Local Sourcing and Supplier Development in Global Health: Analysis of the Supply Chain Management System's Local Procurement in 4 Countries
Bibliographic record
Abstract
From 2006 to 2014, Supply Chain Management System (SCMS), the global procurement and distribution project for the U.S. President's Emergency Plan for AIDS Relief (PEPFAR), distributed over US$1.6 billion worth of antiretroviral drugs and other health commodities, with over US$263 million purchased from local vendors in 14 countries in sub-Saharan Africa. A simple framework was developed and 39 local suppliers from 4 countries were interviewed between 2013 and 2014 to understand how SCMS local sourcing impacted supplier development. SCMS local suppliers reported new contracts with other businesses (77%), new assets acquired (67%), increased access to capital from local lending institutions (75%), offering more products and services (92%), and ability to negotiate better prices from their principles (80%). Additionally, 70% (n=27) of the businesses hired between 1 and 30 new employees after receiving their first SCMS contract and 15% (n=6) hired between 30 and 100 new employees. This study offers preliminary guidance on how bilateral and multilateral agencies could design effective local sourcing programs to create sustainable local markets for selected pharmaceutical products, laboratory, and transport services.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".