Tracing the repeated failure of doha development trade round from a neo- gramscian perspective
Bibliographic record
Abstract
This paper analyzes the repeated failure of the Doha Round talks in world trade since 2001 from a neo-Gramscian perspective. The lack of progress and breakdown of multilateral trade negotiations reflect an emerging new architecture of power politics in the international economy. Four major players in world trade, the US, the EU, Japan and Canada, used to have a significant impact in terms of shaping the agenda of the multilateral trade negotiations as well as defining the outcomes. However, in the context of the WTO, emerging powers such as India, Brazil, and China began to confront the dominance of these countries. Developing and developed countries have contending views on the agenda issues, marked by confrontation on the former’s refusal to open non-agricultural markets and industrialized states’ refusal to open their agricultural markets. By undertaking a discourse analysis of statements of major social forces such as market-oriented capital groups, bureaucrats, and political leaders, the paper argues that both sides employ certain strategies and discourses to coerce or to persuade the opposing parties. Hence, the multilateral trade negotiations emerge as zones of exercising hegemony through discursive and strategic measures rather than being an area to produce common norms, values and policies for the well being of all members in the world trade regime.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".