The New Wave of Middle Eastern Academic Migration in the 21st Century: Roots and Routes
Notice bibliographique
Résumé
Migration data from receiving countries like the United States and Canada show that Middle East and North African (MENA) international students are one of the fastest growing migrant populations in the 21st century. Focusing on Iran, Egypt, and Turkey, three countries which share many similar historical attributes, this dissertation examines the historical, economic, and sociopolitical processes that have led to the migration of students and academics to the United States and Canada. While there has been rigorous scholarship on MENA migration, the primary focus has been on refugees and religious minorities fleeing wars and authoritarian regimes. There has been little research theorizing academic migration from the region and its implications on sending and receiving countries. Understanding waves of academic migration from this region is critical because the rapid exodus of academics from these states will lead to the loss of educated, high-skilled workers, leaving their homelands wanting for skilled labor. In addition, educated youth and academics have long been a politically active entity, by holding protests, strikes, and sit-ins. Therefore, their flight can lead their homelands to continue to shift toward authoritarianism.\nThis work is located at the intersection of Middle East Studies, global migration, comparative history, and political sociology. It further engages in studies of global capitalism in the Global South and its relations with state repression in its various forms such as economic, ideological, cultural, sociological, and gendered repression. By analyzing the new wave of academic migration from Iran, Egypt, and Turkey to the Global North, this work argues that two primary reasons have caused this new wave of migration: a) state repression, which significantly increased in the 2010s and b) neoliberal restructuring of the sending states’ economies, causing unstable and precarious economic conditions and “drawing” academics to the Global North. \nThis work presents migration data from the three MENA countries to the Global North and charts recent waves of academic migration from 1950 to 2022. In addition, it offers economic data (such as cost of everyday goods, cost of housing, and local currency exchange rates with the dollar) gathered from governmental statistics organizations, demonstrating the developments in people’s living conditions. These data points show deteriorating economic conditions of the working class. Alongside precarious economic conditions, the work studies other push factors in these states, including state repression. In the early 21st century, repression has manifested in increased rates of political prisoners, decrease in press and media freedom, and massacres carried out by governments. \nThis project centers the migration accounts of thirty-four recent migrants from Iran, Egypt, and Turkey who are academics, journalists, activists, or artists. In these interviews, recent migrants comment on said growing repression, being persecuted, their hurried escapes, and governmental assaults on the working class’ dignity. They also reflect on possibilities of their return to their homelands and their vision for their homelands’ futures.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,006 | 0,005 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 source (Gemma direct ou Codex distillé), 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 ».