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<p>Measuring technological complexity across species, as well as across&#xa0;temporal and spatial scales, is an ongoing challenge among authors who work on primatological, archaeological, and/or ethnographic questions. Researchers in these individual fields have developed a number of innovative ways of approaching this issue that reflect the specific affordances of their data with a known set of limitations. However, comparability between these approaches is often difficult. One such field-specific approach is the techno-unit method of Oswalt <i>et al.</i> (1976), which has had a massive impact on our interpretation of ethnographic technology over the fifty years since its publication. Nevertheless, this method has issues with its compression of variability and the different pathways to “complexity”. Here, we review a number of different ways technological complexity has been measured in non-human primates, the archaeological record, and modern human foragers, in order to identify the relative strengths and weaknesses of each. We suggest that the approach deployed in any given study should continue to follow the data and research questions under consideration, but that we lack an easily-applicable method that allows explicit comparisons between fields of study. In this context, we introduce the Tool Systems Approach as one possible way of doing so, which decomposes tool manufacture into its constituent steps (<i>i.e.</i>, Tool Systems Total) and discrete forms of action (<i>i.e.</i>, Total Discrete Actions). We apply the approach to a number of different technologies across the three fields, to explore the practicalities of its application, as well as its limitations. Plotting these different technologies with regards to their maximum complexity through time reveals trends that may map onto important changes in cognitive evolution, which are also reflected in ever-growing variability in the complexity of individual artefacts. The ramifications for the study of technological complexity as a whole are discussed.</p>

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The Tool Systems Approach: Measuring Complexity in the Primatological, Archaeological, and Ethnographic Records

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月15日

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  • James Clark,
  • Lucy Timbrell,
  • Cecilia Padilla-Iglesias,
  • Laura van Holstein,
  • Jonathan Paige,
  • Antoine Muller,
  • Chris Clarkson,
  • Kathelijne Koops,
  • Eleanor M. L. Scerri,
  • Manuel Will

摘要

Measuring technological complexity across species, as well as across temporal and spatial scales, is an ongoing challenge among authors who work on primatological, archaeological, and/or ethnographic questions. Researchers in these individual fields have developed a number of innovative ways of approaching this issue that reflect the specific affordances of their data with a known set of limitations. However, comparability between these approaches is often difficult. One such field-specific approach is the techno-unit method of Oswalt et al. (1976), which has had a massive impact on our interpretation of ethnographic technology over the fifty years since its publication. Nevertheless, this method has issues with its compression of variability and the different pathways to “complexity”. Here, we review a number of different ways technological complexity has been measured in non-human primates, the archaeological record, and modern human foragers, in order to identify the relative strengths and weaknesses of each. We suggest that the approach deployed in any given study should continue to follow the data and research questions under consideration, but that we lack an easily-applicable method that allows explicit comparisons between fields of study. In this context, we introduce the Tool Systems Approach as one possible way of doing so, which decomposes tool manufacture into its constituent steps (i.e., Tool Systems Total) and discrete forms of action (i.e., Total Discrete Actions). We apply the approach to a number of different technologies across the three fields, to explore the practicalities of its application, as well as its limitations. Plotting these different technologies with regards to their maximum complexity through time reveals trends that may map onto important changes in cognitive evolution, which are also reflected in ever-growing variability in the complexity of individual artefacts. The ramifications for the study of technological complexity as a whole are discussed.