Language in the Public Space of a Dalmatian Town: The Linguistic Landscape of Zadar
Notice bibliographique
Résumé
The objective of this paper is to analyse and describe the linguistic landscape of Zadar. Zadar is one of Croatian towns that have been parts of different socio-cultural and administrative entities throughout several millennia of their history. In its history Zadar was also the final destination of many migrants and immigrants. Because of these facts, Zadar has almost always been a multilingual town and its contemporary linguistic ecology (although slowly changing) is one of the most interesting ecologies in Croatia, because of the existence of several Croatian dialects, regiolects and standard languages (Brozovic, 1976). In this paper I will present the results of the analysis of the linguistic landscape of Zadar. The analysis will be based on methodology used in previous research on linguistic landscape (Backhaus, 2007 ; Cenoz and Gorter, 2006 ; Gorter, 2006 ; Jaworski and Thurlow, 2010 ; Franco Rodriguez, 2009 ; Shohamy et al., 2010 ; Shohamy and Gorter, 2009). However, most of previous research on linguistic landscape was conducted in towns and cities comprising rival ethnolinguistic communities actively participating in the symbolic construction of public space with their choices of language on signs (cf. linguistic landscapes of Jerusalem, Montreal, Brussels, Tokyo, Rome, San Sebastian, Bangkok, and other). In Zadar, on the other hand, several ethnolinguistic communities exist (with varying numbers of members), but the results will show that the linguistic landscape does not display elements of rivalry between them. The methodology used in this research is similar to methodologies used in previous studies of linguistic landscape. The elements of linguistic landscape (Backhaus, 2007) will be photographed with a digital camera on five locations in the town (quarters Arbanasi, Poluotok, Vostarnica, Relja, and Puntamika). These locations are chosen because they contain numerous religious, administrative, municipal, educational, and juridic institutions, which is the reason why all citizens of Zadar must at some point pass through these quarters and experience the linguistic landscape. The photographs will then be analysed according to standard procedure developed by previous researchers (explained in detail in Backhaus, 2007). However, most previous studies of linguistic landscape have only taken into account the texts on the signs and the frequency of languages, but have forgotten authors and the ideological processes behind the authors' decisions. In this paper, the results will also incorporate the qualitative data collected in interviews with people actively involved in the production of signs in public space and people who are active consumers of these signs, i.e. the passers-by. These qualitative data will hopefully provide an insight into different ideological aspects of the production of language in the public space.
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 | 0,001 | 0,003 |
| 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) | 0,002 | 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 ».