | 88 |
| 维多利亚女王Queen Victoria | Sov | 19 | 60 | 82 | 68 | 54 | 40 | 85 | 85 |
| 丘吉尔Winston Churchill | Sov | 19 | 88 | 75 | 66 | 54 | 62 | 80 | 70 |
| 永乐帝Yongle Emperor | Sov | 14 | 85 | 80 | 71 | 54 | 73 | 72 | 78 |
| 毛泽东Mao Zedong | Sov | 19 | 97 | 64 | 46 | 53 | 73 | 42 | 75 |
| 萨拉丁Saladin | Sov | 12 | 84 | 60 | 73 | 53 | 77 | 55 | 40 |
| 杰斐逊Thomas Jefferson | Sov | 18 | 75 | 85 | 59 | 51 | 56 | 82 | 88 |
| 凯撒Julius Caesar | Sov | −1 | 90 | 40 | 75 | 49 | 78 | 25 | 55 |
| 丰臣秀吉Toyotomi Hideyoshi | Sov | 16 | 90 | 55 | 73 | 49 | 84 | 32 | 20 |
| 忽必烈Kublai Khan | Sov | 13 | 82 | 70 | 77 | 46 | 76 | 60 | 45 |
| 西奥多·罗斯福Theodore Roosevelt | Sov | 19 | 80 | 80 | 70 | 46 | 51 | 78 | 80 |
| 腓特烈·巴巴罗萨Frederick Barbarossa | Sov | 12 | 78 | 60 | 81 | 44 | 74 | 50 | 40 |
| 汉武帝Emperor Wu of Han | Sov | −2 | 80 | 72 | 85 | 43 | 63 | 55 | 80 |
| 斯大林Joseph Stalin | Sov | 19 | 95 | 62 | 54 | 43 | 65 | 30 | 55 |
| 苏莱曼大帝Suleiman the Magnificent | Sov | 15 | 85 | 85 | 77 | 41 | 68 | 72 | 85 |
| 朱元璋Zhu Yuanzhang | Sov | 14 | 90 | 68 | 35 | 38 | 75 | 38 | 78 |
| 玻利瓦尔Simón Bolívar | Sov | 18 | 85 | 40 | 87 | 36 | 86 | 30 | 40 |
| 秦始皇Qin Shi Huang | Sov | −3 | 90 | 88 | 69 | 33 | 78 | 40 | 80 |
| 帖木儿Timur | Sov | 14 | 90 | 40 | 85 | 33 | 82 | 32 | 38 |
| 路易十四Louis XIV | Sov | 17 | 80 | 78 | 58 | 30 | 61 | 55 | 72 |
| 慈禧Empress Dowager Cixi | Sov | 19 | 55 | 30 | 24 | 29 | 71 | 22 | 15 |
| 亚历山大大帝Alexander the Great | Sov | −4 | 92 | 35 | 95 | 28 | 77 | 26 | 55 |
| 查士丁尼一世Justinian I | Sov | 5 | 78 | 85 | 76 | 27 | 78 | 60 | 72 |
| 奥朗则布Aurangzeb | Sov | 17 | 82 | 55 | 79 | 24 | 76 | 30 | 25 |
| 希特勒Adolf Hitler | Sov | 19 | 92 | 30 | 91 | 20 | 83 | 2 | 3 |
| 教育家 · n=9 · 明 58 · 终 76Educators · n=9 · Luc 58 · End 76 | |||||||||
| 吉米·威尔士Jimmy Wales | Educ | 20 | 72 | 80 | 82 | 75 | 60 | · | |
| 亚伯拉罕·弗莱克斯纳Abraham Flexner | Educ | 19 | 82 | 85 | 86 | 74 | 42 | 85 | 88 |
| 萨尔曼·可汗Salman Khan | Educ | 20 | 75 | 72 | 83 | 73 | 56 | · | |
| 威廉·冯·洪堡Wilhelm von Humboldt | Educ | 18 | 85 | 92 | 82 | 70 | 70 | 90 | 93 |
| 埃兹拉·康奈尔Ezra Cornell | Educ | 19 | 70 | 80 | 75 | 68 | 52 | 82 | 88 |
| 布克·T·华盛顿Booker T. Washington | Educ | 19 | 82 | 82 | 79 | 55 | 90 | 78 | 82 |
