Cultural Diplomacy and Trade: Making Connections
Bibliographic record
Abstract
The North American Cultural Diplomacy Initiative’s (NACDI) approach to cultural diplomacy is based on: an expansive and nuanced approach to the term culture; a belief in the necessity of relational, rather than transactional engagement; and an interest in understanding the significance of non-state actors in the current network environment of diplomacy. Rather than seeing the multifaceted nature of cultural diplomacy as a challenge, NACDI points to complexity as a reason to advance nuanced discussions, including the recognition of a wide range of actors and activities, and well-developed indicators that have specific qualitative and quantitative measurements. The report, Cultural Diplomacy and Trade: Making Connections, demonstrates that cultural diplomacy and trade are intrinsically linked, and that investment in cultural diplomacy results in a corresponding impact in trade. The report has a four-part structure, which begins by emphasizing the need for common language to facilitate conversations between policymakers, practitioners, and academics. Next, the report addresses the history of Canadian cultural diplomacy and trade, suggesting that Canada needs to understand its successes in cultural diplomacy to date in order to establish and build on best practices. Third, the report engages with the thorny issue of metrics as a means to monitor and demonstrate the impact of Canada’s cultural diplomacy. Here, NACDI argues for comprehensive indicators that take into account short, medium, and long-term assessments, and that utilize qualitative and quantitative measurements. The fourth component of the report addresses a range of case studies from Australia, Japan and South Korea. These provide strategic information as to how other nations are utilizing cultural diplomacy, specifically with regards to creative industries and trade.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.011 | 0.023 |
| Scholarly communication | 0.022 | 0.012 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".