Bibliographic record
Abstract
Political Communication in the Anglophone World: Case Studies, by Theodore F. Sheckels, extends political communication scholarship—primarily rhetorical scholarship—into the extensive English language arena outside the United States and the United Kingdom. While wrestling with the extent to which insights derived from and approaches used in political communication research focused on the United States can be used in other nations with different government structures, different media operations, and different political cultures, Sheckels provides insight into a variety of political communication topics ranging from the role gender plays in campaign politics to the politics involved as one speaks upon the occasion of leaving high office. This book explores how Canadian Prime Minister Pierre Elliott Trudeau used moments of media attention to push his foreign and domestic policy agenda, as well as another Canadian Prime Minister, Kim Campbell, and the difficulties she faced because of her gender. Sheckels also examines Jamaica’s Michael Manley and his shift from advocating socialism to later supporting free markets, and reggae artist Bob Marley and his musical shift from concern for Kingston’s poor to embracing pan-Africanism. Popular media images of Africa are also considered, as the book investigates Mwai Kibaki’s attempts to unify Kenya, Nelson Mandela’s presidential rhetoric, and Thabo Mbeki’s “I am an African Address.” Finally, Sheckels goes to Australia to consider Gough Whitlam’s unprecedented dismissal as prime minister, and Kevin Rudd’s farewell speech after being replaced by his own party members. Asking new questions and using novel rhetorical approaches, Political Communication in the Anglophone World illuminates how communication proceeds, whether the medium be speech, song, website, or pirouette.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.023 | 0.008 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".