| 玛丽亚·蒙台梭利Maria Montessori | Educ | 19 | 85 | 85 | 78 | 38 | 82 | 88 | 88 |
| 利兰·斯坦福Leland Stanford | Educ | 19 | 72 | 78 | 50 | 36 | 31 | 85 | 92 |
| 阿莫斯·布朗森·奥尔科特Amos Bronson Alcott | Educ | 18 | 55 | 30 | 72 | 35 | 49 | 25 | 15 |
| 罗马 · n=19 · 明 58 · 终 41Rome · n=19 · Luc 58 · End 41 | |||||||||
| 维斯帕先Vespasian | Rome | 1 | 88 | 78 | 71 | 78 | 64 | 90 | 60 |
| 费边Fabius Maximus | Rome | −3 | 90 | 55 | 79 | 75 | 63 | 85 | 86 |
| 哈德良Hadrian | Rome | 1 | 92 | 85 | 70 | 75 | 58 | 65 | 82 |
| 辛辛纳图斯Cincinnatus | Rome | −6 | 80 | 25 | 85 | 74 | 77 | 86 | 72 |
| 君士坦丁大帝Constantine the Great | Rome | 3 | 92 | 93 | 66 | 74 | 73 | 90 | 95 |
| 图拉真Trajan | Rome | 1 | 95 | 82 | 74 | 71 | 62 | 82 | 85 |
| 阿格里帕Marcus Vipsanius Agrippa | Rome | −1 | 90 | 78 | 80 | 70 | 76 | 88 | 85 |
| 苏拉Sulla | Rome | −2 | 95 | 50 | 59 | 70 | 69 | 88 | 42 |
| 盖乌斯·马略Gaius Marius | Rome | −2 | 92 | 88 | 75 | 61 | 69 | 25 | 80 |
| 小加图Cato the Younger | Rome | −1 | 70 | 32 | 81 | 58 | 75 | 16 | 60 |
| 提比略·格拉古Tiberius Gracchus | Rome | −2 | 70 | 35 | 73 | 57 | 66 | 5 | 55 |
| 西塞罗Cicero | Rome | −2 | 88 | 38 | 83 | 55 | 77 | 4 | 92 |
| 庞培Pompey the Great | Rome | −2 | 92 | 45 | 62 | 55 | 70 | 3 | 30 |
| 马克·安东尼Mark Antony | Rome | −1 | 85 | 28 | 44 | 50 | 78 | 15 | 25 |
| 克拉苏Crassus | Rome | −2 | 70 | 30 | 45 | 49 | 63 | 5 | 15 |
| 布鲁图斯Marcus Junius Brutus | Rome | −1 | 60 | 12 | 63 | 44 | 63 | 15 | 18 |
| 尼禄Nero | Rome | 1 | 55 | 15 | 26 | 34 | 60 | 8 | 10 |
| 康茂德Commodus | Rome | 2 | 42 | 8 | 15 | 24 | 64 | 10 | 6 |
| 卡利古拉Caligula | Rome | 1 | 45 | 18 | 22 | 19 | 66 | 7 | 10 |
| 央行行长 · n=9 · 明 57 · 终 56Central bankers · n=9 · Luc 57 · End 56 | |||||||||
| 保罗·沃尔克Paul Volcker | CBnk | 20 | 88 | 85 | 88 | 81 | 86 | 90 | 90 |
| 马里纳·埃克尔斯Marriner Eccles | CBnk | 19 | 78 | 85 | 79 | 79 | 85 | 78 | 88 |
| 本·伯南克Ben Bernanke | CBnk | 20 | 84 | 78 | 72 | 78 | 49 | · | |
| 威廉·麦克切斯尼·马丁William McChesney Martin | CBnk | 20 | 82 | 90 | 83 | 72 | 58 | 85 | 85 |
| 克里斯蒂娜·拉加德Christine Lagarde | CBnk | 20 | 76 | 74 | 68 | 68 | 70 | · | |
| 杰罗姆·鲍威尔Jerome Powell | CBnk | 20 | 78 | 76 | 70 | 68 | 61 | · | |
| 阿瑟·伯恩斯Arthur Burns | CBnk | 20 | 70 | 58 | 39 | 31 | 71 | 32 | 28 |
| 蒙塔古·诺曼Montagu Norman | CBnk | 19 | 72 | 62 | 57 | 24 | 86 | 40 | 42 |
