Oneiric architecture: a filmic exploration of the subjective dream experience
Bibliographic record
Abstract
The mind’s ability to fill void space with elaborate landscapes and complex structures is \ntruly extraordinary. As humans we have an innate ability to create spaces, sometimes \nentirely new, sometimes variations of places we know, drawing from elements that we \nencounter in our conscious lives. This thesis explores this phenomenon of dreaming from \nan architectural perspective. This research considers the history of dreams as cultural and \nartistic phenomena and their subsequent representation amongst a vast array of media. \nFilm is identified as the most appropriate medium to represent the temporal qualities \nof dreams, and as such, is suggested as a potential tool for developing an architectural \ndesign strategy. In response to an increasingly objective architectural landscape, the \nhypothesis suggested herein uses filmic devices to design spaces that mimic aspects \nof the subjective dream experience. This thesis has culminated in the proposal of a \n“dreamatorium” development on Bethel Lake in Sudbury, Ontario. The project is a public \npark that explores oneiric space through a series of pathways and pavilions.
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 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 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".