Ruin-Ophilia: Preserving Cultural Narratives of a Lighthouse Through Controlled Ruination
Bibliographic record
Abstract
Once vital aspects of safer navigation routes and icons of industrial development, the Imperial Towers of Lake Huron and the Georgian Bay dominated over the Bruce Peninsula coastal landscape for almost two centuries.Their contribution to the development of their respective regions rendered them cultural landmarks and embedded them in the larger cultural narratives of their locales.However, advancements in technologies, like many other engineering works, led these structures to become obsolete.Among these is the Nottawasaga Island Lighthouse, now with all alternative use options exhausted, awaiting its end.This thesis explores a way to turn this ruination process into an architectural experience.Through "controlled ruination" the transmission of larger cultural narratives is enabled while the manmade melts into nature.ii AckNOwLedgemeNts I would like to thank my advisors Mariana Esponda and Susan Ross for all their support and encouragement.Without their extensive knowledge and great advice, this thesis would not have been accomplished.Thank you for giving me the passion to work with historic structures.I am
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".