Crafting Attention in Immersive and Interactive Practices
Bibliographic record
Abstract
This creation is part of the ongoing project “Positioning the Audience in Cinematic Virtual Reality”, supported by the Scientific and Technological Research Council of Turkey. The project engages with the attentional and corporeal resonance between spectators and visual experiences in participatory and immersive practices. In the continuing first phase of the project, we are designing and producing a VR creation that will then enable us to conduct audience research to focus on the attention practices of the viewers in the second phase. Hence, as a critical research-creation project it has two complementary and symmetrical foci that employ both theory and practice, and that are intertwined with one another. In tandem with making an interactive and photorealistic (cinematic) VR film where spectator crafts the very narrative unfolding by voluntary and involuntary attentional participation in a given scene, we are also developing a conceptual framework on how immersive and interactive technologies are conditioned by the freedom given to the spectator. As interdisciplinary project it brings together researchers from film studies, new media studies and psychology to develop a holistic understanding on the attention of spectator in moving image technologies. In making, instead of using game-based interactivity technologies enabled by the controllers, the VR film uses gaze detection techniques and the attentional economy of the spectator as active defining element of the narrative unfolding. Combining both the bottom-up and the top-down attentional procedures it allows spectators to craft a circular experience and aims to problematize the craft of the spectator. In theory it aims to develop an historical and critical understanding of visual practices where spectator is the active producer of the optical experience in certain media ecology including technologies from proto-cinematic devices to the post-cinematic media constellation comprising video games, Virtual Reality etc. Therefore we aim to problematize and rend sensible the craft and the autonomy of the viewer by combining conventional academic research practices with artistic experimentation. The creation undertaken in the first phase of the research is aimed to result in multiple alternative designs, which will form the basis of our presentation at IFM2023.
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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 | 0.001 | 0.001 |
| 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".