Ideas, Institutions, and Welfare Program Typologies: An Analysis of Pensions and Old Age Income Protection Policies in Sub‐Saharan Africa
Bibliographic record
Abstract
Abstract Since the 1980s, social policy research shifted attention from institutional development of welfare programs to what were described as crises of the welfare state in an era of austerity. Much of the scholarly debate in this area had focused on the maturation of welfare programs, especially the post‐war old age income support programs in the advanced industrialized countries to the neglect of social protection in Sub‐Saharan African (SSA) countries. This paper is intended to bring the dynamics of social policy in SSA countries into the comparative welfare dialogue and into the global social security debate in particular. Using a historical institutionalist approach, this study analyzes the trajectories of old age income support development in SSA countries through a careful study of old age income security or protection strategies in the region across time and space. The paper develops ideal typologies for understandings variations and transformations of pensions and old age income provision programs in the region. In doing this, it argues that the ideas and institutions around which recent rounds of pension reforms revolves have always been at both the foreground and background of old age income protection thinking and practices in SSA countries since the pre‐colonial era.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".