OBJECTIVE According to the pristine conditions hypothesis, high-confidence identifications will be "remarkably accurate" when identification procedures (i.e., system variables, e.g., fair filler selection, double-blind administration, unbiased lineup instructions) are optimal, even if estimator variables (e.g., weapon presence, lighting, distance) are suboptimal (Wixted & Wells, 2017, p. 10). This has led some to conclude that estimator variables are not of much importance under those conditions. HYPOTHESIS We hypothesized that when multiple estimator variables are deficient, even high-confidence identifications will be less accurate than they would be when multiple estimator variables are optimal. METHOD With a sample of 2,191 college students (Mage = 20.14, 73% women), we conducted a strong test of this hypothesis by comparing a situation in which estimator variables were manipulated to produce either very good or very poor memory performance. RESULTS High-confidence suspect identifications were made significantly less frequently under poor viewing conditions than under good viewing conditions, and these differences are substantial if one assumes low base rates of guilt. CONCLUSIONS Estimator variables can be important for evaluating even high-confidence suspect identifications and establish some important boundary conditions for the pristine conditions hypothesis. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

中文翻译：

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即使对于在原始条件下进行的高可信度阵容识别，估计变量也很重要。

目标根据原始条件假设，当识别程序（即系统变量，例如公平的填充物选择、双盲给药、无偏见的阵容说明）是最优时，高置信度的识别将“非常准确”，即使估计变量（例如，武器存在、照明、距离）不是最理想的（Wixted & Wells，2017 年，第 10 页）。这导致一些人得出结论，估计变量在这些条件下并不重要。假设我们假设当多个估计变量不足时，即使是高置信度的识别也不会像多个估计变量最佳时那样准确。方法 以 2,191 名大学生（法师 = 20.14，73% 为女性）为样本，我们通过比较估计变量被操纵以产生非常好的或非常差的记忆性能的情况，对这一假设进行了强有力的测试。结果 与在良好的观看条件下相比，在较差的观看条件下进行高可信度嫌疑人识别的频率要低得多，如果假设犯罪率较低，则这些差异是很大的。结论 估计变量对于评估甚至高置信度的嫌疑人身份识别和为原始条件假设建立一些重要的边界条件也很重要。（PsycInfo 数据库记录 (c) 2021 APA，保留所有权利）。结果 与在良好的观看条件下相比，在较差的观看条件下进行高可信度嫌疑人识别的频率要低得多，如果假设犯罪率较低，则这些差异是很大的。结论 估计变量对于评估甚至高置信度的嫌疑人身份识别和为原始条件假设建立一些重要的边界条件也很重要。（PsycInfo 数据库记录 (c) 2021 APA，保留所有权利）。结果 与在良好的观看条件下相比，在较差的观看条件下进行高可信度嫌疑人识别的频率要低得多，如果假设犯罪率较低，则这些差异是很大的。结论 估计变量对于评估甚至高置信度的嫌疑人身份识别和为原始条件假设建立一些重要的边界条件也很重要。（PsycInfo 数据库记录 (c) 2021 APA，保留所有权利）。