Propaganda Instruments in Contemporary Campaigns: Comparison of Estonian Political Television Advertisements and Modern Television Commercials
Bibliographic record
Abstract
The author argues in the present article that although propaganda is considered mostly a tool of ideological communication suitable for use during wars or in totalitarian states, it is still used in contemporary democratic societies at peacetime and there are no major differences between employing instruments of propaganda in the public or the private sectors. The present analysis is based on the similarities and differences between Estonian political television advertisements and modern television commercials with an emphasis on the application of propaganda instruments. The author employed content analysis when studying the sample in which were 100 non-political and 84 political advertisements. This research shows that Estonian political television advertisements and international non-political television advertisements share some significant similarities: cognitive propaganda instruments are more widely employed than social ortechnological ones. The role oftechnological propaganda instruments is diminishing and such instruments are replaced by structural ones. A major difference is that, on average, there are more propaganda instruments per advertisement in political television advertisements than in non-political television advertisements, and technological propaganda instruments are not employed in non-political television advertisements.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".