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Wash That Man Right Out of My Hair

2018· article· en· W2908814368 on OpenAlexaboutno aff
Hotchandani

Bibliographic record

VenueFeminist Studies · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican Political and Social Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsArtArt historyMythologyVisual artsLiterature

Abstract

fetched live from OpenAlex

Carolina Hotchandani 633 Wash That Man Right Out of My Hair Now it happened that Metis was going to have a daughter, and she sat inside Zeus’s head hammering out a helmet and weaving a splendid robe for the coming child. Soon Zeus began to suffer from pounding headaches and cried out in agony. All the gods came running to help him, and skilled Hephaestus grasped his tools and split open his father’s skull. Out sprang Athena, wearing the robe and the helmet, her gray eyes flashing. Thunder roared and the gods stood in awe. —from “Athena,” in D’Aulaire’s Book of Greek Myths, 1962 I’ve never met the doctor who happens to be on call when I go into labor. A sweet-smelling aftershave precedes him into the delivery room. We’re gonna get that baby right out of you, he says, pulling a latex glove over one hand and stretching the opening wide so it snaps back with a loud smack against his wrist. I want those hands nowhere near me. I imagine him coaching little league, tapping his baseball cap to send signals to tiny players in the outfield. He chews gum for the entirety of my labor. After I push with all my might for three and a half hours and the baby has still not moved, he says with a half-wink, Poor thing. You’ll be so sore when this is all over. The baby’s been out of me for a while now, but that man is still inside. I go over what happened again and again, desperate to find the angle through which he exits the scene and stays gone. He sees himself from the outside: a hero who enters the scene in medias res, scenting the room with sweet nectars. He will stop in, introduce himself , smile his neighborly smile, before he sets off on a journey through the hospital. Doors will open, doors to women splayed on beds. Women 634 Carolina Hotchandani writhe; women scream in pain. Some will be monstrous—Scyllas and Charybdises among them. Their wounds will gape. Their wombs will pull against his virile strength. They hold the center of the earth within them; theirs, the blood of the wine-dark sea. Do not waver; do not let their currents steer you. Skate above the dark waters. Wait to come through the door till they quake, till they halve. Stand back till they split in two. Then sew them up, and it’s you, it’s you who’s made them new! Pull that man right out of my head. Let me be Zeus on this hospital bed. ...

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)0.000
metaresearch head score (Gemma)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.333
Threshold uncertainty score0.952

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.3330.127

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 head0.069
GPT teacher head0.307
Teacher spread0.238 · 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 designQualitative
Domainnot available
GenreEmpirical

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
Published2018
Admission routes1
Has abstractyes

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