Bibliographic record
Abstract
A crumbling infrastructure, and: Clichés are clichés for a reason John Emil Vincent (bio) Keywords Prose poetry, John Emil Vincent A crumbling infrastructure I had too much computer. And a bad case of quaint. Such as it was, time stood still and there I was with someone seemed half my age and less a quarter my hygiene. We walked to Emily Dickinson's grave. We held hands; he said his fingers were empurpled from picking kale in deep frost. I found that twee. In an adorable way. We did all the things two boys can to celebrate the failure of language. Twice. And then, embarrassed, we stank of each other. Me more. I affectionately called him goat boy. But never to what I remember of his face. [End Page 755] Clichés are clichés for a reason When the Sasanian king learned that the poor could not afford to listen to music, he gathered the then ten-thousand known lute players and gave them each an ox, a donkey, and a donkey-load of wheat. With this small self-sustaining fortune, they would wander the countryside plucking and playing and maybe even now and then dancing. However, the lutists summarily gobbled up the ox and the wheat and rode back to the king on ten thousand near-dead donkeys. The king was understandably angry. But don't believe what history says about him. He did not banish them to wander the earth. No. Instead he calculated a little and knowing they each still had a lute slung on their backs, he sent them away, telling them in real serious king voice that he wasn't mad, just disappointed. He suggested, disappointing as they were, that they would never find a home and never be full-bellied and always be outsiders. And they'd forever hang out on the edges of local fairs with rickety rides. This was a totally fucking brilliant king. Now with ten thousand poor, but mostly just dispirited, lutists, the poor would hear good, truly sad music from then to now even, even to right now. Imagine that. While I don't find it exactly laudable I do find it fun to think about. Like so many smart things, there is however a kind of discomfort once it reaches a certain level, and you'd prefer the smartypants just dial it down, and your friend just shut up cuz they are saying everything they think about you in a puppet play and not really leaving the ugly actual puppet-themed bits out even though you'd think they would do that instinctively. But no. And then they go on and on about how everything is hidden in plain sight and how look at him over there he's simply exactly what he is and isn't that a treat. And you could certainly take a page out of the King of Sasania's playbook and quote unquote banish this dipshit friend, even this loved one, [End Page 756] perhaps even "a squeeze" as they say, to a world where they are sure they must wander unloved, unknown, poor, and cold sometimes, with no ox, no donkey, or a skinny, beaten, near-dead donkey, and nothing but their own smart instrument on their smart but very ribby back. And say, hey friend, the part of me that's stupid's intimidated by your articulate sorrow. And the smart part, tired of your dumb voice. But, go on, strike a chord. My meat part will listen. [End Page 757] John Emil Vincent john emil vincent lives in Montreal. His first book of poems, Excitement Tax, drops soon from DC Books. Copyright © 2017 The Massachusetts Review, Inc.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.064 | 0.030 |
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".