Political Brand: role of social agents as a promotional tool for the development of political interest
Bibliographic record
Abstract
Recent studies in many democratic countries like USA, Europe and Canada have confirmed that political participation of the electorates is declining over time. The trend is mainly attributed to the youth disengagement due to lack of interest in politics. This matter has become a serious concern for scholars and politicians, while they try to find new ways to develop youth interest in politics. In fact, studying political-interest is not a simple subject because it is directly linked to the behavior of voters.’ To ameliorate this behavior, it requires great efforts to position political brand in an attractive way to appeal the young voters. Furthermore, the behavior of young voters is directly influenced by their social networks. Brand awareness and brand association (in this case political party or politician) dependent on the intensity and amplitude of information and the nature and manner of available tools used for promotional purposes. Particularly in politics, politicians have to select more reliable and strong socially acceptable marketing tool to develop their desired image. This research tends to analyze the role of social agents as a promotional tool in the development of political interest among young voters. Specifically, this paper investigates three core questions. First, who is the most influential and reliable social agent to develop brand awareness and association? Secondly, how social agents, media, and internet can play their role as promotional tools in political interest development? Thirdly, how the branding strategies could be applied to ameliorate the political interest in youth? Data has been collected from the young students of University of Gujrat, Pakistan to analyze the young voters’ behavior and the mediating role of social networks, as promotional tools, in the development of political interest. Analysis of the available data indicates that politicians or political parties, who are actively engaging in developing strong relationships with youth by effectively mobilizing the social agents, media, and internet, shall be successful in developing and inducing the political interest among the youth and consequently enhancing voting-turnout.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".