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Cited by 39Paleontology and Stratigraphy of FossilsPaleontology and Evolutionary BiologyHistory of Science and Natural History

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Anthropologically introduced biases in natural history collections, with a case study on the invertebrate paleontology collections from the middle Cambrian Spence Shale Lagerstätte

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Whitaker, Anna, Kimmig, Julien·2020·Palaeontologia Electronica
DOI 10.26879/1106
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Abstract

Natural history collections are critical for modern scientific investigations, which are greatly expanding on the potential data applications of historic specimens.However, using these specimens outside their original intent introduces biases and potential misinterpretations.Anthropogenic biases can be introduced at any point during the life of museum specimens, from collection, preparation, and accession, to digitization.These biases can cause significant effects when the user is unaware of the collection context, as specific collection biases are often known anecdotally, but not ubiquitously.In this case study, the University of Kansas collection of Spence Shale Lagerstätte material was examined for anthropogenic biases using a collections inventory, interviews with stakeholders, and a literature review.Biases were found related to collector interest, locality preference, and researcher interest and specialization.These biases create a distorted view on the diversity and ecology of the Spence Shale, and need to be considered in future research.

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  • Preservational variations can also be induced by fossil collection, preparation, accession, and digitization.

    “Preservational variations can also be induced by fossil collection, preparation, accession, and digitization (Whitaker & Kimmig, 2020).”

    From Probability-based preservational variations within the early Cambrian Chengjiang biota (China) (2022) · cites this paper as Whitaker & Kimmig, 2020

    The Field Bias section describes collectors favoring complete, well-preserved fossils, and the Preparation Bias section says preparation can remove or alter fossil surfaces. The Acquisition and Curation Bias and Digitization and Database Bias sections describe which specimens become available or appear in digital records, but do not say accession or digitization changes the fossils’ physical preservation. No page numbers are available in our copy. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Variations can be induced following certain practices such as sampling from a preferred locality, or the background, interest, and specialization of the sampling team.

    “Variations can be induced following certain practices such as sampling from a preferred locality, or the background, interest, and specialization of the sampling team (Whitaker & Kimmig, 2020).”

    From Probability-based preservational variations within the early Cambrian Chengjiang biota (China) (2022) · cites this paper as Whitaker & Kimmig, 2020

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Metadata

Authors
Whitaker, A., & Kimmig, J.
Affiliations
  • University of Toronto (CA)
  • Pennsylvania State University (US)
ORCID
Venue
Palaeontologia Electronica
Publisher
Coquina Press
Published
2020
ISSN
  • 1094-8074 (ISSN-L)
  • 1935-3952
DOI
10.26879/1106
OpenAlex
W3112564621
Cited by
39
References
3
Citations by year
2026: 4 · 2025: 8 · 2024: 8 · 2023: 8 · 2022: 5 · 2021: 6
FWCI
2.50
Type
journal article
Language
en
Open access
Licence
cc-by-nc-sa
Locations
Palaeontologia Electronica (publishedVersion, cc-by-nc-sa)
Funders
  • U.S. Department of Agriculture
  • Paleontological Society
  • U.S. Forest Service
Topics
  • Physical Sciences › Earth and Planetary Sciences › Paleontology › Paleontology and Stratigraphy of Fossils
  • Physical Sciences › Earth and Planetary Sciences › Paleontology › Paleontology and Evolutionary Biology
  • Social Sciences › Arts and Humanities › History and Philosophy of Science › History of Science and Natural History
Keywords
natural history collections, museum specimens, Lagerstätte, invertebrate paleontology, Middle Cambrian, collection inventory

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

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