INTENTION AND ROLE OF ANTI-BULLYING CAMPAIGN OF FAMILY CHANNEL CANADA: A CRITICAL DISCOURSE ANALYSIS APPROACH
Bibliographic record
Abstract
Keywords: CDA, anti-bullying campaign, government, Family Channel Canada, intention, role, viewers. Family Channel’s Anti-Bullying campaign is an unprofitable advertisement that is created by Family Channel Canada and Canadian government as the two biggest powerful sides in Canada. Although the campaign asks people to take a stand against bullying, but it is well known ability to influence people and spread information makes Family Channel Canada and Canadian government insert their own importance behind it. Then, CDA is a suitable approach to analyze it. The study is aimed: (1) to identify the intention behind creating Family Channel’s Anti-Bullying campaign; (2) to find out the role of Family Channel’s Anti-Bullying campaign for society; (3) to find out whether the viewers agree or disagree with Family Channel’s Anti-Bullying campaign. This study uses qualitative quantitative approach to provide better understanding and answer to wide range of research questions. The qualitative research could provide in-depth and rich data, while the quantitative method is useful toward generalizing research findings. This study reveals that behind the campaign, there is hidden intention to build good imagery of Canadian government and Family Channel Canada. This campaign’s role is to lead the society to the path that has been planned by the Canadian government and Family Channel Canada and to mold public’s opinion. Lastly, there are 143 agree comments from the total 509 comments, it could be generalized that viewers actually agree with this campaign. The writer suggests the society to be more selective and smart in watching something. The powerful sides also should maintain their power well and use it only for the society needs. It would be better if the next researcher digs up deeper in the field of discourse in our daily life. Maybe, the discourse that lays behind some figures and images in advertisements. Developing the discourse behind those images could also do by combining the theory of CDA and theory of visual design.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".