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MIGRACIJE MUSLIMANA IZ ZAPADNE BOSNE NA PODRUČJE BANIJE I KORDUNA U SOCIJALISTIČKOM PERIODU I VJERSKO ORGANIZIRANJE VJERNIKA ISLAMSKE VJEROISPOVJESTI U SISKU I NA KORDUNU // MUSLIMS MIGRATIONS FROM WESTERN BOSNA TO THE BANIJA AND KORDUN AREA IN THE SOCIALIST PERIOD AND THE RELIGIOUS ORGANIZATION OF MUSLIMS IN SISAK AND KORDUN

2019· article· en· W7020853028 sur OpenAlexaboutno aff

Notice bibliographique

RevueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueBalkan and Eastern European Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésImmigrationQuarter (Canadian coin)PopulationBosnianDisplaced personFront (military)RefugeeNorth west
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Muslims began to arrive in the area of Sisak and Kordun in a larger number only in the sixties of the twentieth century. Most of them came to Sisak from the West Bosnian municipalities of Bosanski Novi, Bosanska Krupa, Cazin, Velika Kladusa, Prijedor, Bosanska Dubica, while they came to Kordun mainly from the areas of Velika Kladusa and Cazin. Displacement into an urban center like Sisak in a labor camp in Capraga was a completely different character since settling in the rural zone between the Black Stream and Katinovec in the north and the Masina in the south (more than 50 kilometers distance). Sisak-based workers from western Bosnia came to Sisak for employment, while the Greater Cold and Cazin Muslims settled in Kordun mainly due to overpopulation in the zones in which they lived. The life rhythms of each other differed greatly. Metallurgical workers had permanent incomes, lived in specially built buildings mixed with other workers to those who had other religions and nationalities. The standard of living for all the workers in Caprago was much more equal, and despite religious and national differences, immigrant children entered national and religious mixed marriages. In contrast, the Cordon Muslims lived in very closed communities that remained religious and nationally homogeneous. This group, scattered in ten villages and hamlets at a distance and several kilometers from each other, lived mainly from agriculture and livestock, and individuals worked in Slovenia, Austria and Germany while their families lived in Kordun villages. Most of the Muslims who worked abroad were able to earn enough money to build houses not far from their home villages in a given period and thus maintain ties with friends and relatives and have the opportunity to create their own economy. Being engaged in farming and livestock farming, these Muslims lived, according to their own perception, in a fertile land from the land in the Cazin region. There is another big difference between Sisacki and Kordun Muslims. For the last war (1991-1995), the Kordun Muslims experienced an exodus, most often in their native places in western Bosnia, and they mobilized into various armies (from the Army of Bosnia and Herzegovina, through the 'grandmother' to the army of the Republic of Srpska Krajina and the Croatian Army ). Some of them, due to circumstances in which they found themselves during the war in several armies, and those who escaped or were expelled in 1991 captured the stolen, destroyed and burnt property when they returned after Operation Storm in 1995. By contrast, the Muslims of Sisak and its surroundings were very often Croatian volunteers and participated in the defense of their places of residence (eg Mošćenica) and other settlements in Banija and Croatia. Due to their religious and national affiliation, some of them had problems in the Croatian Army, and many did not exercise their rights as Croatian defender in the post-war period. After the war, the Kordun community increased by influx of new Muslims and high natural increase, while the Sisak community largely stagnated stagnated, and has recently been somewhat reduced due to the complete collapse of Sisak Ironworks, or the departure of younger persons abroad to work.

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)0,003
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Communication savante
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,050
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,001
Communication savante0,0020,001
Science ouverte0,0020,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,101
Tête enseignante GPT0,384
Écart entre enseignants0,283 · 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; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
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

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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