Fiction as Research Practice: Short Stories, Novellas, and Novels (2013) by Patricia Leavy
Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
In the first section, Patricia Leavy explores the genre by explaining its background and possibilities and goes on to describe how to conduct and evaluate fiction-based research.In the second section of the book, she presents and evaluates examples of fiction-based research in different forms including short stories and excerpts from novellas and novels written by different authors.The third and final section explains how fiction and fiction-based research can be used in teaching.Leavy clearly differentiates the term fiction-based research from artsbased research in order to project the emergent field in a clear light of its own.Babbie (2001) explains that just as qualitative research practice emerged as a means of explaining phenomena that could not be captured by quantitative scientific research, social research attempts to study and understand everyday life experiences.Within social research, arts-based research tries to represent phenomena studied aesthetically through various forms of art (Barone & Eisner, 2012).As a form of arts-based research, Leavy describes fiction-based research as a great way to explore "topics that can be difficult to approach" through fiction (p.20).Topics include the intricacies of interactions in everyday life, race relations, and socio-economic class and its effects on human life.In carving its niche in social research, Leavy explains that fiction-based research seeks to create a deeper understanding of experiences in a language that is more accessible to people than research published in academic publications.Using fiction creates an opportunity for the writer to simulate the environment, sights, sounds, and smells of reality virtually, which captivates the reader's imagination.The writer is able to either create new knowledge for the reader or "disrupt dominant ideologies or stereotypes" (p.38).As traditional qualitative researchers, fiction writers engage in intensive research to ensure that they have clear representations of the phenomenon they are presenting.These representations are evident in the realistic scenarios and characters that are portrayed in fiction writing, allowing the reader to be absorbed in the reality of the book.This reality or verisimilitude is the key to effective fictionbased research and traditional qualitative research because both methods try to portray the experiences as true as possible.In describing how one conducts fiction-based research, Leavy compares tenets of qualitative research to those of fiction-based research.She points out that anticipated data is a key consideration in most qualitative research methods but how data is collected, where it is
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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 | 0,014 | 0,089 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 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 découle