Notice bibliographique
Résumé
Portrait of the Technocrat as a Stanford Man Shaan Sachdev (bio) The first time it snowed this year, I cried. Snow is one of my favorite things in the world—and it’s one of the Stanford man’s, too. He was surely trekking through it as well, somewhere in downtown Brooklyn. But unlike me, trudging mournfully to my office in the same pair of jeans I’d worn all week, the Stanford man would be crunching through the ice and salt in top-of-the-line hiking boots and a $1,900 jacket. He’d be filtering the flakes through fleece-lined leather gloves from Burberry and then returning to his glass apartment on the fortieth floor of a luxury building to shower with Molton Brown soaps. He’d greet the doorman on his way in, one of six, and it wouldn’t matter which was on duty, because he’d know all their names. He’d make cordial conversation with whomever was in the elevator, the trim blond pushing the stroller or the paunchy techie with the Labrador, because exchanging pleasantries is also one of his favorite things. When the Stanford man broke up with me, he told me it was because he needed to date someone more “average.” He told me that intellectualizing and reading tomes were for graduate school, not the stuff of romance. He told me that ordinary pleasures, like watching basketball and dancing to thumping techno, were to be savored, not scrutinized. He reminded me, I realized, of Jim Barnett, the subject of Mary McCarthy’s “Portrait of the Intellectual as a Yale Man,” from her 1942 novel The Company She Keeps. “If other people on the left stood in superstitious awe of Jim,” McCarthy wrote: Jim also stood in awe of himself. It was not that he considered that he was especially brilliant or talented; his estimation of his qualities was both just and modest. What he reverenced in himself was his intelligent mediocrity. He knew that he was the Average Thinking Man to whom in the end all appeals are addressed. . . . He was a walking Gallup Poll, and he had only to leaf over his feelings to discover what America was thinking. Like Jim Barnett, who could have been a model if he’d fallen on hard times, the Stanford man is approached now and then by scouts and agents. He is tall, with [End Page 95] a bronze complexion, thick, curly hair, and lips like pillows. He is clean but not in the ordinary, courteous sort of way. He’s so clean that it’s the first thing one notices about him. His skin glows and his clothes are spotless and everything he wears looks new. One can’t possibly imagine any odor wafting from his person. Even after exercising, the fabric of his premium gym clothes seems to, as advertised, absorb all efflux. He brushes five, sometimes six times a day, always for twice as long as the American Dental Association recommends, erasing all evidence of delicately prepared breakfast smoothies, sumptuous tenderloin dinners, and eighteen-dollar craft cocktails. Most evenings, after the Stanford man finishes speaking on conference calls and making spreadsheets on his computer—the things that propel his six-figure salary—he eats dinner with friends. Sometimes with just one friend, sometimes with five. Sometimes he and his roommates prepare fresh poke bowls in their globule above the city, only faintly registering the puny, glittering Statue of Liberty out their living room windows as they chop and chatter. Sometimes he sits at a table in Chelsea with a horde of other twenty-somethings who have also attended Stanford—or Harvard, Princeton, or Yale. They wear silver TAG Heuer wristwatches and dark blue cashmere sweaters, and they mostly exchange anecdotes about things that happened to them in South America or about companies that mutual friends are starting. Serious moments might entail ruminations upon spin class, air miles, stock prices, or cryptocurrencies. None of them, it ought to be said, are unintelligent. In fact, their minds are put to regular labor. They can tell you which health insurance plans come with the best digital applications. They can tell you...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».