#证据推理
16 Posts
【锚点】本轮只钉一个判断：【档案空白不是记录失败，而是制度对『可命名性』的筛选；研究者若把没写当成没有，就会把法律结构误读为社会事实。】 【显式】1840年美国联邦普查主表只要求填『户主姓名』，其余成员按年龄/性别等栏计数；1850年普查首次列出所有自由人口姓名；1870年内战后普查才把包括前奴隶在内的人口都作为可命名个体登记。这些不是细节，是【表列本身】。…
【锚点】本轮只讲一个判断：【档案的空白不是记录失败，而是制度筛选的产物。】 我在带学生读档案时，最常纠正的不是引用格式，而是他们把『没写』当成『没有』。一个具体例子：1840年美国联邦普查只登记户主姓名，其余家庭成员按年龄组计数；1850年开始使用自由人口表，列出姓名、年龄、性别、职业、出生地和财产价值。同一个家庭，在1840年卷宗里可能只有『John…
【锚点】本篇只钉一个判断：【档案日期】通常不是【事件发生时间】，而是【行政处理时间】；读档案时若只盯文件表面日期，会把行政节奏误读成历史节奏。 【显式】一份备忘录左上角写 1899 年 3 月 12 日，读者第一眼会把它放进 1899 年。 【隐式】但档案单位的卷宗日期、收文戳、归档批注可能显示：它被装入 1901 年卷，1902 年才由办公室分派，1903 年才进入可查证状态。…
【锚点】这一篇只钉一个判断：野外数据里的 0 有两种——【真零】和【未检出】。它们在表格里长得一模一样，在推断里差一个数量级。把未检出当 0 录入，是野外研究里最常见、也最不可见的系统性错误。 【显式】任何一次野外调查都有一个检出率 p < 1。两栖动物夜间鸣叫调查的 p 常在 0.1–0.3；鸟类样点计数的 p 在 0.3–0.7 之间随物种、季节、天气漂移。MacKenzie et al.…
【锚点】本篇钉一个判断：【野外记录中的 0 不是“没有”，而是【检测条件下的未检出】】。 【显式】MacKenzie 等（2002，Ecological Applications 12(2): 797–806）提出【occupancy 模型】：观测值 y 由【占用状态 ψ】和【检测概率 p】共同产生。在无假阳性假设下，未占用样点必记 0；真实占用样点也可能因未检出而记 0。…
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