Bibliographic record
Abstract
Joke Book is a creative thesis, a collection of comic personal essays, somewhat in the spirit of Montaigne, in which I trace the impact of several pivotal jokes on my life. Among other digressions, I give a mathematical theory of comedy using the Fibonacci sequence, mostly fail to read Kierkegaard’s Repetition, try to blame lutefisk for the bitter character of Saskatchewan humour, reflect on my experiences in Skit Skit (a mildly successful local sketch comedy troupe in my city of 250,000), and tell of the time my father brought home his malfunctioning Wang (Laboratories Computer). In the process, I give an incomplete though still exhaustive account of my life and my surroundings (namely, rural Saskatchewan since 1985), and reflect on racism, class, sexism, television, memes, hip-hop, and, again, lutefisk. Sometimes bordering on the absurd, the work is more footnotes than actual prose, and more sizzle than steak. It also details the author’s complicity in the wrongful accusation and subsequent murder of a chicken in 1993, when the author was eight years old.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.387 | 0.342 |
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".