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Enregistrement W3130737917 · doi:10.1353/nin.2019.0030

Where I First Learned to Love the Game

2019· article· en· W3130737917 sur OpenAlexvenueaboutno aff
Tim Wendel

Notice bibliographique

RevueNine · 2019
Typearticle
Langueen
DomaineArts and Humanities
ThématiqueThemes in Literature Analysis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésYardBluffBedroomClubNightlifeArchaeologyShoreDirtPopulationGeographyArt historyHistoryArtCartographySociologyFisheryDemography

Résumé

récupéré en direct d'OpenAlex

Where I First Learned to Love the Game Tim Wendel (bio) Somehow Dad cobbled together enough money to buy a modest three-bedroom house with an overgrown yard and bandstand-like gazebo in Olcott, New York, (population two thousand during the summer months). It was a few blocks from the yacht club and the stone-pebble beach near the harbor piers. To the delight of us kids, it was around the corner from George’s Market, which offered a fantasy land of such delicacies as Bazooka Joe bubble gum, Slim Jim sticks and Mrs. Paul’s fruit pies. For kids who had grown up in the country, miles away from the nearest town, Olcott was a bustling metropolis. The village lies on the southern shore of Lake Ontario, thirty-five miles east of Niagara Falls. We had moved there for the summer months so my Dad could sail, both racing and family cruises, sometimes going forty miles across the big lake to Toronto, Canada. Despite its small size, Olcott offered other pursuits, which I soon discovered. To this day I’m not sure why one day I decided to bike up West Main Street, past Jackson Street, turning right on Crescent Heights, which soon became Clinton Street and then West Bluff. The narrow street ran along lake shore, flanked by summer cottages and a few ornate year-round establishments. That first day up here, I was pedaling along the West Bluff when I heard kids yelling and cheering. As I drew closer, I realized it was infield chatter, only heard on a ball diamond. Rolling out to my left, in a sunken field hard by an orchard of dwarf apple trees, kids were playing softball. The field featured plenty of quirks and idiosyncrasies. Home plate had been set up in the far corner, not far from the first row of fruit trees, with the infield made up of weathered bases. Just beyond that regular configuration, left field rose on an incline all the way up the street, where I watched astride my yellow Schwinn bike. Center field was regulation enough, before it rolled downward to the right, falling away all together with a half-foot drop-off that marked some kind of property line. As I watched, one of the older boys, a kid with muscular arms and hair almost as dark as mine, turned nicely on a pitch, pulling it up the left-field hill, toward me. The [End Page 139] infielders watched it soar over their heads and the shortstop, the tallest on the opposing team, ran only a few steps up the hill before letting the ball hit and roll back to him. By deploying such local knowledge, he held the batter to a long single. After three outs, as they changed sides, somebody noticed me up on the street. “You want to play?” somebody shouted. “I don’t have my glove,” I replied. “You can borrow one. C’mon.” I walked my bike down the hill and laid it in the grass beside the other wheels spread far up from the third-base line. “I’m Berg,” said the kid with dark hair about my size. “That’s Danny Clogston and his little brother. And those are the Stein boys out in the field. Go with them. They’re getting killed today.” Somebody tossed me a glove and I pulled it over my left hand, trying to smooth out the pocket so it felt more comfortable, and soon enough everything fell into the rhythm of another game. The next day I convinced my brother Chris to tag along with me. Within the week we were regulars, playing ball on the West Bluff. After dinner, the adults set up lawn chairs on the side of the street and watched our titanic struggles as dusk fell. Even Dad sometimes stopped by on the pretense of making sure we got home okay. So began a string of summers that continued into my late teens, when I left home for good to attend college. Even as we grew older and landed such jobs as lifeguard at the local pool, counselor for the day campers, mowing lawns and painting houses under...

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,508
Score d'incertitude au seuil0,992

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0850,008

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 Opus0,014
Tête enseignante GPT0,223
Écart entre enseignants0,210 · 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

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
Publié2019
Routes d'admission2
Résumé présentoui

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