Can Market Access Help African Agriculture
Bibliographic record
Abstract
ATPC is a project of the Economic Commission for Africa with financial support of the Canada Fund for Africa This publication was produced with the support of the United Nations Development Programme (UNDP). Material from this publication may be freely quoted or reprinted. Acknowledgement is requested, together with a copy of the publication The views expressed are those of its authors and do not necessarily reflect those of the United Nations. iii This paper examines the implications for African economies of the possible outcomes from the ongoing agriculture negotiations in the Doha Round. The paper defines scenarios that capture key elements of the modalities negotiations and undertakes simulations using a global dynamic general equilibrium model to examine the impact of multilateral agricultural trade reforms on African economies. The scenarios vary in their level of ambition in the market access pillar through both the level of tariff cuts in the different tiers and the level of sensitive sectors defined both for developed and developing economies. Results show
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.122 | 0.010 |
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".