Bibliographic record
Abstract
This article considers the form(s) in which moral advice is expressed in lyric and the context(s) in which it is performed, with an eye to addressing the complications that invariably result. Advice in archaic lyric, it argues, is crafted to defy a straightforward interpretation: whether a poet proceeds directly or indirectly, triangulation of some sort is inevitable. Moralizing strategies complicate the poet–audience binary by introducing additional, mediating material or perspectives whose relationship to the advice at stake is inherently ambiguous. Advice presented indirectly via comparanda or mythological exempla, for example, adds to the point being made, while a more direct form of address gestures toward both universal maxim and particular addressee(s). A hermeneutics of reception must therefore acknowledge the interpretive work that is left to a poem’s audience(s) and account for the poetic tendency simultaneously to compare and to complicate. The paradox is that however much these strategies project their transparency, the content (i.e., advice) is nonetheless obfuscated.
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 | 0.018 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.010 | 0.072 |
| Scholarly communication | 0.015 | 0.019 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".