ANALISIS PESAN SEMIOTIKA VIDEO KEKERASAN DALAM RUMAH TANGGA DALAM TAGAR SIGNAL FOR HELP PADA YOUTUBE CANADIAN WOMEN’S FOUNDATION (ANALISIS SEMIOTIKA FERDINAND DE SAUSSURE)
Bibliographic record
Abstract
This research aims to conduct a semiotic analysis of the #SignalForHelp campaign on YouTube, initiated by the Canadian Women's Foundation. The study focuses on analyzing the semiotics of the campaign in relation to Ferdinand de Saussure's theories. The campaign aims to raise public awareness about gender-based violence and provide discreet help to victims, with a particular focus on trauma recovery. By examining the various signs, symbols, and codes used in the campaign, this analysis sheds light on the effectiveness of semiotics in conveying the message of violence at home and the significance of public awareness, victim support, and discreet help in combating gender-based violence. The findings contribute to a deeper understanding of the role of semiotics in shaping social discourse and promoting positive change in addressing gender-based violence.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".