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Record W4362509162 · doi:10.1353/mis.2023.0000

Mother Stay

2023· article· en· W4362509162 on OpenAlexaboutno aff
Jennafer D'Alvia

Bibliographic record

Venue˜The œMissouri review · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFellHeavenHistoryNatural (archaeology)Quarter (Canadian coin)PhenomenonArt historyArtPhilosophyGeologyArchaeologyPaleontology

Abstract

fetched live from OpenAlex

Mother Stay Jennafer D'Alvia (bio) Click for larger view View full resolution Photo by Andrew [End Page 88] It's true what you've heard. There was once a special day when mothers came back from the dead. It happened on a Saturday, so we were all off from work when the mothers floated down from heaven or wherever they had been. At first we were confused. Clumped together and far away, they looked like a giant cloud softening the sunlight. But soon we could make them out: our own dearly departed mothers, and quite alive once more. They fell vertically, like streaks of raindrops on an enormous window, and as their shapes became more and more distinct, we peered up into the sky, trying to find our own. [End Page 89] Of course, it wasn't all the mothers who'd ever perished in the history of the world—that would have been impractical. Only those who'd died in the past year were allowed to come back. I say "allowed," though no one knew how the thing transpired. It may well have been that there was no decision behind it. The mothers might simply have returned as water comes back to the earth in the form of rain. It felt that way at the time, like some kind of natural phenomenon. In any case, some of the ones who didn't get their mothers back became angry; they retreated into their houses with headphones and videos, trying to block out the assault of returned mothers. They were right; it wasn't fair. Still, there was no point in feeling guilty over good fortune. And when my own mother floated down to my front lawn, I wasn't thinking about those others. What she looked like? That's a good question. When I was growing up, my mother was a slim brunette. Then, through the years, she remained thin, while her hair went completely white. But the mother who stepped out of the sun's glare and onto the lawn in front of my house was neither of these ladies; she was a girl of sixteen—exactly half my age—curly-haired and ten pounds overweight. I'll admit, I was startled by my mother's teenage condition. I wanted her back the way she had been—older than I, slender and motherly. When Mom threw her arms around me, the extra teenage chub prevented me from getting the kind of close hug we used to have. She gave a childlike, romantic embrace, as if she wanted everyone in the neighborhood, if not the world, to know how much she'd missed her daughter. I was reassured by the fact that her scent was the same as ever: fresh and doughy. Over her shoulder, I saw my neighbor Pamela Wimple smiling, so happy for me and for herself too. She was holding her newly arrived toddler-mother by the hand. I smiled at her and nodded. It wasn't unusual that my mother had come back as a teen. In fact, the mothers arrived at different ages and in different states of health. Some, like Pamela Wimple's mom, returned as young girls who ran around the yard, while others came back and lay down directly in their hospital beds; they hooked themselves up to IVs and oxygen tanks, then fell in and out of painful sleep. A few even came as young as babies: tiny, maternal infants who needed constant care. I was lucky to have mine back as a teen—to have her at all. In the morning, after her shower, Mom and I sat on the back deck, overlooking the yard. We drank coffee—light and sweet for my mom; [End Page 90] milk, no sugar, for me. Next door, my neighbor was cutting his lawn, and there was a fresh smell of cut grass and gasoline in the air. "Mom, when you were here before," I told her, "I loved you so much. But now you're precious to me." She looked startled by my admission and wary, as if I were expressing a sentiment that she couldn't understand or reciprocate. She smiled...

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.857
Threshold uncertainty score0.204

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0030.003
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.8570.668

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.

Opus teacher head0.074
GPT teacher head0.244
Teacher spread0.170 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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