Quantitative storytelling

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Quantitative storytelling (QST) is a systematic approach to exploring the many frames potentially legitimate in a scientific study or controversy. [1] QST assumes that, in an interconnected society, multiple frameworks and worldviews are legitimately upheld by different entities and social actors. QST looks critically at models used in evidence-based policy. Such models are often reductionist in that tractability (i.e. the possibility of proceeding towards a solution to a given problem) is achieved at the expense of suppressing available evidence. [2] QST suggests corrective approaches to this practice.

Contents

Description

Quantitative storytelling (QST) addresses evidence-based policy and can be considered a reaction to methods of quantification with cost-benefit analysis or risk analysis.

Jerome Ravetz [3] and Steve Rayner [4] discuss the concept that some of the evidence needed for policy is removed from view. They suggest that 'uncomfortable knowledge' is subtracted from the policy discourse with the objective of easing tractability or to advance a given agenda. The word 'hypo-cognition' has been used in the context of these instrumental uses of frames. [5] [6]

According to Rayner, a phenomenon of "displacement" takes place when a model becomes the objective instead of the tool, for example, when an institution chooses to monitor and manage the outcome of a model rather than what happens in reality. [4] Once exposed, the strategic use of hypocognition erodes the trust in the involved actors and institutions. [4]

Approach

QST suggests acknowledging ignorance, as to work out 'clumsy solutions', [4] which may permit negotiation to be had among parties with different normative orientations. QST is also sensitive to power and knowledge asymmetries, [7] [8] as interest groups have more scope to capture regulators than the average citizen and consumer.[ citation needed ]

QST does not forbid the use of quantitative tools altogether. It suggests instead to quantitatively explore multiple narratives, avoiding spurious accuracy and focusing on some salient features of the selected stories. Rather than attempting to amass evidence in support of a given reading or policy, or to optimise it with modelling, QST tries to test whether a given policy option or framing conflicts with existing social or biophysical constraints. These are: [9]

Applications

A recent application of QST exploring the transition to intermittent electrical energy supply in has been made in Germany and Spain. [10] They use QST to explore a case of water and agricultural governance in the Canary Islands. [11]

Applications are to composite indicators [12] , use of biofuels, [13] , innovation [14] , bioplastic [15] , gender perspectives in urban household energy transition [16] , and in the context of Post-normal science [17] .


References

  1. ↑ Saltelli, Andrea; Giampietro, Mario (2017). "What is wrong with evidence based policy, and how can it be improved?". Futures. 91: 62–71. doi:10.1016/j.futures.2016.06.012 (inactive 8 October 2025).{{cite journal}}: CS1 maint: DOI inactive as of October 2025 (link)
  2. ↑ Scoones, I., Stirling, A., 2020. The Politics of Uncertainty. Routledge, Abingdon, Oxon; New York, NY: Routledge, 2020. | Series: Pathways to sustainability.
  3. ↑ Ravetz, Jerome R (2016). "Usable Knowledge, Usable Ignorance". Knowledge. 9: 87–116. doi:10.1177/107554708700900104. S2CID   146551904.
  4. 1 2 3 4 Rayner, Steve (2012). "Uncomfortable knowledge: The social construction of ignorance in science and environmental policy discourses". Economy and Society. 41: 107–25. doi:10.1080/03085147.2011.637335. S2CID   144194568.
  5. ↑ [Lakoff, G., Dean, H. and Hazen, D. (2008) Don't Think of an Elephant!: Know Your Values and Frame the Debate. Chelsea Green Publishing.](https://books.google.es/books?id=zbJ1oxHC9a0C)
  6. ↑ Lakoff, George (2010). "Why it Matters How We Frame the Environment" (PDF). Environmental Communication. 4: 70–81. Bibcode:2010Ecomm...4...70L. doi:10.1080/17524030903529749. S2CID   7254556.
  7. ↑ Boden, Rebecca; Epstein, Debbie (2006). "Managing the research imagination? Globalisation and research in higher education". Globalisation, Societies and Education. 4 (2): 223–36. doi:10.1080/14767720600752619. S2CID   144077070.
  8. ↑ Strassheim, Holger; Kettunen, Pekka (2014). "When does evidence-based policy turn into policy-based evidence? Configurations, contexts and mechanisms". Evidence & Policy: A Journal of Research, Debate and Practice. 10 (2): 259–77. doi:10.1332/174426514X13990433991320.
  9. ↑ Giampietro, Mario; Aspinall, Richard J.; Ramos-Martin, Jesus; Bukkens, Sandra G. F. (2014-05-30). Resource Accounting for Sustainability Assessment: The Nexus between Energy, Food, Water and Land Use. Routledge. ISBN   978-1-317-96207-6.
  10. ↑ A. Renner and M. Giampietro, "Socio-technical discourses of European electricity decarbonization: Contesting narrative credibility and legitimacy with quantitative story-telling," Energy Res. Soc. Sci., vol. 59, Jan. 2020.
  11. ↑ Cabello, V., Romero, D., Musicki, A. et al. Co-creating narratives for WEF nexus governance: a Quantitative Story-Telling case study in the Canary Islands. Sustain Sci (2021). https://doi.org/10.1007/s11625-021-00933-y.
  12. ↑ Kuc-Czarnecka, M., Lo Piano, S., Saltelli, A. (2020). "Quantitative storytelling in the making of a composite indicator". Social Indicators Research. 149(3), 77 (3): 775–802. doi:10.1007/s11205-020-02276-0.
  13. ↑ Cadillo-Benalcazar, J. J., Bukkens, S. G. F., Ripa, M., Giampietro, M. (1 January 2021). "Why does the European Union produce biofuels? Examining consistency and plausibility in prevailing narratives with quantitative storytelling". Energy Research & Social Science. 71 101810. Bibcode:2021ERSS...7101810C. doi:10.1016/j.erss.2020.101810. ISSN   2214-6296.
  14. ↑ Di Felice, L. J., Cabello, V., Ripa, M., Madrid-Lopez, C. (1 July 2023). "Quantitative Storytelling: Science, Narratives, and Uncertainty in Nexus Innovations". Science, Technology, & Human Values. 48 (4). SAGE Publications Inc: 861–887. doi:10.1177/01622439211053819. hdl:10810/62272. ISSN   0162-2439.
  15. ↑ Ayala, M., Thomsen, M., Pizzol, M. (2023). "Using quantitative storytelling to identify constraints in resource supply: The case of brown seaweed". Journal of Industrial Ecology. 27 (6): 1567–1578. Bibcode:2023JInEc..27.1567A. doi:10.1111/jiec.13440. ISSN   1530-9290.
  16. ↑ Musango, J. K. (1 June 2022). "Assessing gender and energy in urban household energy transitions in South Africa: A quantitative storytelling from Groenheuwel informal settlement". Energy Research & Social Science. 88 102525. Bibcode:2022ERSS...8802525M. doi:10.1016/j.erss.2022.102525. ISSN   2214-6296.
  17. ↑ Blackstock, K. L., Waylen, K. A., Matthews, K. B., Juarez-Bourke, A., Miller, D. G., Hague, A., Wardell-Johnson, D. H., Giampietro, M. (1 May 2023). "Implementing post-normal science with or for EU policy actors: using quantitative story-telling". Sustainability Science. 18 (3): 1235–1250. Bibcode:2023SuSc...18.1235B. doi:10.1007/s11625-022-01265-1. ISSN   1862-4057. PMC   9851903 . PMID   36694671.
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