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Analytical categories to describe imaginations about the collective futures: From theory to linguistics to computational analysis.
- Source :
- Futures; Feb2024, Vol. 156, pN.PAG-N.PAG, 1p
- Publication Year :
- 2024
-
Abstract
- Anticipation of collective futures has been described as one of the most critical challenges of contemporary societies. Imaginations or images of the collective future are a form of narrative and social activity that involves many complex political, psychological and cultural nuances that pose significant challenges in terms of assessment. In this article, we propose six analytical categories to describe qualitative information regarding imaginations about the collective futures. These categories reflect a conceptual integration of normative stances in Science, Technology and Society and capacity approaches to Futures Studies. We translated those analytical categories into grammatical markers that allow for their operationalisation. Using a large-scale participatory process in Chile aimed at systematising images of the future, we utilised Natural Language Process to transform the grammatical markers into computational codes that allowed us to automatically assess large amounts of qualitative data. Ultimately, our main argument is that analytical categories to describe imaginations about collective futures can be generated with reasonable foundations in the humanities and social sciences. • The paper discusses integrates Futures Studies and Science and Technology Studies. • Analytical categories are presented to describe imaginations about collective futures. • The categories include centralization, entropization, dimensionality, agency, semiotic distance, and modal attitude. • Grammatical markers are presented to operationalized these categories. • These markers are tested through Natural Language Processing. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00163287
- Volume :
- 156
- Database :
- Supplemental Index
- Journal :
- Futures
- Publication Type :
- Academic Journal
- Accession number :
- 175276611
- Full Text :
- https://doi.org/10.1016/j.futures.2024.103324