Literature of the New Year: Literary Variations on the Celebration of the New Year
Bibliographic record
Abstract
Is the New Year really new or old? Happy or sad? Is it only part of the process and the cycle of seasons making one look back and think of death? Is it a time to wish to stay where one is or hope for opportunities and possibilities? Like a point in a circle, is every day a New Year’s day? Is it a time for nostalgia and reminiscence or promises and resolutions for the future? With the (Gregorian and the British Government) changes in the Western calendar at different times in history and with different countries/cultures celebrating the New Year at different times of the year and with the fiscal year, political (election) year, and academic year being different from the traditional New Year of January 1st, does the New Year mark the beginning and the ending in just an arbitrary way? Centuries ago Britain’s earliest Poets Laureate introduced the tradition of writing a New Year poem. Since then there have been many authors writing New Year essays and poems. They include Robert Herrick, Charles Cotton, Johann Von Goethe, S. T. Coleridge, Charles Lamb, Lord Alfred Tennyson, William Cullen Bryant, Helen Hunt Jackson, Emily Dickinson, George Curtis, Thomas Hardy, Fiona Macleod (William Sharp), D. H. Lawrence, Rabindranath Tagore, and Sylvia Plath, among others.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.013 | 0.014 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".