Scarcity Poetics: Christian Bök’s Eunoia and the Economics of Literary Value
Bibliographic record
Abstract
Christian Bök’s Canadian bestseller Eunoia (2001) is an ideal study in how the romantic notion of literary value actually abides economic theories. Eunoia is a collection of five prose-poems each written using only one vowel grapheme (A, E, I, O, or U). These arbitrary material production constraints work just like economic sanctions, artificially inflating the scarcity—and hence value—of the text, both commercially and literarily. Discourse analysis of surrounding debates reveals that detractions and praises alike abide the same basic supply-and-demand logic: e.g., economic theories of (relative) marginal utility, as applied by Lee Erickson in The Economy of Literary Forms (1996). Building on Erickson’s thesis of how publication media costs shaped literary form and content, on Mary Poovey’s history of literary value’s origin in economic value, and on other efforts to combine literary study with economics, this essay applies economic theory to a rare opportunity to generalize the relation of literary material, form, and content. Conclusively, scarcity poetics/tactics are not just unique to Eunoia, but fundamental to all literary form. Eunoia’s extreme manipulation of linguistic materials isolates the general mechanism by which literary value is produced.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.033 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".