Notice bibliographique
Résumé
It has been my hope that this thesis would serve as a bridge between three things: my past wilderness experiences, my present explorations of great nature poets, and my future as a writer. I desired to write authentic wilderness poems that gave readers new experiences, yet I was afraid that they might not be broad enough in scope and have too much sentimentality to be effective. To find a path through this dilemma I looked to great nature poets, both American and Canadian, as I sought to see how they were such successful writers. In looking at their work I asked many questions. Where did they get their inspiration? Did they use experiences or did they just write creatively? How did they talk about their past effectively? Did "place" play a large role in what they wrote about? The act of writing poetry often feels like a solitary task, as if no one has ever written like you have before, but as I searched the lives of poets I found a companionship and association that was inspiring. Looking at Margaret Atwood, for instance, gave me courage to keep alive the memories of when I was a small child in British Columbia, for she herself wrote about her own childhood experiences. John Haines was another poet who contributed to my writing process. He was not someone who simply experienced nature in his childhood. He was a man who sought it out as an adult and excluded civilization from his life. The end result of my thesis was more than I hoped for. Just by learning from great writers I was able to write boldly about my past, and I found that intertwined in my memories were people that shared those experiences with me, and they too added to the depth of my poems I call "Canadian Wild."
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 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,002 |
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 ».