Political Cartoons as a Vehicle of Setting Social Agenda: The Newspaper Example
Why this work is in the frame
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Bibliographic record
Abstract
In recent years, the cartoons genre has gained considerable research interest across disciplines; for example, communication, media studies and health sciences. More so, cartoons serve as potent source of data used to study social phenomena. This paper aims at illustrating how political cartoons are used as a vehicle of setting social agenda in Nigerian newspapers to reorient and shape the public opinion through recurrent depictions mirroring current socio-political issues at a given period. The cartoons texts were excerpted from two major Nigerian newspapers, Daily Trust and Vanguard during the period 2007-2010. One-hundred cartoons were selected using purposive sampling technique. Fifty cartoons were taken from each newspaper magazine. Specifically, content analysis was used to identify the themes contained in the cartoons depictions. Qualitative method was used to analyze the cartoons through semiotic analysis. The analysis is mainly concerned with the interpretation of the sign system based on the connotation and denotation elements in the cartoons. The results indicated that 80% of the themes focused on substantive issues through which social agenda is set to reflect social practices in the Nigerian social political contexts. Also, the results showed that Nigerian political cartoons set social agenda by mainly encapsulating current and sensitive issues that people are much concerned about. Finally, the study has identified the lack of supportive and clearly defined theoretical background in analyzing political cartoons as a major problem in previous cartoons research. Thus, this paper contributes to the cartoon research by offering theoretical insight to the cartoon genre through agenda setting theory of media effect.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it