Public diplomacy message strategy (Public Diplomacy) (see also public diplomacy approach)
Bibliographic record
Abstract
The variable “public diplomacy message strategy” (or “public diplomacy approach”) refers to public diplomacy efforts in a given country in order to investigate how and with which goal public diplomacy is strategically communicated in the given context. The variable reflects the communication style of a specific actor (a politician, government, or country). Field of application/theoretical foundation: Analyses of public diplomacy message strategies or approaches mostly build on the taxonomy of public diplomacy (Cull, 2008) or the proposed categories of public diplomacy by Fitzpatrick (2010). References/combination with other methods of data collection: Public diplomacy message strategies can, in addition to content analysis, be analyzed by conducting interviews or surveys with public diplomacy actors, which allow validating the results from content analyses. Example study: Dodd & Collins (2017) Information on Dodd & Collins (2017) Authors: Dodd & Collins Research question/reseach interest: Comparison between public diplomacy approaches between Central Eastern European (not explicated) and Western countries (Canada, the United Kingdom, and the United States) Object of analysis: Twitter content posted by 41 embassy accounts (not explicated) Time frame of analysis: March 2015 Information about variable Varible name/definition: Public diplomacy practices: Communication strategy Level of analysis: Tweet Values: Building on Cull’s (2008) taxonomy of public diplomacy: (1) Listening (attempts to collect and collate information about foreign publics and their opinions) (2) Advocacy (activities that promote the country’s policies or general interests among foreign publics) (3) Cultural (efforts to promote cultural resources and achievements of a country) (4) International (activities that involve sending national actors abroad or receiving international actors to strategically manage the international environment) (5) News (use of radio, television and digital media to inform and involve foreign audiences) (6) Other Scales: Nominal Reliability: Krippendorf’s alpha = .50 References Cull, N. J. (2008). Public Diplomacy: Taxonomies and Histories. The ANNALS of the American Academy of Political and Social Science, 616(1), 31–54. Dodd, M. D., & Collins, S. J. (2017). Public relations message strategies and public diplomacy 2.0: An empirical analysis using Central-Eastern European and Western Embassy Twitter accounts. Public Relations Review, 43(2), 417–425. Fitzpatrick, K. (2010). The future of U.S. public diplomacy: An uncertain fate. Martinus Nijhoff/Brill.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.004 |
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".