Transforming Intractable Policy Conflicts: A Qualitative Study Examining the Novel Application of Facilitated Discourse (Track Two Diplomacy) to Community Water Fluoridation in Calgary, Canada
Bibliographic record
Abstract
Governments face challenges in resolving complex health and social policy conflicts, such as the community water fluoridation (CWF) impasse in Calgary. Track Two diplomacy, informal dialogues facilitated by an impartial third party, is proposed to address these issues amid epistemic conflict and declining public trust in fellow citizens, science, and government. This study examined Track Two diplomacy's application in Calgary's CWF policy conflict. Collaborating with policymakers and community partners, the research team explored a Track Two-CWF process and conducted 21 semi-structured interviews with policymakers, scholars, practitioners, observers, and civil society representatives. Data interpretation explored contextual factors, conflict transformation potential, and design features for a Track Two process. A conflict map revealed factors contributing to impasse: the polarizing nature of a binary policy question on fluoridation; disciplinary silos; failed public engagement; societal populism; societal lack of disposition to dialogue; individual factors (adverse impact of conflict on stakeholders, adherence to extreme positions, issue fatigue, apathy, and lack of humility); together with policy-making factors (perceived lack of leadership, lack of forum to dialogue, polarization and silos). Participants suggested reframing the issue as nonbinary, involving a skilled facilitator, convening academics, and considering multiple dialogue tracks for a Track Two process. The first theory of change would focus on personal attitudes, relationships, and culture. Participants expressed cautious optimism about Track Two diplomacy's potential. Track Two diplomacy offers a promising approach to reframe intractable public health policy conflicts by moving stakeholders from adversarial positions to jointly assessing and solving problems. Further empirical evidence is needed to test the suggested process.
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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 | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".