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Record W2906095546 · doi:10.1353/ner.2018.0112

Borders and Crossings

2018· article· en· W2906095546 on OpenAlexaboutno aff
Douglas Silver

Bibliographic record

VenueNew England review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsnot available
Fundersnot available
KeywordsOutrageWhite (mutation)Art historyArtHistoryLawMedia studiesVisual artsPoliticsSociologyPolitical science

Abstract

fetched live from OpenAlex

Borders and Crossings Douglas Silver (bio) The switchboard lamps flash to life every hour on the hour, coinciding with the radio newscast. Americans are calling to speak to President Truman, to Vice President Barkley, to Secretary of War Patterson. Instead they get Operator #9, Genevieve Higgins, who answers with a sprightly "White House, how may I direct your call?" and then incurs a litany of grievances. They are angry about rocketing inflation, about Soviet rockets, the price of eggs, the cost of war. A man from Biloxi fumes over a Negro baseball player debuting for the Brooklyn Dodgers' farm team in Montreal. One surly woman, convinced The Postman Always Rings Twice harbingers a Communist invasion, is aghast when Genevieve tactfully declines to patch her through to the leader of the free world. "Next time you see Harry Truman," she says, "tell him Betsy Mare from Knoxville thinks he's just rotten." The woman's outrage is comical, much like her delusion that Genevieve and the president are acquaintances, that perhaps the message will be relayed during lunch-hour chitchat or hallway pleasantries. The dirty truth about the White House operators is that they don't work in the White House. They—Genevieve and eight other women, all her senior in both age and rank—are installed next door, seated at a wall-length console in an otherwise cramped subbasement of the Executive Office Building. This remove from the Oval Office has in no way discouraged her mother from crowing to the housewives at church group—specifically those whose sons are single and gainfully employed—embellishing her daughter's function of screening calls and plugging jacks to an appointment behooving Senate confirmation. One such housewife, a Mrs. Coleman, new to the church, takes the bait. Her son is a police officer. Prior to that, he was an Army private first class who assailed the beaches of Normandy. His name is Walter and, Genevieve's mother informs her, he will pick her up on Saturday evening. ________ Walter Coleman is husky, with an overbite like a ship's prow and, fittingly, a sodden voice that gurgles as if a lozenge were perpetually dissolving on his tongue. He opens the car door for her, the soda fountain door, waits for her to sit first, insists on paying for their ice cream before she has the chance to offer. His manners are mannered, as if he were adhering to a primer on dating etiquette. To Genevieve's amazement, she finds this endearing. Less so that he prefaces most statements with My mother told me . . . : "My mother told me you [End Page 68] sing like Billie Holiday"; "My mother told me you have a secret recipe for the best apple cobbler in the world"; "My mother told me you talk to the president all the time." Of course, Genevieve doesn't know Walter's mother from a sack of potatoes. He is merely reiterating the extravagant biography her mother fed his mother, an approach Genevieve reciprocates, their conversation more like decryption, translating the puffery of their mothers into the brass tacks of each other. As such, Genevieve clarifies that she sings along to Billie Holiday, that the secret behind her apple cobbler is that she lifted the recipe from a Betty Crocker cookbook, that only Mrs. Burston (Operator #1) and Mrs. Reynolds (Operator #2) deal directly with the president. None of this deters him. He, too, likes Billie Holiday. He, too, likes Betty Crocker. He voted for Harry Truman but hoped the president would've accomplished more by now. "I'll pass along your disappointment," she says. "No need. I haven't given up on him yet." Genevieve isn't sure if he is mirroring her sarcasm or oblivious to it. Either way, she is grateful when Walter slurps the last fudgy puddle of his sundae and they reverse course to her house. He escorts her to the door. In the dark his features seem less pronounced, the shadow chiseling his jawline. She thanks him for the wonderful night. "Maybe next time we'll go to a movie," he says. "My mother told me you have a real thing for Cary Grant." "He's...

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.034
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0170.037
Scholarly communication0.0150.017
Open science0.0010.011
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0340.005

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 head0.018
GPT teacher head0.346
Teacher spread0.328 · 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 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
Published2018
Admission routes1
Has abstractyes

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