The New Wave of Middle Eastern Academic Migration in the 21st Century: Roots and Routes
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".