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Enregistrement W4401390730 · doi:10.5325/hungarianstud.51.1.0001

Introduction to the Special Section on Transcarpathia

2024· article· en· W4401390730 sur OpenAlexvenueno aff
Péter Balogh

Notice bibliographique

RevueHungarian Studies Review · 2024
Typearticle
Langueen
DomaineArts and Humanities
ThématiqueAncient and Medieval Archaeology Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSection (typography)Special sectionHistoryComputer scienceEngineeringEngineering physicsOperating system

Résumé

récupéré en direct d'OpenAlex

The tragic events unfolding in Ukraine over the past decade have understandably triggered considerable scholarly attention to that country. Yet despite Ukraine’s rich internal diversity, the focus is often on national or interstate relations. A recent roundtable on Hungarian-Ukrainian relations in the Hungarian Studies Review (vol. 49, no. 2) is a case in point, with only one out of the six contributions specifically dealing with the subnational level—namely with the region of Transcarpathia (since 1946 called Zakarpattia Oblast).1 We believe that region merits more attention generally and in this journal for at least three, interrelated, reasons. First, Ukraine’s westernmost oblast borders Hungary and hosts a considerable, though shrinking, ethnic Hungarian minority. Second, as the authors here convincingly show, Transcarpathia is a particularly rich terrain for studying interethnic relations, including but not limited to Ukrainian-Hungarian ties. Last but certainly not least, the status and rights of the region’s ethnic Hungarians are often referred to as a key factor in the recently deteriorating relations between Hungary and Ukraine.2Hence, we believed it was worth presenting our ongoing research on interethnic issues in Transcarpathia at the 2022 ASEEES Annual Convention. Organized by Árpád von Klimó, our session was titled “Hungarian-Ukrainian Borderland Questions: New Research” and chaired by Paul Hanebrink, with the author serving as discussant. Three papers were presented, and their revised versions now constitute the bulk of this special section. While one of the articles deals with a more distant period, the remaining two focus on much more recent times, namely the years between Russia’s partial occupation of Ukraine in 2014 and its full-scale invasion in 2022. That period saw growing economic and political asymmetry between Hungary and Ukraine.3 Not unrelatedly, it also saw a sharp increase in Hungary’s financial and political support of its ethnic kin in Transcarpathia and the curbing of minority language rights in Ukraine.4John Swanson’s historically focused article is rather unique also in a methodological sense. While even historical studies of everyday multiethnic cohabitation typically rely on qualitative sources (such as diaries or newspaper reports), his contribution builds on statistical data on a small Transcarpathian town, Bilke. The fact that the area has repeatedly switched state affiliation over the period studied—the first half of the twentieth century—is not necessarily to the researcher’s disadvantage, as different types of data are thus available. In this case, beyond official census data (which often recorded ethno-religious identification or native language), Swanson makes use of school records and cadastral maps. Comparing these different data for the very same individuals (in this case a Jewish girl and her family) has enabled him to identify their social and spatial mobility patterns (movements, segregation, etc.) over time.Katalin Kovály’s article takes us to much more recent times, namely to the period 2017–20, during which Hungary’s kin-state aid to Transcarpathia experienced its peak. She is interested in how that and other dynamics have influenced the role of formal and informal ethnic capital among economic actors in Berehove Raion (district), which until recently had an ethnic Hungarian majority. To learn about these effects, Kovály has primarily conducted interviews with local entrepreneurs and representatives of business organizations. While these actors may already previously have relied on ethnic ties informally, she found that among the region’s Hungarians the role of formal ethnic relations has increased, largely due to Hungary’s financial support (which is mostly channeled through formal institutions). This has put them in a more advantageous position vis-à-vis their Ukrainian competitors, which has become a source of tension between the two groups.Ágnes Erőss’s contribution fills a gap by focusing on immobility in a region that is otherwise typically studied for its salient (e)migration patterns.5 Since 2016, she has conducted fieldwork among Transcarpathian Hungarians mainly in rural peripheries, finding that mobility and immobility patterns are often intertwined with family strategies. As such, these patterns heavily impact, and are heavily impacted by, generational and gender dimensions. Additionally, they are also affected by individuals’ possession, or lack thereof, of the citizenship of the kin state (in this case Hungary) and their geographical distance thereto.This small collection of articles on Transcarpathia aims to contribute to the study of local Ukrainian-Hungarian relations and, more generally, of ethnic ties in the borderlands of Hungary and beyond. The future of Ukrainian Hungarians will depend on how long the full-scale war lasts, but despite their initial exodus, in 2022 at least Transcarpathians were reported to move back and forth between their homes and Hungary.6 Should those patterns of mobility and immobility be sustained, the region is likely to play a role in Ukrainian-Hungarian relations in the future as well.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,343
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,001

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.

Tête enseignante Opus0,064
Tête enseignante GPT0,300
Écart entre enseignants0,236 · 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
GenreSynthèse

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

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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