Towards Sustainable Futures - Using strategic foresight in the design of transformative sustainability
Bibliographic record
Abstract
The unprecedented scale of disruption brought about by the COVID-19 crisis has brightly illuminated the dysfunction in many current social systems, adding to the litany of pressing planetary issues like mass extinctions, melting ice caps and biosphere loss. It’s widely recognized that ‘business as usual’ and associated incremental, slowed-paced change by political, business and social actors to address climate and social crisis are not sustainable nor sufficient options for the future health and wellbeing of the planet and most of its population. Innovative new ways to design and implement low carbon systems and socially inclusive solutions are required. \n \nFor organizations looking to navigate waves of disruption and create opportunities to ‘build back better’, what are the current and emerging design frameworks for sustainability? What conditions and mindsets are standing in the way of a transition to a low carbon, socially equitable future? And what might be some of the areas of opportunity for organizations seeking transformative sustainability in the future? \n \nThis research project explores how organizations might respond strategically to these challenges through the practice of foresight. Strategic foresight is a way of designing and building futures by understanding change through the lens of emerging trends and longtime drivers of change. It allows participants to generate strategies that address the critical uncertainties of tomorrow, and select actions today that may help shape desired futures and outcomes. \n \nThrough a literature review, the authors explore the interconnected nature of the sustainability challenge in Canada and what’s holding change back. They unearth emerging visions, systems and mindsets of sustainability that can help build a preferable future. Taking an action research approach, insights from the literature review informed a real-world case study during which the researchers designed and facilitated a strategic foresight process with TREC Renewable Energy Coop, a nonprofit leader in community-scale renewable energy and social finance in Toronto, Canada. The aim of the case study is to better understand how strategic foresight frameworks and practices can help organizations gain deeper insights into what the future may hold, and use those insights to develop robust transition capacities that will help guide them from legacy operating systems and mindsets to more transformative and sustainable business models and solutions. \n \nThe paper maps the insights gained through the research journey about how strategic foresight might be used by both sustainability and foresight practitioners. For organizations that are curious about the potential power of foresight to design and execute for sustainable futures, the case study section of the paper illuminates the potential. The paper concludes with findings and design principles generated by the dynamic praxis-oriented research process, and ideas for possible next steps and future research to help build the future we need.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".