Assessing Sustainable Development Goal Alignment in Local Food Systems: Insights from an Automated Text Analysis of the Organizational Literature

There is growing interest in assessing local food systems to guide efforts toward sustainability and aligning these assessments with the United Nations’ 17 Sustainable Development Goals (SDGs). However, the complexity of portraying local food systems poses numerous challenges for local communities,...

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Main Authors: Coralie Gaudreau, Arbi Chouikh, Laurence Guillaumie, Daniel Forget, Stéphane Roche
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Social Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-0760/13/11/582
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author Coralie Gaudreau
Arbi Chouikh
Laurence Guillaumie
Daniel Forget
Stéphane Roche
author_facet Coralie Gaudreau
Arbi Chouikh
Laurence Guillaumie
Daniel Forget
Stéphane Roche
author_sort Coralie Gaudreau
collection DOAJ
description There is growing interest in assessing local food systems to guide efforts toward sustainability and aligning these assessments with the United Nations’ 17 Sustainable Development Goals (SDGs). However, the complexity of portraying local food systems poses numerous challenges for local communities, and automated text analysis and artificial intelligence (AI) offer promising solutions. This study tested the use of an automated textual analysis to assess the alignment of the Mauricie region’s food system in Quebec, Canada, with the SDGs. The analysis examined 35 organizational documents from the region using an automated text analysis based on a list of keywords for each SDG. Initially, the analysis revealed that several initiatives in the Mauricie region covered specific SDGs quite well, such as eliminating hunger (SDG 2). Areas such as health and well-being (SDG 3) received moderate attention, while SDGs such as life below water and on land (SDGs 14 and 15) were less emphasized. When these results were presented to regional stakeholders, these stakeholders reported that the findings did not closely reflect their perceptions of the food system. This study confirms the potential of automated textual analysis and AI in assessing local food systems and underscores the parameters and challenges of accurately portraying sustainability in local food systems.
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spelling doaj-art-f5a92dffc7794fd5a10b8a7c926f902c2024-11-26T18:22:13ZengMDPI AGSocial Sciences2076-07602024-10-01131158210.3390/socsci13110582Assessing Sustainable Development Goal Alignment in Local Food Systems: Insights from an Automated Text Analysis of the Organizational LiteratureCoralie Gaudreau0Arbi Chouikh1Laurence Guillaumie2Daniel Forget3Stéphane Roche4Faculty of Nursing Sciences, Public/Community Health Programs, Université Laval, Quebec City, QC G1V 0A6, CanadaFaculty of Administrative Sciences, Université Laval, Quebec City, QC G1V 0A6, CanadaFaculty of Nursing Sciences, Public/Community Health Programs, Université Laval, Quebec City, QC G1V 0A6, CanadaVice-Rectorate of International Affairs and Sustainable Development, Université Laval, Quebec City, QC G1V 0A6, CanadaFaculty of Forestry, Geography and Geomatics, Université Laval, Quebec City, QC G1V 0A6, CanadaThere is growing interest in assessing local food systems to guide efforts toward sustainability and aligning these assessments with the United Nations’ 17 Sustainable Development Goals (SDGs). However, the complexity of portraying local food systems poses numerous challenges for local communities, and automated text analysis and artificial intelligence (AI) offer promising solutions. This study tested the use of an automated textual analysis to assess the alignment of the Mauricie region’s food system in Quebec, Canada, with the SDGs. The analysis examined 35 organizational documents from the region using an automated text analysis based on a list of keywords for each SDG. Initially, the analysis revealed that several initiatives in the Mauricie region covered specific SDGs quite well, such as eliminating hunger (SDG 2). Areas such as health and well-being (SDG 3) received moderate attention, while SDGs such as life below water and on land (SDGs 14 and 15) were less emphasized. When these results were presented to regional stakeholders, these stakeholders reported that the findings did not closely reflect their perceptions of the food system. This study confirms the potential of automated textual analysis and AI in assessing local food systems and underscores the parameters and challenges of accurately portraying sustainability in local food systems.https://www.mdpi.com/2076-0760/13/11/582local food systemfood system assessmentSustainable Development Goals (SDGs)sustainable dietsustainable development
spellingShingle Coralie Gaudreau
Arbi Chouikh
Laurence Guillaumie
Daniel Forget
Stéphane Roche
Assessing Sustainable Development Goal Alignment in Local Food Systems: Insights from an Automated Text Analysis of the Organizational Literature
Social Sciences
local food system
food system assessment
Sustainable Development Goals (SDGs)
sustainable diet
sustainable development
title Assessing Sustainable Development Goal Alignment in Local Food Systems: Insights from an Automated Text Analysis of the Organizational Literature
title_full Assessing Sustainable Development Goal Alignment in Local Food Systems: Insights from an Automated Text Analysis of the Organizational Literature
title_fullStr Assessing Sustainable Development Goal Alignment in Local Food Systems: Insights from an Automated Text Analysis of the Organizational Literature
title_full_unstemmed Assessing Sustainable Development Goal Alignment in Local Food Systems: Insights from an Automated Text Analysis of the Organizational Literature
title_short Assessing Sustainable Development Goal Alignment in Local Food Systems: Insights from an Automated Text Analysis of the Organizational Literature
title_sort assessing sustainable development goal alignment in local food systems insights from an automated text analysis of the organizational literature
topic local food system
food system assessment
Sustainable Development Goals (SDGs)
sustainable diet
sustainable development
url https://www.mdpi.com/2076-0760/13/11/582
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