Qualitative Political Communication| Understanding the Impact of the Transnational Promotional Class on Political Communication
Bibliographic record
Abstract
This article is an overture to political communication researchers to broaden their categories and contexts of analysis when assessing the role of promotional practices in political life. It aims to make both methodological and empirical contributions to qualitative political communication research. Drawing on ongoing research into the proliferation of political communication strategies around the exploitation of oil in Canada and the United States, the article analyzes efforts by promotional intermediaries to achieve legitimacy for their clients in three sites: Montreal, Canada; Houston, Texas; and Fort McMurray, Alberta. Bringing to light the tools, techniques, and claims to authority of promotional actors and their practices, the article demonstrates the importance of field research to the analysis of political communication. By getting inside the social worlds of the actors and processes involved, researchers can make sense of the ways that political communication is defined, understood, and acted upon by interlocutors and audiences. The article also addresses specific methodological challenges of undertaking this research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".