Geography Graduate Group, College of Agriculture and Environmental Science, University of California, Davis, Davis, California, United States of America.
Agricultural Sustainability Institute, University of California, Davis, Davis, California, United States of America.
PLoS One. 2023 Feb 3;18(2):e0278991. doi: 10.1371/journal.pone.0278991. eCollection 2023.
Interdisciplinary and transdisciplinary fields of inquiry and action have been important academic frontiers in recent years. The field of agroecology is a prime example of transdisciplinarity. With roots in the biophysical sciences, social sciences, and peasant movements, publications in agroecology have been growing rapidly in recent decades. Here we explain a method-the script-expert adaptive classification (SEAC) method-that allows us to examine the engagements between agroecology and the social sciences by identifying publications within the agroecological literature that engage with social science at various levels. Using the term "agroecology" and its iterations, we gathered a corpus of agroecology literature up to and including 2019 with 12,398 unique publications from five publication databases-Scopus, Web of Science, Agricola, CAB Direct, and EconLit. Using the SEAC method we then classified each publication as engaged, partially engaged, and not engaged with social sciences and separated this Agroecology Corpus 2019 into three corpora: agroecology engaged with social sciences (with 3,125 publications), agroecology not engaged with social sciences (with 7,039 publications), and agroecology with uncertain engagement with social science (with 2,234 publications) or unclassifiable. This article explains the SEAC method in detail so other transdisciplinary scholars can replicate and/or adapt it for similar purposes. We also assess the SEAC method's value in identifying social science publications relative to the classification systems of the major multidisciplinary bibliographic databases, Scopus, and Web of Science. We conclude by discussing the strengths and weaknesses of the SEAC method and by pointing to further questions about agroecology and the social sciences to be asked of the corpora.
跨学科和交叉学科的研究和行动领域近年来一直是重要的学术前沿。农业生态学是跨学科的一个主要范例。农业生态学的根基在于自然科学、社会科学和农民运动，近几十年来，农业生态学领域的出版物数量迅速增长。在这里，我们解释了一种方法——脚本-专家自适应分类（SEAC）方法——该方法通过确定农业生态学文献中与社会科学在不同层面上相互作用的出版物，使我们能够检查农业生态学与社会科学之间的相互作用。我们使用术语“农业生态学”及其变体，收集了截至 2019 年的农业生态学文献，这些文献来自五个文献数据库——Scopus、Web of Science、Agricola、CAB Direct 和 EconLit，其中包含 12398 篇独特的出版物。然后，我们使用 SEAC 方法对每一篇出版物进行分类，分为与社会科学有密切联系、有一定联系和没有联系，并将 2019 年的农业生态学文献分为三个部分：与社会科学密切相关的农业生态学（3125 篇）、与社会科学没有联系的农业生态学（7039 篇）和与社会科学联系不确定或无法分类的农业生态学（2234 篇）。本文详细解释了 SEAC 方法，以便其他跨学科学者可以复制和/或根据类似目的进行改编。我们还评估了 SEAC 方法在识别与主要多学科文献数据库（Scopus 和 Web of Science）的分类系统相关的社会科学文献方面的价值。最后，我们讨论了 SEAC 方法的优缺点，并指出了进一步需要从这些文献中提出的关于农业生态学和社会科学的问题。
