Anticipating the Impacts of Integrating Disruptive Technologies from Societal Dialogues, A Promising Tool?
Bibliographic record
Abstract
The recent history of technological development has taught us that it is essential to consider a technology's social readiness level before considering its integration into society. While we have relied heavily from the outset on local participation to prepare for this integration, some experiences have been more positive than others. Two examples, nanotechnology in France and the Montreal Declaration in Quebec, can serve as benchmarks for the necessary conversation around current advances in future quantum technologies, even before they are developed. In the context of the creation of Sherbrooke's Quantum Innovation Zone, DistriQ, the “Quantum Dialogues” project launched from the Institut quantique (Université de Sherbrooke) aims to foster collaborations between the research community, entrepreneurs and society in an integrated dialogue-based approach. This article focuses on the first phase of this project: the application of a specific participatory practice, the Transformative Scenario Planning, from Kahane [1], to the development of quantum technologies at multiple levels of governance structures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".