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The six scenario archetypes framework: A systematic investigation of science fiction films set in the future.
Fergnani, Alessandro; Song, Zhaoli.
  • Fergnani A; National University of Singapore, Singapore.
  • Song Z; National University of Singapore, Singapore.
Futures ; 124: 102645, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-843860
ABSTRACT
We propose a new scenario archetypes method generated by extracting a set of archetypal images of the future from a sample of 140 science fiction films set in the future using a grounded theory analytical procedure. Six archetypes emerged from the data, and were named Growth & Decay, Threats & New Hopes, Wasteworlds, The Powers that Be, Disarray, and Inversion. The archetypes in part overlap with and confirm previous research, and in part are novel. They all involve stress-point critical conditions in the external environment. We explain why the six archetypes, as a foresight framework, is more transformational and nuanced than previously developed scenario archetypes frameworks, making it particularly suited to the current necessity to think the unthinkable more systematically. We explain how the six archetypes framework can be used as predetermined images of the future to create domain specific scenarios, making organizations more resilient to critical, disruptive futures. We finally present and discuss a case study of the application of the method to create scenarios of post-Covid-19 futures of work. (https//www.youtube.com/watch?v=q82_X7fN_XA).
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Qualitative research / Systematic review/Meta Analysis Topics: Long Covid Language: English Journal: Futures Year: 2020 Document Type: Article Affiliation country: J.futures.2020.102645

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Qualitative research / Systematic review/Meta Analysis Topics: Long Covid Language: English Journal: Futures Year: 2020 Document Type: Article Affiliation country: J.futures.2020.102645