Bibliographic record
Abstract
Facing global crises that are interconnected and overlapping, it is clear that the world as we know it is in transition. Some call this the meta-crisis. Some situate us in a time between worlds, where we are “living off of expired stories” (Machado de Oliveira, 2021) and need to ready ourselves for different ones. In the tradition of systemic design, we seek to inquire into how design practices can be adapted for deeply complex contexts like transition. What does it mean to situate our design practice in the societal transitions we find ourselves in and with some directionality toward the transitions we desire? We are asking ourselves these questions in an ongoing project focused on transitions to well-being economies in Toronto, Canada. \n \nHere, we outline four systemic design orthodoxies (i.e., norms that guide thinking and action) that we hypothesize can be limiting working within the context of transition: rushing, seriousness, needing requisite variety, and creating anew. In our project, we experiment with flipping these orthodoxies and working from a foundation of slowing down, light-heartedness, following existing relations, and noticing existing wisdom and innovation. In our presentation, we share stories and learnings from the project thus far and reflect on what it means to design in this time between worlds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".