Bibliographic record
Abstract
At the centre of this personal essay is my effort to understand the impact of buildings on literature, and the impact of literature on buildings. What happens when the built environment is drastically altered? How does memory mediate between what used to be there and what replaced it? I have drawn from personal experience, ancient myths and modern fairy tales, seeking to highlight both the intimate and the universal voice about places and the memories of those places. Piecing together personal narrative in prose and poetry with passages from classic and modern works, I endeavor to create an openended collage of words and virtual images that help readers navigate their own oceans of memory and architecture. I am inspired by the work of other authors who animate the page, letting words and thoughts come in and out of focus. Among them are the American author Carole Maso ( The Art Lover , 1990; Ava, 1993); the Canadian classicist and poet Anne Carson ( If not, winter: Fragments of Sappho , 2003; Nox, 2010); the German academic and author W.G. Sebald ( The Emigrants , 1996; Austerlitz, 2001); and the French conceptual artist Sophie Calle ( Take Care of Yourself , 2007; The Address Book , 2012).
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.015 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".