| 鲁道夫·冯·哈文斯坦Rudolf von Havenstein | CBnk | 19 | 40 | 35 | 48 | 15 | 87 | 10 | 12 |
| 总统 · n=40 · 明 52 · 终 51Presidents · n=40 · Luc 52 · End 51 | |||||||||
| 德怀特·艾森豪威尔Dwight D. Eisenhower | Pres | 19 | 80 | 78 | 82 | 85 | 64 | 82 | 80 |
| 乔治·H·W·布什George H. W. Bush | Pres | 20 | 76 | 72 | 74 | 82 | 66 | 70 | 74 |
| 切斯特·A·阿瑟Chester A. Arthur | Pres | 19 | 58 | 62 | 61 | 74 | 55 | 55 | 78 |
| 詹姆斯·麦迪逊James Madison | Pres | 18 | 72 | 88 | 81 | 69 | 75 | 62 | 88 |
| 威廉·麦金莱William McKinley | Pres | 19 | 78 | 70 | 64 | 69 | 62 | 66 | 74 |
| 巴拉克·奥巴马Barack Obama | Pres | 20 | 85 | 66 | 63 | 68 | 79 | · | |
| 拉瑟福德·B·海斯Rutherford B. Hayes | Pres | 19 | 62 | 58 | 64 | 67 | 65 | 50 | 50 |
| 约翰·昆西·亚当斯John Quincy Adams | Pres | 18 | 60 | 50 | 86 | 66 | 67 | 58 | 40 |
| 哈里·杜鲁门Harry S. Truman | Pres | 19 | 72 | 78 | 79 | 65 | 74 | 80 | 88 |
| 比尔·克林顿Bill Clinton | Pres | 20 | 90 | 60 | 56 | 64 | 50 | · | |
| 杰拉尔德·福特Gerald Ford | Pres | 20 | 58 | 52 | 71 | 63 | 68 | 55 | 50 |
| 詹姆斯·A·加菲尔德James A. Garfield | Pres | 19 | 68 | 38 | 65 | 63 | 62 | 48 | 42 |
| 约翰·肯尼迪John F. Kennedy | Pres | 20 | 82 | 60 | 70 | 63 | 69 | 62 | 55 |
| 马丁·范布伦Martin Van Buren | Pres | 18 | 85 | 76 | 48 | 63 | 71 | 42 | 62 |
| 詹姆斯·门罗James Monroe | Pres | 18 | 68 | 78 | 77 | 62 | 58 | 74 | 78 |
| 威廉·霍华德·塔夫脱William Howard Taft | Pres | 19 | 50 | 58 | 70 | 62 | 51 | 55 | 60 |
| 尤利西斯·格兰特Ulysses S. Grant | Pres | 19 | 80 | 62 | 69 | 61 | 65 | 60 | 52 |
| 约翰·亚当斯John Adams | Pres | 18 | 58 | 62 | 76 | 59 | 65 | 68 | 65 |
| 吉米·卡特Jimmy Carter | Pres | 20 | 55 | 62 | 78 | 55 | 80 | 58 | 68 |
| 乔·拜登Joe Biden | Pres | 20 | 62 | 60 | 60 | 55 | 74 | · | |
| 卡尔文·柯立芝Calvin Coolidge | Pres | 19 | 62 | 48 | 61 | 52 | 41 | 55 | 40 |
| 乔治·W·布什George W. Bush | Pres | 20 | 72 | 60 | 61 | 52 | 88 | · | |
| 沃伦·哈定Warren G. Harding | Pres | 19 | 55 | 40 | 34 | 52 | 37 | 32 | 25 |
| 伍德罗·威尔逊Woodrow Wilson | Pres | 19 | 80 | 72 | 68 | 52 | 50 | 55 | 68 |
| 约翰·泰勒John Tyler | Pres | 18 | 50 | 48 | 44 | 43 | 66 | 26 | 55 |
| 理查德·尼克松Richard Nixon | Pres | 20 | 85 | 55 | 31 | 43 | 71 | 12 | 58 |
| 罗纳德·里根Ronald Reagan | Pres | 20 | 88 | 72 | 59 | 43 | 59 | 72 | 78 |
| 扎卡里·泰勒Zachary Taylor | Pres | 18 | 45 | 30 | 58 | 43 | 60 | 45 | 30 |
