Power, knowledge and resistance: between co-optation and revolution in global trade
Bibliographic record
Abstract
It has been recognised that the process of multilateral trade negotiations has been fundamentally altered by the increased involvement of non-governmental organisations (NGOs) since the Uruguay Round. NGOs have helped to increase the voice of the developing world, nullify some of the asymmetries in political power vis-à-vis the rich world, and provide trade analysis to bolster participation. What is less recognised is the growing importance of certain international governmental organisations (IGOs) that provide demand driven advocacy through the provision of knowledge and expertise to developing states that, at times, challenges the dominant neoliberal agenda at the WTO. Unlike NGOs, many of these organisations are able to hold observer status on WTO committees and write member state submissions. Yet, ideologically and in terms of their specific capacity-building functions, these organisations are also distinct from other IGOs operating in the area of global trade. Through everyday actions, ‘insider’ IGOs such as the South Centre and United Nations Conference on Trade and Development undertake work that redresses imbalances of power in global economic governance and transforms the ‘common sense’ underlying trade practices. In this paper, we develop a set of ideal types aimed at unpacking and illuminating the variegated degrees and types of ‘resistance’ exercised within the international trade system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.083 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.006 |
| 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".