Bibliographic record
Abstract
Interactive films have contributed to the viewers/users’ increasing storytelling engagement with social issues and events. With the rise of interactivity and refugee films, previous forms and storytelling methods have been changed and reformed in hybridity and as emerging immersive technologies. While these technological developments increase the overall complexity of the storytelling’s interface, they forced many users to reexamine their understanding of what they see and experience in this mediated world. Users must have a foundational knowledge of media literacy to interact with its interface and reap the benefits meaningfully. At the same time, the machine-based advances in interactivity can be referred to as the ‘interface of knowledge.’ Which type of social engagement has been created through interactive technological storytelling? Which social engagement or subject is more appropriate or efficient for interactive narratives? Do refugee stories and discourses contribute to interactive engagement? The popularization and celebration of immersive technologies, such as virtual reality and interactive films, requires significant financial spending power, digital literacy, and access to specific resources and technologies, which most of their subject do not have access to. Therefore, the barrier to approaching these immersive technologies is relatively high and inaccessible for the vast majority. This research aims to analyze a series of interactive films focusing on refugees’ storytelling, politics and aesthetics to examine their socio-political engagement. But first, what refugee stories have that appeal and make all these practitioners opt for a more engaging narrative medium? What is the refugee’s contribution or uniqueness that engages creators and viewers/users/players to adventure in their disarray? A strong connection with people whose lives are far from most of the users’ reality creating and being present within distant worlds calls the attention to the traditional cinematic narrative, which often fails to rouse the audience. In this paper, I argue that in interactive narratives, refugee characters and stories redefine the agency and potential of traditional film storytelling while granting the ability to recreate their history/fate. Also, these stories can engender a change in the world or redone the world with a sense of justice for dependable and trustful characters. Refugees possess an allegory of fantasy and unachievable reality that comfort their users. Characters without faces or names, but with well-known and reliable stories, make the users closer to the situation (moral aspect) and responsible (political sense) for their future.
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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 | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".