JOURNAL ARTICLE

An Appreciation of Carl O. Sauer's Intellectual History.

  • Published In: Yearbook of the Association of Pacific Coast Geographers, 2023, v. 85. P. 67 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Yoon, Hong-key 3 of 3

Abstract

Based on Carl O. Sauer's taped reflections on his own academic life, this paper outlines and offers a personal appreciation of Sauer's intellectual history. I argue that Sauer's intellectual life can be conceptualized as three dialectical developmental stages: (1) the Warrenton-Calw stage , marked by general education in his hometown environment; (2) the Chicago-Ann Arbor stage , marked by steep intellectual growth and expansion of his knowledge in geography as an academic subject; and (3) the Berkeley Stage , characterized by his Mexican field work and establishment of his own form of historical-cultural geography. This paper argues that Sauer's own intellectual curiosity, rather than any external influences, was the primary factor behind his scholarly progression to successive stages. Driven by his own curiosity, Sauer covered a wide range of research themes covering physical geography, use of fire in the development of landscape, theoretical discussion of the landscape morphology, and prehistorical agricultural origins and dispersals. He was a remarkable scholar and teacher who made a significant impact on the course of geography. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Yearbook of the Association of Pacific Coast Geographers. 2023/01, Vol. 85, p67
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2023
  • ISSN:0066-9628
  • DOI:10.1353/pcg.2023.a913571
  • Accession Number:174475380
  • Copyright Statement:Copyright of Yearbook of the Association of Pacific Coast Geographers is the property of University of Hawai'i and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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