Bibliographic record
Abstract
As authors we draw from our experience of hosting two virtual design and imagination labs, where we took a deep dive into the evolution of our economic system with a diverse group, and had a profound collective experience imagining possible alternatives that promote wellbeing and flourishing of people and planet. These labs were convened by the David Suzuki Foundation in Turtle Island/Canada during the pandemic. In each Lab, approximately 60 participants were invited from across government, First Nations communities, civil society, academia, and activism. Both the process of inviting, and the lab design and process, were carefully curated with an intention to bring different world views and perspectives to take a deep dive into re-imagining our economic system. As pracademics and systems change practitioners, we reflect on what is required to make visible the underlying conditions (including worldviews, myths, and metaphors) that keep our current systems in place, and what might be needed to free ourselves to imagine alternatives. We refer to this liberation as ‘escape’ and propose six elements of ‘escape’ for transformation. The process of unlearning and releasing ourselves from unhelpful limiting assumptions and worldviews applies to those ‘facilitating’ these processes of systemic change, as much as it applies to those participating in the labs. This form of collective practice requires constant vigilance, as no single methodology of framework is fit for purpose. We reflect on what this kind of methodological pluralism invites and offers, as we bring together different ways of knowing and different knowledge systems, and re-imagine alternatives that recognise the limitations and impact of our current economic system on people and planet.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.140 |
| Scholarly communication | 0.019 | 0.022 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".