Testing the Limits of Welfare State Changes: The Slow‐moving Immigration Policy Reform in Japan
Bibliographic record
Abstract
Abstract In the 1990s, the Japanese government made transformative policy change by significantly expanding social care, thereby contradicting the core of the country's familialistic welfare principle of non‐state intervention in the family. Remarkably, social care expansions were widely accepted by the public as necessary, if not welcome, changes to deal with low fertility and an ageing society. Japanese people seemed to have no problem accepting that the rapid demographic ageing and the ‘modernization’ of the family necessitated outsourcing childcare and elder care. As the supply of native‐born care workers continued to shrink, the Japanese government began turning to foreign care workers. Unlike the case of social care expansion, however, immigration policy changes are proving difficult. Despite ample motivations, opportunities, and positive political mobilization, policy reforms have been slow and are far from achieving their goals. Most Japanese citizens are highly ambivalent about opening up the country to immigration, and the idea of immigration and multicultural societies remains disconnected from that of a shared national identity premised on ethnic and cultural homogeneity. This article shows the importance of public sentiments and national collective imaginary in policy change.
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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 | 0.024 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".