Narrativity has been proposed as an indicator of episodic memory strength when people discuss their past (Nelson and Horowitz in Discourse Processes 31:307–324, 2001. https://doi.org/10.1207/S15326950dp31-3_5). Referential Activity, the extent to which words convey a speaker's experience of being present in the event being described, has been independently hypothesized to indicate episodic memory strength (Maskit in J Psycholinguist Res, 2021. https://doi.org/10.1007/s10936-021-09761-8). These hypotheses are tested using a linguistic measure of narrativity and a computerized measure of referential activity to predict previous independent ratings of episodic memory strength that used the Levine et al. (Psychol Aging 17(4):677–689, 2002. https://doi.org/10.1037//0882-7974.17.4.677) measure of internal details in retold personal memories provided by Schacter (Addis et al. in Psychol Sci 19(1):33–41, 2008. https://doi.org/10.1111/j.1467-9280.2008.02043.x). Raters scored narrativity on four brief near and far past memories elicited from 32 subjects, using Nelson's narrative temporal sequence method based on Labov’s (J Narrat Life Hist 7(1–4):395–415, 1997. https://doi.org/10.1075/jnlh.7.49som) analysis of spoken narratives of personal experience; computerized weighted scores of referential activity (WRAD) were obtained on these same 128 memories. Data analysis showed that narrative temporal sequences predict internal details and WRAD predict internal details. Adding WRAD to narrative temporal sequences improved the prediction of internal details.

当人们讨论他们的过去时，叙事性被提议作为情景记忆强度的指标（Nelson 和 Horowitz in Discourse Processes 31:307–324, 2001. https://doi.org/10.1207/S15326950dp31-3_5）。参考活动，即词语传达说话者在所描述事件中的存在体验的程度，已被独立假设为指示情景记忆强度（J Psycholinguist Res 中的 Maskit，2021。https://doi.org/10.1007/s10936 -021-09761-8)。这些假设使用叙述性的语言测量和参考活动的计算机化测量来测试，以预测以前使用 Levine 等人的情景记忆强度的独立评级。（Psychol Aging 17(4):677–689, 2002. https://doi.org/10.1037//0882-7974.17.4。677）由 Schacter 提供的重述个人记忆的内部细节测量（Addis 等人在 Psychol Sci 19(1):33–41, 2008. https://doi.org/10.1111/j.1467-9280.2008.02043。 X）。评分者使用 Nelson 的基于 Labov 的叙事时间序列方法（J Narrat Life Hist 7(1–4):395–415, 1997. https://doi.org /10.1075/jnlh.7.49som）对个人经历的口述叙述的分析；在同样的 128 个记忆上获得计算机化的参考活动加权分数 (WRAD)。数据分析表明，叙事时间序列预测内部细节，WRAD 预测内部细节。将 WRAD 添加到叙事时间序列中可以改进对内部细节的预测。组织/10.1111/j.1467-9280.2008.02043.x）。评分者使用 Nelson 的基于 Labov 的叙事时间序列方法（J Narrat Life Hist 7(1–4):395–415, 1997. https://doi.org /10.1075/jnlh.7.49som）对个人经历的口述叙述的分析；在同样的 128 个记忆上获得计算机化的参考活动加权分数 (WRAD)。数据分析表明，叙事时间序列预测内部细节，WRAD 预测内部细节。将 WRAD 添加到叙事时间序列中可以改进对内部细节的预测。组织/10.1111/j.1467-9280.2008.02043.x）。评分者使用 Nelson 的基于 Labov 的叙事时间序列方法（J Narrat Life Hist 7(1–4):395–415, 1997. https://doi.org /10.1075/jnlh.7.49som）对个人经历的口述叙述的分析；在同样的 128 个记忆上获得计算机化的参考活动加权分数 (WRAD)。数据分析表明，叙事时间序列预测内部细节，WRAD 预测内部细节。将 WRAD 添加到叙事时间序列中可以改进对内部细节的预测。基于 Labov (J Narrat Life Hist 7(1–4):395–415, 1997. https://doi.org/10.1075/jnlh.7.49som) 对个人经历口头叙述的分析的叙事时间序列方法；在同样的 128 个记忆上获得计算机化的参考活动加权分数 (WRAD)。数据分析表明，叙事时间序列预测内部细节，WRAD 预测内部细节。将 WRAD 添加到叙事时间序列中可以改进对内部细节的预测。基于 Labov (J Narrat Life Hist 7(1–4):395–415, 1997. https://doi.org/10.1075/jnlh.7.49som) 对个人经历口头叙述的分析的叙事时间序列方法；在同样的 128 个记忆上获得计算机化的参考活动加权分数 (WRAD)。数据分析表明，叙事时间序列预测内部细节，WRAD 预测内部细节。将 WRAD 添加到叙事时间序列中可以改进对内部细节的预测。