Bibliographic record
Abstract
âMais où sont les neiges dâantan?â François Villonâs most famous line is a kind of translation, a variation of the old âubi suntâ trope: Where are the things that used to be? But Villon specifically asks: Where are the snows? Even in the thick of a snowy winter, this snow is not the same as the remembered snows. The difference is affective, but it is also ecological: the worldâs climate is dramatically changing. Winter itself is changing.Donato Mancini has collected over eighty translations of Villonâs line, from Thomas Urquhartâs 1653 translation of Rabelaisâs quotation of the line, all the way up to translations by Florence Dujarric (2013) and Michael Barnholden (2014). From these he has arranged forty â a number that once stood for a countless number, like the forty thieves or the forty years of the biblical flood â into a booklength poem.Taking a cue from Caroline Bergvallâs âVia,â but deviating from it in significant ways, snowline traces how Villonâs line has changed and yet stubbornly stayed the same over six hundred years. It is a meditative and pointedly nostalgiac book: You will grow older as you read it, and the world around you will continue to melt into air.ABOUT THE AUTHORDonato Mancini is the author of Ligatures (2005), Ãthel (2007), Buffet World (2011), Fact âNâ Value (2011), You Must Work Harder to Write Poetry of Excellence (2012), and Loitersack (2014). He lives in Vancouver.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.092 | 0.004 |
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; both teacher heads agree on what is shown here.
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".