Bibliographic record
Abstract
C ontention: crosswords are the shit.Acknowledgement: they might not seem to be.Rebuttal: if they don't "seem to be," you've either made a mistake or you haven't given them a chance or you're just kind of a drag.For those who don't yet get crosswords, though, this one's for you.And for those who do get crosswords, this one is for you as well.To get started, we have to dive into the crossword's contentious, feverish, one-hundred-percent-riveting past.To get meaningful, we have to surface to bathe in the glory of its present.We start in New York.Some patriotic Italians would have you believe their countryman, Giuseppe Airoldi, came up with the crossword concept pre-1900.They are liars.The first crossword was born on the morning of December 21st, 1913, to a writer for the New York World: one Arthur Wynne.Was this the crossword we know and love today?The one that drives the masses to take the free ad-riddled newspaper they'd otherwise leave moldering in its vandalized box?The one that's inspired films, books, and regrettable fashion statements?The one that gives us a brief respite from the tedium of what we've settled for?No.This is 1913, guys.They didn't even have TV.Google some pictures of a McDonald's menu from another country.That's how the first crosswords were: disconcertingly different.It wasn't even called a crossword-for all his smarts, Wynne settled on the far less tongue-delighting "Word-Cross Puzzle" as his game's title.Studious onomatologists will happily inform you that, owing to a type-setting error, the Word-Cross became the Cross-Word (a moment of accidental genius on par with the potato chip).After that, laziness kicked in and the term lost its majuscules, becoming known simply as the crossword.So yeah-the twentieth century is going through puberty and the New York World has just knocked the socks off its readership with the greatest innovation in newspapers since objectivity.People are clamoring for their fix, ink is flying absolutely everywhere, horses and buggies run amok as their drivers are otherwise occupied.The president of the Amateur Athletic Union complains that his athletes are too busy with puzzles to properly train.A Princeton professor tries to use them in place of a textbook.A Knoxville reverend forces his congregants to complete a sermon-related crossword puzzle before he'll even begin preaching.Legal aid organizations in Cleveland
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.596 | 0.547 |
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".