Bibliographic record
Abstract
Immigration policies are aimed at young-to-middle-aged people, for good reasons. The exceptions are parental and grandparental immigration programs, designed to reunite yesterday’s immigrants and their young children with the (grand)parents who still live in the country of origin. (Grand)parental immigration has been an unquestioned facet of immigration law for the last century and a half. Elderly people are the least threatening immigrants: they rarely commit crimes, they are not conduits for further immigrant family members, and they are unlikely to fundamentally change the culture of the destination state. Yet the last few decades have seen an unprecedented and mostly unremarked assault on parental and grandparental immigration, with some rather shoddy economics as the only reason. Quotas have been lowered, required sponsorship amounts have been raised, health conditions have been made stricter, and family structures have been added to the list of criteria. This article looks at the tightening of immigration rules since the 1970s in three types of immigrant-receiving countries: traditional settler states, modern settler states, and liberal states which seek to discourage immigration. The article concludes that reasons, whether legal, political or economic, are lacking in both quantity and quality. The growing restrictions on elderly immigration are unjust and senseless, and should be reversed.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.210 | 0.128 |
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".