The role of non-governmental organizations in global health diplomacy: negotiating the Framework Convention on Tobacco Control
Bibliographic record
Abstract
The Framework Convention on Tobacco Control (FCTC) is an exemplar result of global health diplomacy, based on its global reach (binding on all World Health Organization member nations) and its negotiation process. The FCTC negotiations are one of the first examples of various states and non-state entities coming together to create a legally binding tool to govern global health. They have demonstrated that diplomacy, once consigned to interactions among state officials, has witnessed the dilution of its state-centric origins with the inclusion of non-governmental organizations (NGOs) in the diplomacy process. To engage in the discourse of global health diplomacy, NGO diplomats are immediately presented with two challenges: to convey the interests of larger publics and to contribute to inter-state negotiations in a predominantly state-centric system of governance that are often diluted by pressures from private interests or mercantilist self-interest on the part of the state itself. How do NGOs manage these challenges within the process of global health diplomacy itself? What roles do, and can, they play in achieving new forms of global health diplomacy? This paper addresses these questions through presentation of findings from a study of the roles assumed by one group of non-governmental actors (the Canadian NGOs) in the FCTC negotiations. The findings presented are drawn from a larger grounded theory study. Qualitative data were collected from 34 public documents and 18 in-depth interviews with participants from the Canadian government and Canadian NGOs. This analysis yielded five key activities or roles of the Canadian NGOs during the negotiation of the FCTC: monitoring, lobbying, brokering knowledge, offering technical expertise and fostering inclusion. This discussion begins to address one of the key goals of global health diplomacy, namely 'the challenges facing health diplomacy and how they have been addressed by different groups and at different levels of governance' (Kickbusch et al. 2007a: 972).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".