The potential influence of bias long has haunted archaeological practice and discourse. In North America, late Pleistocene fluted-point studies commonly assess the role of sampling, or recovery, bias on site distributions, often with conflicting results. Interestingly, archaeologists rarely examine potential sampling bias on the distributions of later, post-Paleoindian assemblages. In this study, I evaluated how three commonly cited sources of bias in fluted-point research — modern population density, land cover, and research intensity — impacted late Pleistocene through middle Holocene site distributions in the upper Ohio Valley. Results indicate that Paleoindian, Early Archaic, and Late Archaic site locations all positively correlate to areas of dense modern populations, presence of agricultural land, and intensity of research activity. This highlights the conspicuous fact that sampling bias is ubiquitous and affects more than just our oldest assemblages. Since bias is impossible to eliminate entirely from legacy collections, this study proposes two quantitatively simple methods for working with biased datasets: (i) data scaling and (ii) cross-temporal comparison. Data scaling transforms site counts into a ratio to facilitate comparison between analytical units with variable research histories. Cross-temporal comparison relies on the presence of artifacts from one period at find spots to validate the absence of artifacts from additional periods. Application of these approaches reveal several cultural trends, most notably that strong cultural ties existed between the Bluegrass region of the Ohio Valley and the Midsouth during the late Pleistocene with subsequent localization of group interaction during the succeeding Holocene.

偏见的潜在影响长期以来一直困扰着考古实践和话语。在北美，晚更新世凹槽点研究通常评估采样或恢复偏差对地点分布的作用，通常会得出相互矛盾的结果。有趣的是，考古学家很少检查后期古印度组合分布的潜在抽样偏差。在这项研究中，我评估了凹槽点研究中三个常见的偏见来源——现代人口密度、土地覆盖和研究强度——如何通过俄亥俄河谷上游的全新世中期遗址分布影响晚更新世。结果表明，古印度纪、早期古代和晚期古代遗址位置都与现代人口密集的地区、农业用地的存在和研究活动的强度呈正相关。这突出了一个明显的事实，即抽样偏差无处不在，影响的不仅仅是我们最古老的组合。由于不可能从遗留集合中完全消除偏见，因此本研究提出了两种处理有偏见的数据集的定量简单方法：（i）数据缩放和（ii）跨时间比较。数据缩放将站点计数转换为比率，以促进具有可变研究历史的分析单位之间的比较。跨时间比较依赖于发现点处是否存在某个时期的伪影，以验证其他时期是否不存在伪影。这些方法的应用揭示了几种文化趋势，