Infrastructuring Public Consultation in Town Planning— How Town Planners Translate Public Consultation into a Socio-Technical Support System
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract For public consultation in town planning, town planners can employ various software systems to improve the dialogue with citizens. This article looks at attempts to do so by following the work of a team of municipal town planners across four stages of public consultation held between 2012 and 2015. The study is based on detailed semi-structured interviews, field notes from regular visits to the planners’ office, and a database of public consultation comments and attendance at consultation events across the stages. Using an approach that considers planners’ work in the selection and implementation of software within institutional objectives and constraints as “infrastructure” work, we examine the joint deployment, use and effects of nine software tools and arising practices for public consultations. Our findings demonstrate how the infrastructure work of planners involved numerous interpretations about the possibilities for software adaptation and the effects of software use, which were enabled and constrained by consultation and planning requirements. The results also indicate a role for researchers in helping planners mediate between formal processes and public concerns, and illustrates how this technological-institutional struggle in infrastructuring work forms an essential part of town planners’ practice.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it