Exploring the Relationship between Stories from the Land and Character Development
Notice bibliographique
Résumé
The purpose of this research is to explore the relationship between stories from the land and character education, and to examine how the land forms the characters of those who live there.Twenty-seven participants were chosen through the snowball, or chain sampling, method from three groups of people living roughly within the boundaries of Hastings County, Ontario.Three groups of people were included: those living on Tyendinaga Mohawk Territory; generational farmers, whose families had settled in this area; and relative newcomers who have come to the area as recently as twenty years ago and self-identified as coming here in order to be closer to the land.Ages varied, with the youngest participant being 30 years old and the eldest being 94.Each participant was asked to share a story from his or her experience of living with and on the land in this area.During personal and individual visits, stories were conveyed through conversation between the participant and the researcher, and recorded using both audio and video equipment.After transcription, the stories were coded for evidence of character development and reflected upon using three lenses: Noddings (2003) circles of caring; Haig-Brown's (2010) ways through which the land teaches us; and the traditional Ojibway story of the Seven Grandfather Teachings.This reflection process was guided by the notion of close reading of the transcripts, close listening to audio recordings for voice inflection and laughter, and close watching of video recordings for body language.Findings from the research revealed rich connections between the stories and the three lenses used.Every aspect of character development was evidenced in one or more stories.The stories affirmed that, as the elders have traditionally taught, the land moulds people.Those who live in the same area develop character in similar ways.There was no substantial difference shown between the character traits evident in the stories given by Mohawk people and those from the other two groups.Character traits identified were reflective of the
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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 | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 ».