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Enregistrement W3019450620 · doi:10.21301/eap.v15i1.5

The Novel “Snowman” by David Albahari. A Socio-Anthropological Reading

2020· article· en· W3019450620 sur OpenAlexaboutno aff
Marija Brujić

Notice bibliographique

RevueEtnoantropološki problemi / Issues in Ethnology and Anthropology · 2020
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueBalkans: History, Politics, Society
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTrilogyDiasporaImmigrationSociologyReading (process)EmigrationHegemonyBiographyAnthropologyHistoryGender studiesArt historyLinguisticsPolitical sciencePhilosophy

Résumé

récupéré en direct d'OpenAlex

In this paper ideas of literary anthropology that legitimize research of fiction work in socio-cultural anthropology are combined with the theories and methodologies of migration studies. Novels can be used as a source for understanding and interpreting certain phenomena from our socio-cultural reality and be an object of research. Therefore, this paper analyzes the novel Snowman (1996) by David Albahari from his so-called “Canadian Trilogy”. It is his first novel after his emigration to Canada from Serbia in 1994. This paper aims to draw attention to the possibilities and potentials of anthropological analysis of Serbian literature that originated in Canada as one of the possible strands of literary anthropology. Is a prerequisite for successful integration of the first generation of immigrants good competence in the foreign language, a prestigious and well-paid job, and higher education? The answer to this question can contribute to a better understanding of the fictional representation of migrants and be useful in anthropological studies of contemporary migrations. To test this hypothesis, we have juxtaposed the novel “Snowman” with Albahari’s collection of essays “Diaspora and other things” on the life of immigrants in Canada based on the author's personal experiences and experiences of his co-nationals in Canada, and working biography of the author. Furthermore, we test Robert Park’s concept of the “marginal man”. While researching American Jews, Park concluded that they are “men on the margin of the two cultures” and that “marginal men personality” is a “cultural hybrid”, developed as a reaction to life in new surroundings. Finally, in the analysis section Milton Bennett’s method “developmental model of intercultural sensitivity” is used. Bennett’s model consists of six stages: denial, defense, minimization (first stage) and acculturation, adaptation, integration (second stage) and can be applied for the purpose of interpreting immigrants’ experiences in a foreign society. The main character of the novel “Snowman” is a writer from a small European country which is at war. He got a job at a university in a faraway northern non-European country and speaks their language fluently. However, he is nostalgic and homesick, feels misunderstood among his new colleagues and his new life seems to him hopeless. Finally, overburdened with all these emotions, he succumbs to heavy snowfall. Previous research of working migrants suggests that incompetence in the language of the country of residence, a low paid and unskilled job and low level of education are the main factors for their low level of integration. On the other hand, using the example of the educated main character from the novel, this paper shows that adaptation, integration, and positive emotions, such are pleasure and happiness, do not have to correlate with the level of education, language competence, and prestigious employment in a foreign country. In other words, the protagonist of the “Snowman” did not want to develop intercultural sensitivity. Therefore, we propose that migration studies should research not only what migrants do and how they behave but how they feel in their new surroundings. In this respect, migration literature with biographical elements may serve as an important source for this kind of research.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Études des sciences et des technologies, Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesÉtudes des sciences et des technologies
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,879
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0040,041
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,037
Tête enseignante GPT0,361
Écart entre enseignants0,325 · 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2020
Routes d'admission1
Résumé présentoui

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