Bibliographic record
Abstract
Research shows that more than 60 percent of South African born professionals, who graduated from South African universities, are leaving the country to work abroad in search of better working environments and financial rewards.This research assessed the intention to migrate and a number of factors that are likely to influence intentions to migrate such as age, professional group, education, gender, and population group.The research also examined the countries to which people intend to migrate.Using survey data on migration from the Human Science Research Council of South Africa, descriptive and multivariate models were used to assess the relationship between various socio-demographic factors and the intention to migrate.For the multivariate models, logistic regression technique was used in analyzing migration trends.Results show that age and education have major influences on the intentions to migrate.It was also found that gender, marital status and population groups are significant factors when assessing the migrants.About 88 percent of respondents do not intend to migrate permanently to another area in South Africa or to another country in the next 12 months.About 97 percent are not planning to move temporarily, and 98 percent do not v consider migrating.Thus, majority of respondents do not intend or plan to migrate either permanently or temporary.This also means that, assuming that all expressed intentions turn into behaviour, migratory moves might decrease.Those who are likely to move would do so mainly to Australia (26 percent), Great Britain (19 percent), United States of America (19 percent), and Canada (7 percent).The least popular destinations, amongst others, were Angola, Egypt, France, and Germany (about 1 percent of respondents would consider moving to each of these countries).Those who intend to move within South Africa account for 85 percent and those intending to move outside South Africa account for 15 percent.This implies that there is a high possibility that we will observe more internal than international migration in the near future.Younger people aged between 18-24 years old were more likely to move than those between 35-45 years.It is evident that males were more willing to move abroad than females and more women were likely to move within South Africa.Of those who do not have any formal education, none would want to move abroad, but some would consider moving within South Africa.Those with a bachelor's degree are the most likely to move abroad, followed by those with honours degree or superior qualification.About 37 percent of those married or currently living together were unlikely to plan to move permanently.Fifty four percent of those who are married or currently living together said that they were unlikely to plan to move temporarily.We find that Indians/Asians are 74 percent vi less likely to plan to move out and return to their current place of residence at a later date.Africans/Blacks are more likely to move within South Africa than any other races.Whites and Indians are less likely to move within South Africa.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".