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Record W2293525928

The Missing Kidney

2016· article· en· W2293525928 on OpenAlexaboutno aff
Maxine Rosaler

Bibliographic record

VenueSouthern review/˜The œSouthern review · 2016
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsnot available
Fundersnot available
KeywordsHarmDreamDirtArtArt historyMedicineHistoryPsychoanalysisPsychologySocial psychology
DOInot available

Abstract

fetched live from OpenAlex

When I was twenty-two years old, I had to leave Montreal, where I was in love with Steven Tomlinson, to go back to New York to have one of my kidneys removed. I had mentioned in course of a routine checkup at McGill University clinic that I peed a lot; doctor tested my urine, one thing led to another, and it was discovered that my right kidney was diseased and shrunken and doing me more harm than good. Steven was my first real boyfriend, first boy I loved and first boy who loved me. Once, he told me with tears in his eyes that he would love me even if I lost an arm; he would love me if I lost a leg; and now he could add a kidney to list of missing body parts whose elimination would in no way alter his love for me. The night before I was to leave for New York, Steven shook me awake at three in morning to tell me that he had had a dream that I wouldn't be coming back to Montreal. He made me swear that I would never leave him. We had vacated apartment we'd been sharing for past six months and were camping out on living room floor of a friend of his, in a sleeping bag that smelled like dirt of creation. I promised that I would come back as soon as I recovered from operation, but I knew I was never coming back; I also knew that I would never find anyone to love me as much as Steven did. My mother referred to Steven as the goy boy, a name she had come up with to belittle him, which was something she had always done, one way or another, with all my boyfriends. I always thought that goy meant Christian, and Steven had been brought up as an atheist, but looking at him through my mother's eyes, there did seem to be something very goyishe about his family--the parents were divorced; father, whom I met one night when I went with Steven to his house for dinner, was an ice-cold professor of experimental psychology; and his third wife, Paula, epitomized a certain kind of Wasp wife. She was a timid, nervous sparrow of a woman, who kept on looking anxiously at her husband, seeking his approval for meal, which must have taken hours to prepare, and which I was incapable of enjoying, my extreme discomfort in presence of Professor Tomlinson having robbed me of all appetite. The one distraction from my own unease that evening was Steven's: his green eyes were clouded over with something I had never seen in them before--a fierce look of self-protectiveness, so different from open and, for me, slightly unsettling look of adoration that I was accustomed to seeing shining in them. The conversation around dinner table consisted of professor asking me questions and me answering them at much greater length than was necessary. When he asked me what my father did for a living, for example, I didn't simply tell him that my father was director of advertising for a small import/export company in Manhattan, I told him that my father hated his job and that he had always wanted to be an English professor but when he was at Columbia University, where his father, a millionaire who was first Jew with a seat on New York Curb Exchange and who had lost all his money in stock market crash of 1929, was on board of directors, dean told my father that Jews couldn't get jobs as professors and so that's why he ended up being in advertising, which was a shame, since he would have been a wonderful English professor; he was a very literary man. Next, Professor Tomlinson asked me how I happened to come to McGill. It was kind of serendipity, I told him, and in one long, run-on sentence I spoke of my nomadic college experience: first, University of Wisconsin, which I hated, except for cold weather (I liked way it would make tiny icicles form in my nose and I liked frozen look of everything); then, my transfer to Harpur College, where in place of goofy-looking Midwesterners, I found neurotic New York Jews; and finally, my decision to transfer to McGill because a girl waiting in line with me at Harpur College cafeteria, where food was inedible except for cinnamon doughnuts, which were fabulous (why had I used that ridiculous word? …

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0280.007

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 head0.020
GPT teacher head0.289
Teacher spread0.269 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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
Published2016
Admission routes1
Has abstractyes

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