Targeted transfers, a left-wing policy? The impact of left-wing governments and corporatism on transfers to low-income families (1982–2019)
Why this work is in the frame
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Bibliographic record
Abstract
In the last decades, several countries introduced new income-tested child benefits and targeted in-work tax credits to boost the income of low-income families. Inspired by the power resource theory, I postulate that left-wing governments tend to increase benefits to low-income families because their ideology favours redistribution and to consolidate the vote of low-income families, but that both right- and left-wing governments increase benefits for middle-income families. The impact of left-wing governments should be stronger in countries with a weak bargaining system as social partners are unable to reduce inequalities between families. To demonstrate this argument, I use statistical analyses based on OECD data to measure the effect of government ideology and corporatism on the level of benefits received by low- and middle-income families in OECD countries from 1982 to 2019. The results indicate that left-wing parties have a significant impact on benefits received by low-income families, but not on benefits received by middle-income families. Also, even though corporatism is associated with different types of child benefits, it does not influence the relationship between left-wing governments and benefits received by low-income families.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it