Articuler Imaginaires, Sciences participatives et innovations technologiques: Retour d'expérience sur les Explorations Quantiques 2050
Bibliographic record
Abstract
This text presents the Explorations 2050 methodology based on its application to quantum technologies between 2022 and 2023 Quantum Explorations 2050 at Grenoble Alpes University in collaboration with the University of Sherbrooke. The methodology brings together researchers and citizens to develop collective imaginaries about the future of technologies in order to think scientifically about the human and societal challenges of technological innovation in a participatory research approach. Participants (researchers, citizens, artists, businesses, etc.) imagined socio-technical futures mobilising quantum physics by 2050. Imagination is used as a performative tool capable of influencing technological trajectories. The method combines design fiction workshops, morphological analysis and literary narration. Five contrasting scenarios of societies coexisting in 2050 are produced. These narratives explore the tensions between technosolutionism and sobriety, innovation and ethics on individual and collective scales. The project shows how collective narratives can co-construct meaning and inform collective deliberation on innovations. In this respect, Explorations 2050 offers a novel methodological framework for thinking about ‘imaginaries of action’ capable of influencing research and innovation policies. While highlighting the risks of possible drifts towards technological standardisation of imaginaries of the future, the authors call for truly transformative creativity.
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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.039 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".