Bibliographic record
Abstract
Migration is one of the most enduring themes of human history. It is one of the most drastic life changes and transitions an individual can face. Each person's reaction to migration is unique; migrants may either experience stability and opportunity or a sense of emotional uprootedness, or in fact, all. Having recently migrated to Australia from South Africa, I was curious to know about the experiences of other South Africanswho were in the early stages of migration. Over the last decade South Africa has experienced severe political, social and economic uncertainty, as well as increasing levels of violence and crime. For these reasons, many South Africans have chosen to leave their country of birth. By 1992 South Africa had one of the world's highest crime rates, on a per capita basis. In 1994 South Africa had the highest per capita incidence of rape recorded from anywhere and from then to 1996 the total annual number of rape cases reported nationally increased from 42 429 to 50 481. The 1996 homicide rate of 61 per 100 000 placed the country among the most violent in the world. According to a Health Review released in 1997, violence is the leading cause of injury mortality in South Africa. A report from the World Economic Forum declared that South Africa's organised crime is second only to Colombia's, with its frightening drug cartels, and Russia's, with its omni-present mafia. According to a recent study, the rape homicide rate in one of South Africa's major cities, Cape Town, is 12 times higher than in the United States, which is an entire nation. (The Star newspaper Internet site). As a consequence, many South Africans have made the decision to build a safer, more secure life elsewhere. While many choose to settle in the United States, Canada and the United Kingdom, a large portion of South Africans choose to begin their new life in Australia. South African immigrants perceive Australia to offer the type of lifestyle, values and culture into which they can readily integrate. According to the Australian Immigration Statistics Internet site, the immigration of South Africans to Australia has risen steadily over the last decade. Between 1984 and 1988 14,700 South African's immigrated to Australia. Between 1997 and 1998 there were 4,281 new immigrants, and between 1998 and 1999 there were 5,024 South African immigrants. The latest Census in 1996 recorded 55,755 South African-born persons in Australia, an increase of 14% from the 1991 Census. It would seem as though anyone living in South Africa would want to leave and that a feeling of total relief would be the full story. But, I am one of those and relief is not all there is. Instead, a blend of powerful emotions is deeply felt and the psychological repercussions, far-reaching. It is my belief that migration entails one of the most extreme forms of rupture at the social level and the intrapsychic level; it involves alterations in the external reality that rebound in each individual's internal reality.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.027 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.025 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 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".