Bibliographic record
Abstract
Architectural monuments lie scattered in small communities throughout Ontario, hidden by the everyday, masked by the sub-urban streets. The sub-urban streets where I lived felt impersonal and unnatural, with cookie-cutter designs and sterile atmosphere, with no sense of place. This lack of character, this illusion of the perfect suburbs, inspired the search that went beyond the ordinary to seek out the extraordinary. \n I began a pursuit to find monuments with value, to explore their histories, to observe their architecture, to photograph with a new perspective. I chose eight distinct heritage buildings to explore. Each preserves an identity, each holds expression, manifests character, each became a monument to my observations. One can appreciate the thoughtfulness that went into every detail, the craft that went into every patterned brick, the design that locates the heart of the home. \n Observations shape unnoticed potentials; they change each building, bringing it into the present. A photograph must do more than freeze time. Photography, like other creative acts, must interpret its subject matter. A photograph is powerful; it can be uplifting, it can be insightful, moving, and even imaginative. But when a photograph is part of a series of photographs, an accumulation of details that unfolds the story of a building, then it’s not just about what an individual photo says by itself, but instead it is about how the image forms connections with other stories, histories, forces, and sensations. \n This thesis in its entirety is an experiment, formed from individual elements brought together, creating unforeseen connections. It is for the observer to define what they see in the history, the images, and the narrative.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".