| 格罗弗·克利夫兰Grover Cleveland | Pres | 19 | 72 | 62 | 68 | 41 | 72 | 62 | 60 |
| 威廉·亨利·哈里森William Henry Harrison | Pres | 18 | 55 | 40 | 56 | 40 | 49 | 35 | 30 |
| 唐纳德·特朗普Donald Trump | Pres | 20 | 86 | 28 | 24 | 39 | 76 | · | |
| 本杰明·哈里森Benjamin Harrison | Pres | 19 | 52 | 55 | 58 | 37 | 54 | 45 | 62 |
| 米勒德·菲尔莫尔Millard Fillmore | Pres | 18 | 52 | 40 | 35 | 35 | 62 | 30 | 25 |
| 林登·约翰逊Lyndon B. Johnson | Pres | 20 | 95 | 85 | 60 | 33 | 71 | 60 | 88 |
| 赫伯特·胡佛Herbert Hoover | Pres | 19 | 68 | 55 | 71 | 30 | 87 | 30 | 22 |
| 詹姆斯·波尔克James K. Polk | Pres | 18 | 88 | 74 | 59 | 29 | 71 | 76 | 82 |
| 詹姆斯·布坎南James Buchanan | Pres | 18 | 40 | 30 | 48 | 25 | 86 | 10 | 8 |
| 安德鲁·杰克逊Andrew Jackson | Pres | 18 | 88 | 60 | 48 | 23 | 54 | 58 | 70 |
| 富兰克林·皮尔斯Franklin Pierce | Pres | 19 | 42 | 28 | 32 | 20 | 75 | 18 | 15 |
| 安德鲁·约翰逊Andrew Johnson | Pres | 19 | 45 | 30 | 48 | 17 | 77 | 28 | 25 |
| 革命者 · n=16 · 明 48 · 终 40Revolutionaries · n=16 · Luc 48 · End 40 | |||||||||
| 圣马丁José de San Martín | Rev | 18 | 85 | 62 | 87 | 86 | 79 | 72 | 80 |
| 马萨里克Tomáš Garrigue Masaryk | Rev | 19 | 72 | 85 | 88 | 86 | 52 | 82 | 68 |
| 迈克尔·柯林斯Michael Collins | Rev | 19 | 80 | 58 | 58 | 80 | 83 | 35 | 78 |
| 胡志明Ho Chi Minh | Rev | 19 | 85 | 75 | 60 | 63 | 83 | 66 | 82 |
| 列宁Vladimir Lenin | Rev | 19 | 92 | 80 | 49 | 56 | 88 | 52 | 85 |
| 图森·卢维杜尔Toussaint Louverture | Rev | 18 | 80 | 60 | 68 | 51 | 92 | 25 | 58 |
| 加里波第Giuseppe Garibaldi | Rev | 19 | 88 | 55 | 78 | 48 | 75 | 78 | 85 |
| 埃米利亚诺·萨帕塔Emiliano Zapata | Rev | 19 | 70 | 45 | 72 | 47 | 88 | 22 | 62 |
| 托洛茨基Leon Trotsky | Rev | 19 | 88 | 62 | 51 | 43 | 87 | 15 | 45 |
| 丹东Georges Danton | Rev | 18 | 72 | 38 | 56 | 41 | 89 | 10 | 15 |
| 克伦威尔Oliver Cromwell | Rev | 16 | 82 | 55 | 41 | 40 | 82 | 32 | 18 |
| 孙中山Sun Yat-sen | Rev | 19 | 72 | 50 | 67 | 39 | 78 | 50 | 50 |
| 切·格瓦拉Che Guevara | Rev | 20 | 70 | 35 | 71 | 27 | 76 | 10 | 35 |
| 卡斯特罗Fidel Castro | Rev | 20 | 90 | 78 | 41 | 25 | 72 | 58 | 82 |
| 罗伯斯庇尔Maximilien Robespierre | Rev | 18 | 78 | 40 | 39 | 18 | 90 | 5 | 15 |
| 恩克鲁玛Kwame Nkrumah | Rev | 20 | 78 | 55 | 45 | 17 | 54 | 28 | 40 |
