The role of participatory design activities in supporting sense-making in the smart city
Bibliographic record
Abstract
We examine the role of participatory design activities in supporting sense-making while anticipating technological effects in smart cities. The effects of technology are not univocal. Therefore, creating smart city visions that enclose multiple meanings requires providing environments where stakeholders make the often-implicit processes of meaning attribution to technology explicit. We develop and test three participatory design activities to anticipate value changes and controversies in smart cities, and analyze how these activities supported seven sense-making properties. Our results show that visibilizing, reframing, and imagining are key characteristics of participatory design activities in supporting sense-making. Visibilizing technological impacts ‘makes things public,’ revealing existing perspectives and fostering new ones. Reframing technological impacts enhances empathy for diverse interests instead of treating smart cities as technical problems. Imagining supports understanding connections between technology and society to anticipate impacts. Our insights contribute to the provision of participatory design activities to articulate multiple meanings around smart cities.
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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 | 0.078 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.023 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".