Bibliographic record
Abstract
Migration may become the most important branch of demography in the early decades of the new millennium in a rapidly globalizing world. This paper discusses the causes, costs and benefits of international migration to countries of the South and North, and key issues of common concern. International migration is as old as national boundaries, though its nature, volume, direction, causes and consequences have changed. The causes of migration are rooted in the rate of population growth and the proportion of youth in the population, their education and training, employment opportunities, income differentials in society, communication and transportation facilities, political freedom and human rights and level of urbanization. Migration benefits the South through remittances of migrants, improves the economic welfare of the population (particularly women) of South countries generally, increases investment, and leads to structural changes in the economy. However, emigration from the South has costs too, be they social or caused by factors such as brain drain. The North also benefits by migration through enhancement of economic growth, development of natural resources, improved employment prospects, social development and through exposure to immigrants’ new cultures and lifestyles. Migration also has costs to the North such as of immigrant integration, a certain amount of destabilization of the economy, illegal immigration, and social problems of discrimination and exploitation. Issues common to both North and South include impact on private investment, trade, international cooperation, and sustainable development. Both North and South face a dilemma in seeking an appropriate balance between importing South’s labour or its products and exporting capital and technology from the North.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".