Bibliographic record
Abstract
Public space is neither a fixed thing, nor a stable concept. This paper applies the term ‘dialogue’ as a conceptual basis for the idea of public space as something that changes according to multiscalar and overlapping contexts, with use and discourse. The concept of dialogue is developed from the dialogism of Mikhail Bakhtin whose related notions of ambivalence, polyphony, heteroglossia, carnival and chronotope are used to support a dialogical understanding of public space. The paper develops this understanding by creating a parallel between Bakhtin’s dialogism and the Barking Town Square by muf architecture/art (2004-2010). Through this parallel reading, the paper suggests that design proposals for the public realm are valued propositions that suggest a particular transformation of aesthetic, ethical, social and political relations through the ordering and transformation of spatial relations. No design, no conception, and therefore no dialogue creating public space can be neutral—but inevitably takes place within a fraught dialogical context inseparable from individual positioning and responsibility. The question of boundary maintenance thus arises inevitably, and the paper examines a range of such problematic demarcations, including between public and private, typologies and flexible criteria, immediate and social contexts, and ideals and reality. Given dialogue’s condition of ambivalence and incompleteness, the paper argues that the inherent contradictions to the concept of ‘public space’ are its very conditions for existence.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.055 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.008 |
| 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".