Contesting the “Classical,” Creating Communities
Bibliographic record
Abstract
On December 6, 2022, the authors convened the first virtual “Intercollegiate Classical Japanese Poetry Contest”—also known as Reiwa yonen sankō jūsanban utaawase 令和四年三校十三番歌合 (Three-Schools Poetry Contest in Thirteen Rounds in the Fourth Year of Reiwa)—between our first-semester students of classical Japanese language (bungo). The contest is shaping up to be an annual event, with sequels involving a new set of institutions held in 2023 and 2024. This paper presents our reflections on this project, including its genesis, its outcomes, and its prospects. In addition to exploring the value of creative composition in classical language education, we argue that such approaches challenge the perception of bungo as “dead,” and we outline the process we undertook to incorporate this particular assignment into coursework and class time. Within the landscape of bungo pedagogy in North America, experimental approaches such as our contest promise to foster community, enrich understanding of bungo, and bolster student interest in classical language and culture.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.024 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.018 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".