The Experiential Futures of Futureproof: A Format for Improvising Future Scenarios
Bibliographic record
Abstract
The Futureproof project is a model for engaging with the work of experiential futures using the format of improv theatre. It answers to the need for popularizing engagement with futures thinking identified in futures studies, and posits comedy and adaptability - two inherent qualities of improvisation - as areas of particular interest to the aims of futures discourse and experiential futures work. Key methods from its core disciplines of futures studies and improv are evaluated and combined to create a format for the creation and performance of improvised future scenarios that are accessible to a general audience. On a practical level, Futureproof outcomes include three public performances for sold-out crowds at the Bad Dog Theatre in Toronto, staged with a cast of professional improv actors and the engagement of a guest expert, each time representing a different discipline. The analysis and discussion of the experience suggests that both laughter and adaptability, key elements of improv art and the Futureproof format, can be usefully employed in the service of futures thinking and research. Looking ahead, the project also considers possible future iterations of the format, suggesting potentially advantageous design changes to its framework to orient it towards varied audiences.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 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".