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This paper presents the methodology and results of an assessment of the applicability and utility of artificial intelligence for advanced theory-based content analysis.
The pilot study tests the applicability, usefulness, and added value of AI for advanced theory-based content analysis within the framework of IEG's thematic evaluations. The paper assesses the efficiency gains generated by AI-assisted content analysis in labelling and classifying text according to an outcome-based conceptual framework. These assessments are conducted using a set of interventions associated with the World Bank's chronic malnutrition and stunted growth portfolio.
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Franzen, S., Quang, C., Schweizer, L., Budzier, A., Gold, J., Vellez, M., Ramirez, S. & Raimondo, E. (2022). Advanced Content Analysis: Can Artificial Intelligence Accelerate Theory-Driven Complex Program Evaluation? IEG Methods and Evaluation Capacity Development Working Paper Series. Independent Evaluation Group. Washington, DC: World Bank. https://ieg.worldbankgroup.org/sites/default/files/Data/Evaluation/files/Methods_AI.pdf
This is part of a series
These resources are part of the IEG methods papers series.
'Advanced content analysis: Can artificial intelligence accelerate theory-driven complex program evaluation?' is referenced in:
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