An Architecture Of Shifting Mores: Transforming the Modern Downtown
Bibliographic record
Abstract
Since its inception, modernism has represented an embrace of changing socioeconomic conditions and has been characterized as a medium for enacting social change. Modernism is both shaped by and contributes to the moulding of changing social mores. The built fabric acts as an indicator of cultural values but is also acted upon by its inhabitants to reflect shifting social norms. An architecture reflective of shifting mores embraces this duality and uses it to instill a sense of optimism for the future. This thesis contends that modernism embodies a cycle of everevolving values and cultural shifts. As collective opinions change and socioeconomic conditions are transformed, it is essential that we demand new uses and meanings from our built environment. An architecture of shifting mores diverges from traditional modernist thinking. We can no longer wipe the slate clean to serve our shifting needs. This thesis is sited in London, Ontario’s Downtown Heritage Conservation District where ideas of pragmatism, hybridity, innovation, and shifting mores were tested on a city block, resulting in the proposed design framework. This thesis responds to the conditions of modernization that have resulted in the city as we know it. The framework being proposed puts cultural heritage at the forefront of city building while finding creative, new uses for underutilized infrastructure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".