Notice bibliographique
Résumé
Billy at the Bat Alan Gordon (bio) The outlook wasn't brilliant for the sabermetrics crowd, Their theories were reviled; their doctrines disavowed, And baseball went on telling us the way that games were won: "The sacrifice, the stolen base, the manufactured run." Through decades of equations, through years of tracking games, From the postulates of Cramer to the premises of James, There seemed but little hope that sabermetrics would prevail, As tears were shed at Harvard, Princeton, MIT, and Yale. They thought, "If only one GM would dare stick out his neck, If only Branch were still alive, if only we had Veeck." But seemingly the scientific push was made in vain, For baseball treated evidence and logic with disdain. But then in '97, in the midst of disrepair, The Oakland A's cleaned house and there were changes in the air, A man named Billy Beane spoke of a new kind of success, And damned if Billy didn't start computing OPS! And statisticians far and wide let out a lusty yell, It rumbled off their charts and graphs and Microsoft Excel, It knocked upon the blackboards and bounced off the almanacs, For Billy, mighty Billy, had read all of James's abstracts. There was ease in Billy's manner as he had base-stealing banned, There was pride in Billy's bearing and a slide rule in his hand, And when he preached the value of the all-important walk, 'Twas little doubt that "old baseball" was in for quite a shock. [End Page 143] GMs and scouts around the league belittled Billy's "math," Ex-players and announcers shared a universal wrath, (Ironically Joe Morgan, greatest critic of them all, Was quite the sabermetric gem when he was playing ball . . . ) But Billy battled on (despite substantial lack of funds), And showed his team the darker side of bunts and hit-and-runs, He had ten words of wisdom for his players who had doubts, "To maximize your runs you have to minimize your outs." He surveyed new statistics as the rest of baseball laughed, He studied trends and patterns of the players he would draft, He traded off his superstars for undervalued scrubs, Unloading hefty contracts on the Yankees and the Cubs. And sabermetric gurus, with a boundless sense of pride, Watched on with vindication as their theories were applied, But deep inside their hearts, there was a single fear that lurked, "It's beautiful on paper, but in real life will it work?" At last Billy's experiment had gotten under way, They fought their way through April, they powered on through May, And all throughout the season Billy tinkered with the team, To squeeze every advantage out of each and every seam. And Oakland won nine more games than they'd won the year before, The next year they went out and won another thirteen more, The onslaught had continued and, refusing to plateau, They made it to the postseason for four years in a row. And baseball's ideology was turned upon its ear, "It takes money to win" had been their axiom for years, But Billy's humble payroll hadn't stopped him in the least, In fact, as Oakland's payroll dropped, their win total increased! And quickly sabermetrics started spreading from the A's, It caught on with the Dodgers and the Red Sox and the Jays, And still the seed is spreading as the old convictions fall, And in ten years the whole league will be playing "Moneyball." [End Page 144] Through baseball's evolution we've seen eras come and go, We watched the dead ball disappear and batting average grow, We marveled at the farm system that Rickey had revealed, We watched as night games swept the land (except at Wrigley Field). We've seen a lot of eras, some imperfect, some ideal: The era of free agency, the era of the steal, The pitchers age, the hitters age, the age of the home run, Now thanks to Billy Beane the age of reason has begun. Alan Gordon Alan Gordon is a graduate student at the University of Southern California School of Social Work. He has also...
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) | 0,010 | 0,001 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».