20:30 BRUXSELS TALKS
Bibliographic record
Abstract
On the 23rd of January 2020, a radio talk show of the future, 20:30 Bruxsels Talks, took place in Brussels. With guests and artists from the year 2030, it discussed how the transition to a climate-proof city had happened since 2019. In this article, we present and frame the development of the show and provide insight into the participative creation process. The radio show exemplifies (a) how future fiction can be used as a tool to evoke change and (b) how the participatory development of futurist fiction can be used as a method to trigger imagination and conversation on what citizens want for our cities. We argue that there is an opportunity for researchers to explore fiction as a method, as a format and as a space. Foresight practitioners who want to create engaging stories may find inspiration in the body of knowledge of arts-based research and the arts. Note: This article should be read in conjunction with 20:30 Bruxsels Talks: A Script for a Future Fiction Radio Show, in this issue, written by the same author team and published in this volume.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.257 | 0.098 |
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".