Table 8表 8 · 图谱索引(figures.csv,n=459)。除世纪(负号为公元前)外,各分皆 0–100。明与终按清醒与善终色阶着色。由 tools/gen_appendix.py 直接从开放数据集生成。The Atlas Index (figures.csv, n=459). All scores 0–100 except century (negative = BCE). Luc and End shaded on the lucidity and ending scales. Generated directly from the open dataset by tools/gen_appendix.py.
附录 DAppendix D
变量、编码与回归细节(含 R1/R5 完整结果)Variables, Coding, and Regression Details (with full R1/R5 results)
- 样本流(各分析 n 为何不同)。 459 人带明 → 404 人带两个手工结局、入主回归(55 人缺一结局;两个虚构群体排除)→ 404 人中 400 人有可红化传记、397 人回收得有效盲明(R2)→ 客观死法编码 449 人,客观制度存续年数编码 136 位建制者(R3a)→ 317 人带完整六轴剖面 → 深度效度测验(§4)为 20 人 × 3 评审,另加 12 篇合成传记。每项分析各自标明其 n;差异源于上述纳入规则,而非个案挑选。 Sample flow (why the n changes across analyses). 459 figures carry a lucidity score → 404 carry both hand-coded outcomes and enter the main regressions (55 lack one outcome; two fictional cohorts excluded) → of the 404, 400 have a redactable biography and 397 return a valid blind lucidity (R2) → objective manner-of-death is coded for 449, and objective institution-survival years for the 136 institution-builders (R3a) → 317 carry the full six-axis profile → the depth validation battery (§4) is 20 subjects × 3 raters plus 12 synthetic biographies. Each analysis names its own n; the differences are these inclusion rules, not case selection.
-
可复现性。 所有分数由 Claude 族(Anthropic)子代理产生,每道单评审;每一发布量均可由开放数据集与
tools/脚本重生。因分数依赖模型,未来模型重评预期会漂移——跨模型族复评(R4)同时兼作可复现性检验。 Reproducibility. All scores are produced by subagents of the Claude family (Anthropic), single-rater per pass, and every released quantity is regenerable from the open dataset andtools/scripts. Because the scores depend on the model, re-scoring under a future model is expected to drift — the cross-model-family re-run (R4) doubles as the reproducibility check. - 明派生:每人 2–3 有后果阶段,逐阶段 明=√(理·玄)·100,按代价加权;术取峰值。 Lucidity derivation: 2–3 consequential phases per subject, per-phase lucidity = √(Pattern×Mystery) rescaled to 0–100, cost-weighted; skill takes the peak.
- 模型拟合优度: 善终 R²=0.457(adjR² .450,rmse 20.7);存续 R²=0.719(adjR² .716,rmse 13.5)。明单变量 R²:善终 .247、存续 .387。 Model fit: personal survival R² = 0.457 (adj R² .450, rmse 20.7); organizational survival R² = 0.719 (adj R² .716, rmse 13.5). Lucidity univariate R²: personal .247, organizational .387.
