Identifying social science engagement within agroecology: Classifying transdisciplinary literature with a semi-automated textual classification method.

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...

Full description

Bibliographic Details
Main Authors: Natalia Pinzón, Ryan E Galt, Marcela Beatriz Baukloh Coronil
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2023-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0278991
_version_ 1811168403435552768
author Natalia Pinzón
Ryan E Galt
Marcela Beatriz Baukloh Coronil
author_facet Natalia Pinzón
Ryan E Galt
Marcela Beatriz Baukloh Coronil
author_sort Natalia Pinzón
collection DOAJ
description 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.
first_indexed 2024-04-10T16:25:43Z
format Article
id doaj.art-56d4b1ac2e53426a855c0a6e147a0863
institution Directory Open Access Journal
issn 1932-6203
language English
last_indexed 2024-04-10T16:25:43Z
publishDate 2023-01-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS ONE
spelling doaj.art-56d4b1ac2e53426a855c0a6e147a08632023-02-09T05:32:19ZengPublic Library of Science (PLoS)PLoS ONE1932-62032023-01-01182e027899110.1371/journal.pone.0278991Identifying social science engagement within agroecology: Classifying transdisciplinary literature with a semi-automated textual classification method.Natalia PinzónRyan E GaltMarcela Beatriz Baukloh CoronilInterdisciplinary 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.https://doi.org/10.1371/journal.pone.0278991
spellingShingle Natalia Pinzón
Ryan E Galt
Marcela Beatriz Baukloh Coronil
Identifying social science engagement within agroecology: Classifying transdisciplinary literature with a semi-automated textual classification method.
PLoS ONE
title Identifying social science engagement within agroecology: Classifying transdisciplinary literature with a semi-automated textual classification method.
title_full Identifying social science engagement within agroecology: Classifying transdisciplinary literature with a semi-automated textual classification method.
title_fullStr Identifying social science engagement within agroecology: Classifying transdisciplinary literature with a semi-automated textual classification method.
title_full_unstemmed Identifying social science engagement within agroecology: Classifying transdisciplinary literature with a semi-automated textual classification method.
title_short Identifying social science engagement within agroecology: Classifying transdisciplinary literature with a semi-automated textual classification method.
title_sort identifying social science engagement within agroecology classifying transdisciplinary literature with a semi automated textual classification method
url https://doi.org/10.1371/journal.pone.0278991
work_keys_str_mv AT nataliapinzon identifyingsocialscienceengagementwithinagroecologyclassifyingtransdisciplinaryliteraturewithasemiautomatedtextualclassificationmethod
AT ryanegalt identifyingsocialscienceengagementwithinagroecologyclassifyingtransdisciplinaryliteraturewithasemiautomatedtextualclassificationmethod
AT marcelabeatrizbauklohcoronil identifyingsocialscienceengagementwithinagroecologyclassifyingtransdisciplinaryliteraturewithasemiautomatedtextualclassificationmethod