Bibliographic record
Abstract
Stephen is middle-aged. He's gay. He's content, except when he isn't. Stephen is a teacher. He's a poet. He has a new teaching job in Kamloops, BC. Stephen has HIV. DR SAD is the story of one man's journey across Canada and through his diagnosis. It is the story of the distance between queer urban spaces and a small campus in a small city in small-town BC. It is the story of discovering the self within the world, and the world within the self, of discovering the difference between living a life and simply enduring one. This is a tragicomic cross-campus, cross-country romp that believes in the power of romance. Weaving together narratives of past and present, of Toronto's Gay Village and the streets of Kamloops, BC this lively and dynamic semi-autobiographical novel dives deeply into gender and queerness, class and privilege, and the realities of aging. It is a dynamic and engaging hybrid, stylistically daring while remaining intimate and human. Leaping through time and mixing the playfully serious with the seriously playful, DR SAD blends poetry with prose and finds the humour in despair in one complete, glittering tragedy of triumph
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.364 | 0.187 |
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".