- R1 差异检验(堆叠 808 行 = 404×2,标准化;主体聚类 SE): 术 Δ=+0.252(z=5.46, p<.001;群体聚类 z=3.37);建制力 Δ=+0.022(z=0.37);明 Δ=−0.065(z=−1.24, p=0.21);朝向 Δ=+0.114(z=2.31→聚类 1.64);难度 Δ=+0.053(z=1.37)。自助(B=2000)明之差 95% CI [−0.165, +0.034],P(偏命)=0.886。 R1 differential test (stacked 808 rows = 404 × 2, standardized; subject-clustered SE): skill Δ = +0.252 (z = 5.46, p < .001; cohort-clustered z = 3.37); institution-building Δ = +0.022 (z = 0.37); lucidity Δ = −0.065 (z = −1.24, p = 0.21); orientation Δ = +0.114 (z = 2.31 → clustered 1.64); difficulty Δ = +0.053 (z = 1.37). Bootstrap (B = 2000) lucidity difference 95% CI [−0.165, +0.034], P(fate-tilt) = 0.886.
- R5 优势分析(general dominance): 善终端:建制力 56.4% > 明 25.5% > 难度 7.1% > 术 5.5% ≈ 朝向 5.4%;存续端:建制力 48.0% > 明 20.1% ≈ 术 19.6% > 朝向 10.5% > 难度 1.8%。VIF: 术 1.47 / 建制力 1.42 / 朝向 1.40 / 明 1.71 / 难度 1.03。设定曲线(明偏命): 16 设定中 min −0.129 / max +0.071 / 中位 −0.004,仅 50% 为正,单变量 −0.125。 R5 dominance analysis (general dominance): personal: institution-building 56.4% > lucidity 25.5% > difficulty 7.1% > skill 5.5% ≈ orientation 5.4%; organizational: institution-building 48.0% > lucidity 20.1% ≈ skill 19.6% > orientation 10.5% > difficulty 1.8%. VIF: skill 1.47 / institution 1.42 / orientation 1.40 / lucidity 1.71 / difficulty 1.03. Specification curve (fate-tilt): across 16 specs min −0.129 / max +0.071 / median −0.004, only 50% positive, univariate −0.125.
- 两幅肖像数据(入池条目):拿破仑 术89/建制72/明64/善终28/存续70;华盛顿 术58/建制90/明84/善终96/存续96。 Two-portrait data (pooled entries): Napoleon skill 89 / institution 72 / lucidity 64 / personal 28 / organizational 70; Washington skill 58 / institution 90 / lucidity 84 / personal 96 / organizational 96.
附录 EAppendix E
R2 结局盲重评(全池):方法与结果R2 Outcome-Blind Rescore (full pool): Method and Results
方法。 对全池每位进入回归的人物,依次执行四步:(1)取其公开维基传记;(2)由一独立的脱敏代理删除姓名、别名与头衔(统一替换为"Subject X"),删除导语判词以及 Legacy、Reputation、Influence、Assessment 与流行文化各节,并剥离评价性形容词,同时保留一切行为事实;(3)由另一独立的盲评代理仅据脱敏文本、按六轴量表打分,既不知身份,也不见图谱分;(4)由同一引擎算出 明_blind。全池 400 人(404 回归样本中,4 人无可脱敏传记)重打,其中 397 人得到有效的 明_blind。相关局限见 §7.1:脱敏与评审均由 LLM 完成(同一模型族),系单评审,且盲化并不完美。
结果(标准化;n=397)。
Method. For every figure entering the regression, four steps are performed: (1) take the public Wikipedia biography; (2) an independent redactor agent deletes name, aliases, and titles (replaced uniformly by "Subject X"), the lead's summary judgements, and any Legacy, Reputation, Influence, Assessment, or pop-culture sections, and strips evaluative adjectives while preserving all conduct facts; (3) a separate independent blind-judge agent scores the six axes from the redacted text alone, knowing neither identity nor atlas score; (4) blind lucidity is computed by the same engine. All 400 pooled figures (of the 404 in the regression, four lacked a redactable biography) were re-scored, and 397 yielded a valid blind lucidity. The limitations (see §7, item 1) are that redaction and judging are both done by a model of the same family, single-rater, and imperfectly blinded.
