Constructive controversies : Redesigning democratic debate and ethical deliberation in the smart city
Bibliographic record
Abstract
The main goal of this thesis is to explore and enable the constructive use of socio-technical controversies, by means of design approaches, in order to stimulate democratic debate and ethical deliberation about smart cities. Socio-technical controversies are conflicts that follow from the complex interaction between the social and technical aspects of society. The association with controversies is often negative, and they are rather avoided then celebrated. However, controversies reveal what is at stake when introducing technology in the urban sphere. In other words, controversies are places where politics ‘happens’: a plurality of perspectives comes together, values are negotiated and new social practices emerge, forming spaces of self-organized participation and value-assessment. In this thesis, therefore, I suggest to embrace controversies as entry points to a more democratic debate on smart cities. Moreover, I argue that controversies allow a re-entering of public values into this democratic debate. By understanding controversies as resource rather than a burden, I aim to enhance the democratic debate on smart cities with a stronger emphasis on the values at stake that ignite the issues of importance. Through operationalizing controversies, I seek to open up space for debate, where diverse perspectives and a plurality of values can co-exist and lead to creative yet critical resolutions. This research concerns a societal need and scientific question in interaction with each other – discussing democratic participation in relation to the smart city raises research questions at the intersection of the ethics of technology, political theory and public debate, which are both theoretical and practical in nature. As a result, this transdisciplinary thesis embodies the theoretical conceptualization of controversies, whilst incorporating their societal character and engaging input from stakeholder representing the quadruple helix: research, government, industry and civil society. To achieve this, I propose design as a means to operationalize socio-technical controversies. Through a Research-through-Design process, I develop and evaluate two distinct design approaches to work with socio-technical controversies: the Network of Conflicts (Ch 4) and Future Frictions (Ch 5). By making issues visible and experiential, design helps to create agonistic public spaces that aim at constructively dealing with disagreements without necessarily resolving conflict. In conclusion, I show that the combination of controversy-thinking and design techniques provides a valuable approach for rethinking democratic debate and ethical deliberation in the smart city.
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 | 0.083 | 0.102 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.021 | 0.101 |
| Scholarly communication | 0.039 | 0.055 |
| Open science | 0.006 | 0.034 |
| Research integrity | 0.014 | 0.016 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".