Bibliographic record
Abstract
Men and women meet, match, marry, and mate. This is the eternal story which Shakespeare's comedies retell again and again: Jack shall have Jill; Nought shall go ill: The man shall have his mare again, and all shall be well. ( A Midsummer Night's Dream , 3.2.461-3) The details may vary considerably – and all is not always well – but in every comedy this basic formula remains the same. Sometimes men chase after women. Sometimes women chase after men. Often men pursue women who pursue other men who pursue women, giving us the mad merry-go-rounds of love we find in plays like A Midsummer Night's Dream or The Two Gentlemen of Verona . Frequently women turn themselves into men for a while, like Julia, Viola, or Rosalind. Less often men get themselves turned into women, like Falstaff, or, like Bottom, into beasts. But even if their actual shape or sex remains unchanged, everyone is in some way altered by love, transmuted into something rich and strange, or “metamorphis'd” like Proteus and Valentine ( Two Gentlemen of Verona , 1.1.66, 2.1.30). The experience of passion changes everything: one's view of the world, of the beloved, even – or above all – one's own sense of self. Characters who, out of youth, inexperience, or disinclination had hitherto remained untouched by love suddenly find themselves caught up in the maelstrom of desire where everything is thrown into moral and emotional chaos before falling into a new Gestalt of socialized couples which represents the final (and, with luck, stable) product of this mysterious process of human natural selection.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".