Results (standardized; n = 397).
- 逐结局 OLS(盲):善终 明 β=+0.34(t8.3)、ΔR²=.089;存续 明 β=+0.08(t2.4)、ΔR²=.005。对比命名分(善终 .27;存续 .21):存续系数大半坍缩、善终系数增强。 Per-outcome OLS (blind): personal lucidity β = +0.34 (t 8.3), ΔR² = .089; organizational β = +0.08 (t 2.4), ΔR² = .005. Versus named (personal .27; organizational .21): the organizational coefficient mostly collapses while the personal one strengthens.
- 差异 Wald(明,存续−善终):Δ=−0.261;主体聚类 z=−4.66、群体聚类 z=−3.77(命名 −0.065,z=−1.24)。明偏命由不显著转为 p<.001。 Differential Wald (lucidity, org − personal): Δ = −0.261; subject z = −4.66, cohort z = −3.77 (named −0.065, z = −1.24). The fate-tilt goes from non-significant to p < .001.
- 术偏业(盲):Δ=+0.288,主体 z=5.99 / 群体 z=3.28,更强,方向不变。 Skill enterprise-tilt (blind): Δ = +0.288, subject z = 5.99 / cohort z = 3.28, stronger and in the same direction.
- 稳健性(逐一剔除任一群体,明偏命 主体聚类 z): 全程 −4.03(剔春秋)至 −5.04(剔数学家),无单一群体驱动。 Robustness (drop any single cohort; fate-tilt subject-clustered z): from −4.03 (drop spring-autumn) to −5.04 (drop mathematicians), so no single cohort drives it.
- 一致性:r(明_named, 明_blind)≈0.6,均值位移≈0,盲分并非整体平移,而是特定重排(遗产名人回落、被苛评者回升),符合"去掉光环"而非"加噪声"。 Consistency: r(named, blind) ≈ 0.6, mean shift ≈ 0, a specific re-ordering (revered figures fall, harshly-docked ones rise) that is the signature of halo-removal rather than noise.
附录 FAppendix F
R3a 客观结局代理稳健性(全池):方法与结果R3a Objective-Outcome-Proxy Robustness (full pool): Method and Results
目的。 本附录旨在从因变量端斩断共源:将两个手工结局替换为外部、可查证的记录事实,同时保持预测子的图谱原值不动,再重跑逐结局 OLS 与堆叠差异 Wald。这构成研究议程 R3 中"客观结局代理"的一半。
编码(盲于图谱预测分,459/459 由缓存维基抽取,逐条引证)。
Purpose. This appendix cuts common-source from the dependent-variable side: it replaces the two hand-scored outcomes with external, records-based facts, holds the predictors at their atlas values, and re-runs the analysis. It is the "objective outcome proxy" half of agenda R3.
Coding (blind to atlas predictor scores; 459/459 extracted from cached Wikipedia, quote-anchored).
- 个人善终 = 死法序数 0–4:0 被杀/处决/自尽/死于敌手 · 1 废黜且系囚/流放死于拘禁 · 2 失势/罢黜但死时自由 · 3 自然死、离权、体面 · 4 死于任上/巅峰、受尊崇。 Personal fate = manner-of-death ordinal 0–4: 0 executed/assassinated/killed/forced-suicide · 1 deposed & imprisoned/exiled-in-captivity · 2 fell-from-power/disgraced but died free · 3 natural death, out of power, in good standing · 4 died in power / at the height, honored.
