A very fair comparison of the relative condition of farmers in New York State and the Province of Ontario.
Notice bibliographique
Résumé
The CONCLUSION ARRIVED AT:" From all we could learn we found that farmers in Jefferson and St. Lawrence Counties, where we visited, pay as much or more for what they have to purchase and get no more for the produce they have to sell than do farmers in the County of Leeds.We also found that they are not any more prosperous, and from all we could gather are more heavily mortgaged than farmers in the County of Leeds.We also found that well improved farms of the very best of soil, free from broken lands, and lying within from two to ten miles of the city of Ogdens- burg, as well as in other localities where we made enquiries, can be purchased much cheaper than lands of the same quality with same improvements similarly situated in the County of Leeds ; that lands have depreciated in value more in the last ten years in St. Lawrence and Jefferson Counties than similarly situated lands in the County of Leeds."During the last session of Parliament the position of the Canadian farmer as compared with his brother farmer in the United States attracted a good deal of attention, especially with respect to the articles of binder twine and coal oil-the duty on both of which articles was materially reduced by the Government.The general contention of the Opposition was, in effect, that the operation of the National Policy was to increase to the farmer the cost of those articles he was obliged to purchase, and to lessen the prices which he could obtain for the farm and other articles he pro- duced.It was further argued by Sir Richard Cartwright and other Opposition orators that the value of the farm lands had greatly declined on account of the adop- tion of a Protective policy in 1879 ', that mortgages had increased ; that the general condition of the farmer in Canada was worse than it was in the United States, and that the only remedy for such a state of things was closer trade relations with the United States, whereby the Canadian farmer would have access to their " market o2 31.
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) | 0,000 | 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 ».