Prizing Dominance: Disruption, Capital, and the Power and Practices of Literary Prize Culture in Canada
Bibliographic record
Abstract
Literary prize culture operates as a niche sphere within the broader field of cultural production; similarly, larger "reading publics" become condensed into specific "prizing publics" around individual prizes.These prizing publics comprise mainly audience members and readers, but also authors, critics, sponsors, jurors, and scholars (among others), all of whom are offered avenues through which to become part of the prizing mechanism.This study describes an implicit "idealized prizing timeline" that dictates the ways in which members of a prizing public may interact with the prize; at a surface level this timeline organizes and manages participation in order to avoid disruption to the prize.Due in part to the largely inflexible nature of this timeline, literary prizes become prone to disruption.However, literary prizes prove difficult to disrupt in a way that meaningfully shifts the purpose, operation, or reception of a prize.As a result, this study identifies disruption as a key piece of the implicit prizing timeline which prizing institutions and organizers often cannily turn to their own use-leveraging scandal, uncooperative members of the prizing public, or organizational missteps into a fortification of their present and future power as well as a fortification of their dominant, consecratory position in the field of cultural production.This project considers three such disruptions in the Canadian literary prize sphere.The first case study considers the disruption of the Giller Prize in 2010 by Gaspereau Press, during which the small press could not produce enough copies of the award-nominated and then awardwinning novel to satisfy the ravenous prizing public, counter to the desires of the Giller; the second case study examines the disruption of Québécois prize le Prix littéraire des collégiens in 2018, during which the prizing public protested and subsequently disrupted the prize's new sponsorship agreement with Amazon, forcing the prize to choose between social approval and To my parents, first and always: for infecting me with curiosity, instilling me with stubbornness, teaching me the importance of an Oxford comma, and sending me money to buy cheese.To Gido, too-the original Dr. Bayrock.You died before I was born, but you didn't have to be here to show me the way.To Babcha, who supported me at key moments: even now I can feel you lifting me and loving me.Thank you.I'm indebted to my comrades in arms who kept me afloat through difficult times.To Ross for never turning down a Jägerbomb; to Meghan for calling on the pests of the house; to Cait and Callie for nights on the back deck and a group chat for rocks; to Todd for a truly excellent Christmas party right before there were no parties anymore; to Carmen and Allie for tacos and ravioli and potato stuffing and hotpot and Costco chicken strips.Most of all, to Ronnie: my most joyful and steadfast and brilliant pack animal.I wouldn't have made it out without you, and I wouldn't have wanted to, anyway.To my supervisor, Dr. Jody Mason, who attached an article on prize culture to the very first email she ever sent me and never stopped.Thank you for gentle shepherding and fortifying Zoom calls, for updates on your skiing co-op and your willingness to read on the train.Thank you to the rest of my committee, for keen eyes
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.041 | 0.015 |
| Scholarly communication | 0.015 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".