- 事业存续 = log1p(身后制度延续年数),仅建制者;纯思想/艺术/科学/将才遗产记 N/A,借此从因变量端移除建制力↔存续同义反复。 Legacy survival = log1p(years the primary institution persisted after death), coded only for institution-builders; pure intellectual, artistic, scientific, or generalship legacies are N/A, which removes the institution-building-to-survival tautology from the DV side.
-
抽取:58 个模型批次 × 有界维基摘录,每人一条引证记录(402 维基源 / 24 混合 / 33 定论;392 高置信)。产物
data/lucido-study/r3a-objective/。 Extraction: 58 model batches over bounded wiki excerpts, one quote-anchored record per figure (402 wiki / 24 mixed / 33 established; 392 high-confidence). Artifacts:data/lucido-study/r3a-objective/.
结果(标准化 β;t)。
Results (standardized β; t).
- 个人善终(客观死法,n=449): 建制力 +0.42(t=8.47,ΔR².127) > 难度 −0.17 > 术 −0.10 > 明 +0.08(t=1.50,ns) > 朝向 −0.06。在世者剔除(n=404): 建制力 t=8.35 不变,明 t=0.99。 Personal fate (objective, n = 449): institution-building +0.42 (t = 8.47, ΔR² .127) > difficulty −0.17 > skill −0.10 > lucidity +0.08 (t = 1.50, ns) > orientation −0.06. Deceased-only (n = 404): institution-building t = 8.35 unchanged, lucidity t = 0.99.
- 事业存续(客观 log 存续年,建制者 n=136): 建制力 +0.36(t=3.72,ΔR².091) > 朝向 +0.15 > 明 −0.11(ns) > 术 +0.09。 Legacy survival (objective log years, builders n = 136): institution-building +0.36 (t = 3.72, ΔR² .091) > orientation +0.15 > lucidity −0.11 (ns) > skill +0.09.
- 堆叠差异 Wald(建制者配对 n=133): 明偏命之差 Δ=−0.22,主体聚类 z=−1.37,p=.17(仅方向,远弱于盲分 z=−3.8);术偏业之差 +0.11,z=0.96。 Stacked differential Wald (builders paired n = 133): fate-tilt Δ = −0.22, subject z = −1.37, p = .17 (directional, far weaker than blind's z = −3.8); skill-tilt +0.11, z = 0.96.
读法。 结果可从五个方面解读。第一,建制力主梁并非共源:在客观存续下建制力仍有 t = 3.7、在客观善终下有 t = 8.5,共源之忧就此解除。第二,明偏命不外推到客观死法:明对客观善终并不显著(t = 1.5,仅计已故者时 t = 1.0)。第三,两种成因并存,即去光环(命名分中遗产光环虚抬了明)与构念压窄(死法不等于善终,譬如饮鸩从容的苏格拉底客观记为 0 分)。第四,建制力对客观善终略含机械成分(在位者多死于任上),故更干净的检验在存续端。第五,5 级死法量表仍能检出建制力 t = 8.5,可见明的零系数并非纯由粒度所致。综上,R3a 为明偏命划出边界:其方向性得以保留,但不稳健于完全客观的操作化;唯一穿透命名、盲评、客观三种口径的关联,是建制力对结局的关联。
Reading. Five observations follow. First, the master beam is not common-source: on objective survival institution-building still scores t = 3.7 and on objective fate t = 8.5, so the common-source worry is resolved. Second, the fate-tilt does not extend to objective manner-of-death: lucidity is insignificant on objective fate (t = 1.5, realized-only t = 1.0). Third, two causes operate together: halo-removal (the named legacy halo inflated lucidity) and construct compression (manner-of-death is not the same as a good end, since a composed Socrates drinking hemlock scores 0 objectively). Fourth, institution-building's link to objective fate is partly mechanical (rulers tend to die in power), so the cleaner test is on the survival side. Fifth, the five-level fate scale still detects institution-building at t = 8.5, so lucidity's null is not mere coarseness. The bottom line is that R3a bounds the fate-tilt: directionally preserved but not robust to a fully objective operationalization, and the one association surviving named, blind, and objective coding alike is institution-building's link to outcomes.
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