Sisters / The Second Coming / When One Sings One Thinks No Wrong (Italian Proverb)
Bibliographic record
Abstract
Ever since I watched the sun and the moon undress the sky of its colour, ever since I could tell the difference between a "him" and a "her," ever since I could define the line between a "me" and a "you" and protect myself accordingly, I longed for a sister.Ever since I understood I was an accident (or, as Mother would say, "a surprise"), ever since I knew I came into the world dangling on a string, a joker sans joke, ever since I sensed the world is teaming with lonesome travellers and pleasureseekers sans purpose I longed for a sister.Ever since I was singled out and ostracized because my eyes were the wrong colour (Or was it my hair that was all wrong?), ever since I was left out in the cold, refused membership in a club or been un-invited to a party I longed for a sister to comfort me, tell me an injustice had been done-I was good enough.Ever since I managed to override feelings of self-pity and betrayal, ever since I managed to entertain friends and lovers foolishly smiling, ever since the spectacle (all smiles) guaranteed success (yes, I could fit in!), I wished for a sister, a blood relative, who accepted me as I was-smiles, or no smiles.Ever since I understood the medicinal effects wild flowers had on moods, I understood I could never be healed no matter how
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.038 | 0.016 |
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".