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Enregistrement W327389671

AG Pulse 2003: Ag Lenders Assess Year Where Good Was Bad, and Bad Was Worse. (Community Banking)

2003· article· en· W327389671 sur OpenAlexaboutno aff
Steve Cocheo

Notice bibliographique

RevueABA banking journal · 2003
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueCooperative Studies and Economics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGovernment (linguistics)AllotmentAgricultural economicsAsideBusinessSet-asideEconomicsAgricultural scienceMarket economy
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

We've lost every one of our young said Gary Canada, president of Bank of England, Ark., historically home to numerous cotton, rice, and soybean producers. when Canada gave his grim report, it was with a difference. England lost these farmers, he said, not to disaster or mismanagement, to a wholly new factor. It's not that they went broke, said Canada. just got tired of it. Canada explained that the modern farmer's paradox--have a bad crop year, make less money, have a great crop year, make even less money because prices become depressed--proved more than these young farmers were willing to cope with anymore. They were young enough to back out and to try to reconfigure their lives. Other farmers in the area, with more years and more resources at stake, hang on and hope. We don't have a money crop right now, said Canada. farmers are just trying to find one that costs them the least to produce. the departure of the young farmers and the unsuccessful search for a profitable crop has brought about something Canada never expected to see--viable farmland simply sitting idle. Not because of a government set-aside or a conservation effort, solely because no one wanted to farm it because it wasn't worth the time and effort. This is the first time we've had land that wasn't farmed, said Canada. Even with the recent farm bill's continued emphasis on federal farm support, Canada said, his producers need still more money out of Washington. Canada, whose bank is $78.6 million in assets, was one of a group of veteran farm bankers who gathered during the recent ABA National Agricultural Bankers Conference. While not all bankers reported the same degree of gloom that Canada did, few had much good news to share. Here's a state-by-state sampling: big story this year has been report Pohlmann, president of $55 million-assets Ravenna Bank in the south central part of Nebraska. While 75% of his market is irrigated and produced well enough, Pohlmann explains, upland crops, not irrigated, were a loss. And cattle has been iffy, to use his words, because producers had to do a lot of early weaning and supplemental feeding due to the lack of readily available forage. In Oshkosh, in the western part of the state, the report was a bit cheerier still worrisome. Mike Jorgensen, president and CEO of $28.7 million-assets Nebraska State Bank, said the local source of irrigation water, a lake, fell 29 feet below normal levels, such were the demands of the area's rain-starved farmers. Dennis Everson delivered his report with a bit of vaudevillian timing--if only the punchline were cause for laughs. We averaged 500 bushels production, deadpanned Everson. A pause, and then he continued. But that wasn't per acre--that was per farm. The drought hit South Dakota too, he explained. It's nothing government money -- and water -- can't cure, said Everson, the existing backstops leave a hole. Crop insurance, for instance, brought stricken farmers a helpful payment for their lost crops, he said, but the payment doesn't quite pay off the bills. Idaho was also affected by the drought, deep wells have provided a critical reserve for producers, according to Terry Hales, loan manager, Wells Fargo Bank, Boise. However, Hales continued, surface reservoirs are nearly empty. There's enough water to carry local crops through to about mid-2003, and after that, there could be trouble. William Wright, whose Banner Bank serves farmers in Washington, Oregon, and Idaho, said the lack of rain throughout the region had left the cattlemen hurting. …

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)0,002
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
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 enseignants0,404
Score d'incertitude au seuil0,850

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,007
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0050,001
Communication savante0,0120,005
Science ouverte0,0010,003
Intégrité de la recherche0,0060,004
Charge utile insuffisante (le modèle a refusé de juger)0,4040,248

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 Opus0,035
Tête enseignante GPT0,244
Écart entre enseignants0,209 · 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.

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
Publié2003
Routes d'admission1
Résumé présentoui

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