Bibliographic record
Abstract
Abstract The book explains why migration to the United States, Europe, and Asia tripled after 1973. Today, global migration is at a historic high of over 280 million people. Mass migration has transformed international and domestic politics. Such migration is not only unprecedented; it was—at least in the global north—unexpected and unwanted. Publics across Europe, North America, and Asia oppose immigration, and events in the early 1970s should have led to a decline in migration. Instead, global migration tripled. The book asks why. It argues that economic and geopolitical changes unleashed by the OPEC oil crisis led to an unanticipated surge in global migration. Economically, the quadrupling of oil prices halved growth rates in the West, they never recovered, and wages have stagnated for five decades. In response, consumers rebuilt their standard of living on the back of cheap migrant labor. At the same time, OPEC flooded the Middle East and Russia with oil money, destabilizing Iran, ushering in the Iranian Revolution, contributing to Moscow’s 1979 decision to invade Afghanistan, and leading to the two Gulf Wars. In the non-oil-producing states, Egypt and Syria, OPEC-induced inflation put the last nail in the coffin of import substitution industrialization (using tariffs to industrialize), forced a turn to neoliberalism, and led to inequality, mass protests, terrorism (Egypt), and civil war (Syria). These simultaneous economic and geopolitical developments, all set in motion by the OPEC oil crisis, resulted in 115 million migrants that few in the global north expected or wanted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.044 | 0.013 |
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".