Manufactured landscapes : a case study of public space in the contemporary city
Bibliographic record
Abstract
This thesis aims to draw attention to the tensions that emerge out of conceiving a 'world class' public space, and projecting this abstraction onto an extremely hybrid social space in downtown Montreal. From some influential design, architectural, and art critics, the public space commonly known as Berri Square has received both local and international acclaim. But what actually happens in the space has defied expectations and largely been met with critical disdain. A resident base for punkers, skateboarders, and drug dealers as well as an everyday provisional soup kitchen for the homeless was clearly not what the city envisioned for this multi-million dollar public square. Thus, for several years the city has employed various tactics in an attempt to 'reclaim' the site. Through an empirical investigation into the design, development and use of Berri Square this thesis attempts to ground some of the dominant theories concerning the production of contemporary urban space, and contextualise some of the governing forces working to reshape urban space in the contemporary city. Based on the findings of the empirical research, it suggests that the conflicts between its various uses and values will continue to escalate until creative ways to manage them are articulated. An examination into some of the institutional and political constraints barring this articulation is the first step toward this process.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.021 | 0.015 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".