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Enregistrement W4393225686 · doi:10.1353/ner.2024.a922920

A Theory of History

2024· article· en· W4393225686 sur OpenAlexaboutno aff
Nathan Curtis Roberts

Notice bibliographique

RevueNew England review · 2024
Typearticle
Langueen
DomaineArts and Humanities
ThématiquePhilosophy, History, and Historiography
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHistory

Résumé

récupéré en direct d'OpenAlex

A Theory of History Nathan Curtis Roberts (bio) Explore, expand, exploit, exterminate. This was how Oliver Hall passed his time during quarantine. He'd fallen off the wagon with unexpected force, and he'd been off it for eighteen months, living in his late father's unlivable hovel in South Salt Lake, surrounded by empty bottles, aggregating 520 days of headache and heartburn and hangover. He started drinking to mourn the end of his friendship—and working relationship—with Daniel Erlich, a famous artist and filmmaker. He continued drinking because that's how it usually went with drunks, though this was a special kind of bender, the kind you don't expect to come back from. In March of that year, pandemic arrived as the grim late-winter snow melted. And earthquakes shook Utah. And Oliver felt the same uncertainty everyone everywhere was feeling. But being a contrarian—one who didn't believe the universe had any guiding intelligence in its design but did think it had a darkly hilarious wit—he decided to sober up. While all the other drinkers in that largely dry state stood in three-block-long social-distanced lines to purchase enough booze to last until the end of days, Oliver Hall abstained. He knew what to expect. The days of shaking, the nights of sleeplessness, the weeks of startling at every unexpected noise. He searched the app store for a diversion to occupy him through the worst of it. And this was what he found: explore, expand, exploit, exterminate. It was a game about conquering neighbors, trading and hoarding resources, and doing puzzles that weren't really puzzles so much as lining up colors and watching them cascade randomly to the bottom of the screen. He could watch the cascading colors for hours on end. But sometimes he watched YouTube videos. He was especially interested in watching triathletes do their sports and discuss their training. There was a Canadian who was popular on the platform, himself a recovered addict; his upper body was lean almost to the point of scrawniness, and his ass was a perfect muscular globe; he had a movie star chin and jaw, which fit awkwardly but appealingly with his goofy smile; and this triathlete had remarkable endurance not only for athleticism, but for looking into a camera and describing his regimen minute by minute, number by number, week after week. It was as inspiring as it was lulling, and it got Oliver to start running again. And there was Twitter. He didn't participate, but he observed. For no good reason—certainly no reason he could have explained—he kept separate accounts for every interest. One for following visual artists, one for politics, and one for witty gays [End Page 20] who lived for the rare occasions when someone compared them to Oscar Wilde. This was how Oliver spent his pandemic. He went to a behavioral health clinic where everyone was well-intentioned and no one was well-credentialed. (This suited Oliver: for multiple myeloma he would have preferred well-credentialed, but for addiction and major depressive disorder, well-intentioned were where it was at.) He ran and cycled. He played his phone game. He did a lot of "doomscrolling," as everyone on the platform was calling it. And that was how he discovered Simon Abeles, a labor economist with a sense of humor and a handsome man for a profile picture. Simon started showing up in all three of Oliver's feeds—art, politics, gays. He was intimidatingly smart, a genuine polymath, as knowledgeable as if he had a team of researchers just for tweeting. His jokes were a little effortful, and they occurred at clockwork intervals, as if he had them scheduled so that he would occasionally seem human. But he spent most of his time excoriating his enemies in 280-character salvos, fighting with strangers, and calling his more conservative colleagues world-class idiots. Simon Abeles was brilliant, he was beautiful, and he was belligerent. Like the Canadian triathlete, he had a movie-star jaw and a goofy smile. He was also local, which was probably why his tweets showed up so often in Oliver's feeds...

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,017
Score d'incertitude au seuil0,059

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,004
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0030,003
Études des sciences et des technologies0,0050,032
Communication savante0,0100,018
Science ouverte0,0020,004
Intégrité de la recherche0,0030,004
Charge utile insuffisante (le modèle a refusé de juger)0,0170,003

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.

Tête enseignante Opus0,047
Tête enseignante GPT0,228
Écart entre enseignants0,181 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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