More Than a Feeling: The Role of Pathos in Documentary Film and Social Impact Risk Communication
Bibliographic record
Abstract
This research paper examines the use of pathos, or the appeal to emotion to evoke feeling, and its role in digital storytelling and social impact risk communication. A review of the theoretical literature and a case study analysis of the documentary The Social Dilemma are used to explore how the relationship of technical film elements and pathos can influence audiences. An evidence-based approach to storytelling and targeting specific emotional cues are a few of the key strategies discussed. Methods for social impact evaluation of the documentary film, such as measuring the outcome of evoking emotion as an agent of social change, is complex and an area that offers scope for further research as identified by the gap in the literature. The findings of this paper aim to contribute to the evolving literature that recognizes pathos as a powerful and persuasive tool in digital storytelling -- amplifying change in social risk communication messaging.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".