Academic Journal
Machine learning for research on climate change adaptation policy integration: an exploratory UK case study
العنوان: | Machine learning for research on climate change adaptation policy integration: an exploratory UK case study |
---|---|
المؤلفون: | Biesbroek, Robbert, Badloe, Shashi, Athanasiadis, Ioannis N. |
المصدر: | Regional Environmental Change 20 (2020) 3 ; ISSN: 1436-3798 |
سنة النشر: | 2020 |
المجموعة: | Wageningen UR (University & Research Centre): Digital Library |
مصطلحات موضوعية: | Artificial intelligence, Climate change adaptation, Machine learning, Mainstreaming, Policy and decision making, Quantitative text analysis |
الوصف: | Understanding how climate change adaptation is integrated into existing policy sectors and organizations is critical to ensure timely and effective climate actions across multiple levels and scales. Studying climate change adaptation policy has become increasingly difficult, particularly given the increasing volume of potentially relevant data available, the validity of existing methods handling large volumes of data, and comprehensiveness of assessing processes of integration across all sectors and public sector organizations over time. This article explores the use of machine learning to assist researchers when conducting adaptation policy research using text as data. We briefly introduce machine learning for text analysis, present the steps of training and testing a neural network model to classify policy texts using data from the UK, and demonstrate its usefulness with quantitative and qualitative illustrations. We conclude the article by reflecting on the merits and pitfalls of using machine learning in our case study and in general for researching climate change adaptation policy. |
نوع الوثيقة: | article in journal/newspaper |
وصف الملف: | application/pdf |
اللغة: | English |
Relation: | https://edepot.wur.nl/526545 |
DOI: | 10.1007/s10113-020-01677-8 |
الاتاحة: | https://research.wur.nl/en/publications/machine-learning-for-research-on-climate-change-adaptation-policy https://doi.org/10.1007/s10113-020-01677-8 |
Rights: | https://creativecommons.org/licenses/by/4.0/ ; Wageningen University & Research |
رقم الانضمام: | edsbas.E95A2E35 |
قاعدة البيانات: | BASE |
DOI: | 10.1007/s10113-020-01677-8 |
---|