Trade and nutrition policy coherence: a framing analysis and Australian case study
Bibliographic record
Abstract
OBJECTIVE: Maximising synergies and minimising conflicts (i.e. building policy coherence) between trade and nutrition policy is an important objective. One understudied driver of policy coherence is the alignment in the frames, discourses and values of actors involved in the respective sectors. In the present analysis, we aim to understand how such actors interpret (i.e. 'frame') nutrition and the implications for building trade-nutrition policy coherence. DESIGN: We adopted a qualitative single case study design, drawing on key informant interviews with those involved in trade policy. SETTING: We focused on the Australian trade policy sub-system, which has historically emphasised achieving market growth and export opportunities for Australian food producers. PARTICIPANTS: Nineteen key informants involved in trade policy spanning the government, civil society, business and academic sectors. RESULTS: Nutrition had low 'salience' in Australian trade policy for several reasons. First, it was not a domestic political priority in Australia nor among its trading partners; few advocacy groups were advocating for nutrition in trade policy. Second, a 'productivist' policy paradigm in the food and trade policy sectors strongly emphasised market growth, export opportunities and deregulation over nutrition and other social objectives. Third, few opportunities existed for health advocates to influence trade policy, largely because of limited consultation processes. Fourth, the complexity of nutrition and its inter-linkages with trade presented difficulties for developing a 'broader discourse' for engaging the public and political leaders on the topic. CONCLUSIONS: Overcoming these 'ideational challenges' is likely to be important to building greater coherence between trade and nutrition policy going forward.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".