Bibliographic record
Abstract
[Para. 2]: "On October 21, 2021, Joseph Paul Christie—Paul to his many friends—passed away peacefully at home. Paul lived a long and joyous life, from his youth in Toronto to adventures in London as a bookseller and a distinguished career as a court reporter with the Ministry of the Ontario Attorney General, but one of his many defining traits was his love of the arts. For the last thirty years of his life, Paul served as a front of house team member (to over-simplify, we might say ‘usher’) at theatres around Toronto, most notably the Elgin and Winter Garden Theatres. From this insider’s position, Paul saw as much theatre as he could. His theatregoing career stretched back to boyhood, and lasted until he literally could not see any more plays, as the COVID-19 pandemic closed theatres in the spring of 2020. After Paul’s passing, the Toronto Metropolitan University Archives and Special Collections were honoured to receive a gift commemorating a life in the theatre. In dozens of carefully curated binders, we were presented every programme (and ticket stub, and clipping, and souvenir postcard) that Paul Christie collected over the course of sixty-eight years, filed chronologically and with extensive annotation to create the Paul Christie Theatre Program Collection reflecting a lifetime in the arts."
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.073 | 0.030 |
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".