The city as a living museum: reimagining the architecture of industrial monuments through psychogeography and collective memory in Nelson, British Columbia
Bibliographic record
Abstract
Contemporary development is often designed within prescribed metrics of cost and performance ratios - perhaps with some consideration for the programmatic utility and outward presentation of the building - though rarely does it reflect the past history of the site on which it occupies. It is not common for a new development to seek to ascertain the collective subconscious that inhabits the echoing vestiges of its long-established location, one of monumental importance to the city it markedly takes its place within. Albeit a global phenomenon of modern practice in design, a specificity of locale, programmatic intent, and architectural premise are identified within this thesis as an exemplary study of this proposed rethinking of development - through Guy Debord’s Dérive. Any city to undertake this process would require its own depth and breadth of understanding critical to its particular genius loci to materialize a renewed condition of its neglected monuments. Through a collection of research and design - influenced by the Situationists (the Dérive), and urban theorists including Aldo Rossi, Kevin Lynch, and Christine Boyer - the city of Nelson, British Columbia will be analyzed through the frameworks of monumentality, collective memory, and psychogeography to revitalize abandoned industrial monuments as the initial movement for the city to be perceived and experienced as a ‘living museum’ of historic sites, and stories. Many heritage buildings have been preserved (to various degrees) largely within the downtown core of the city, however the precursor industrial monuments have not fared as well against the various conditions of time in an evolving city. As the catalyst for the founding of Nelson, primary industries and historic transportation routes long served as the backbone of all development, yet they are the least respected in terms of their heritage value on the immense sites they occupied. This makes the abandoned industrial monuments of the city the largest gaps in the urban fabric, and prime areas for a conception of recovery, and adaptation, to the contemporary dilemma of land utilization. A total of five historic ‘monuments’ throughout the city have been examined and architecturally illustrated anew as the first in a series of alternate proposals for an episodic rejuvenation of the urban landscape. Each of these sites has a long history of industrial importance in Nelson and have since fallen into disuse. Establishing them as core community spaces with programs both reflective of their collective histories, and of relevant contemporary use, will serve not just to revitalize the individual monuments, but further goals to stimulate future holistic development in neighbouring areas. While the five locations do not have a unifying design style or physical linkage (due to the nature of reflecting their unique origins and memories), they each have specific histories, including architectural narratives, and are all connected via the drifting perceptions of the urban dweller through the method of the Dérive. By reestablishing influential monuments of the city into public spaces with a concentrated collective memory (as well as individual experience), and connecting them with relevant transportation, significant historic places will be made accessible to the community, further revealing the unique conditions and stories that allowed for the urban form of Nelson to come into being.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.024 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".