Co-design and civic governance: self and others in a dispute over urban infrastructure
Bibliographic record
Abstract
This paper explores how citizens help shape the urban environment, partly through their talk, as they participate in a dispute about what elements of that environment should be like. In our investigation of the talk in civic meetings concerning a bicycle lane, we argue that some of the interactional activities of the meeting can be understood as a form of co-design that involves both present and absent others. Accordingly, we seek to expand the understanding of co-design beyond those explicit collaborative practices that involve designers and others to also include contexts of urban governance. Through considering how citizens present themselves in ways that variously detail personal experience, knowledge of a City’s design-consultation processes, and references to multiple others, we can see how a disagreement concerning an element of urban infrastructure (an existing bicycle lane) is enacted in ways that impact subsequent governance decisions (the lane is removed). We consider how conflict and disruption might be considered constitutive elements of some situations of co-design, with our work building on previous scholarship that explores the policy-related settings of, e.g. government debates, as instances of co-design.
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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 | 0.021 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.027 | 0.103 |
| Scholarly communication | 0.019 | 0.014 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".