Structural Adjustment Programs and the Trickle-Down Effect: A Case Study of the Fujimori Period in Peru, Using Reproductive Health as an Indicator for Levels of Poverty
Bibliographic record
Abstract
The purpose of this analysis is to investigate whether the Organisation for Economic Co-operation and Development/United Nations/World Bank (OECD/UN/WB) poverty reduction objectives are compatible with the neo-liberal development model, using Peru as a case study. Three OECD/UN reproductive health indicators were selected to assess poverty: female literacy, infant mortality and maternal mortality. Fertility rates were also analyzed to explore the impact that neo-Malthusian policies have wielded. Shortly after his ascendance to power in 1990, President Fujimori undertook health finance reforms to promote cost-effectiveness and efficiency under political guidance from international financial institutions (IFIs). Internationally, Peru was portrayed as a neo-liberal success story. However, maternal mortality rates throw into contention claims that economic growth has a trickle-down effect. From the fertility rates, it can be deduced that the advent of structural adjustment has led to a resurgence of a neo-Malthusianism approach, putting family planning on the front burner, to the detriment of reproductive health.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".