Design Literacies & Futures Literacies: Pedagogies for Diverse Futures
Bibliographic record
Abstract
Design pedagogy is futural. Our field of practice is to create design leaders of the future. In the context of uncertain futures an exploration of design literacies and futures literacies is a means of preparing our students for what is to come. Framed as a skill that uses collective intelligence, imagination and experimentation to think about the future in innovative ways, futures literacies and, so too design literacies, are about building people’s capacities to make sense of complex situations, while crafting ways to act that are more consistent with the type of futures we want. But how is this to be done? Exploring the ideas of futures literacies and design literacies the paper’s goal is to begin to reimagine both how we can design but also what we teach in design. In doing this, the paper is a provocation to those of us working in design education to think how we can think differently, design differently, and – importantly – teach design differently.
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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.026 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".