Bibliographic record
Abstract
For over four decades, Canadian comics artist Chester Brown has been producing idiosyncratic and highly personal comics that have been influential to generations of other cartoonists. Throughout a career that began with self-published minicomics in the early 1980s, Brown’s work has been central to the history of alternative comics since the undergrounds. In such era- and genre-defining works as his serialized alternative comic book Yummy Fur, his surrealist Ed the Happy Clown, his autobiographical narratives The Playboy and I Never Liked You, his historical biography Louis Riel, his controversial memoir about seeing sex workers Paying for It, and his provocative retelling of biblical tales Mary Wept Over the Feet of Jesus, Brown has continually challenged existing ideas about the kinds of stories comics can and should tell. This book is the first extended critical engagement with the whole of Brown’s life and career. Taking a chronological and biographical approach, the book examines one of the most varied bodies of work in all of comics history in its changing cultural and personal contexts. Accessibly written, generously illustrated, and including lengthy engagements with Brown’s many unfinished and uncollected works, Chester Brown provides a new critical perspective on not just an influential comics artist, but also on the alternative comics history in which he has been a central figure. The book will be of interest to anyone interested in comic books and graphic novels, including how one publication format slowly gave way to the other.
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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 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.379 | 0.197 |
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".