Immersive Storytelling and an Afro- centric Future for XR
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper opens a conversation around a possible Afro-centric future for Immersive storytelling, particularly in XR, one that might challenge Western-centric approaches to XR (extended reality) technologies and storytelling methods. The author argues that African creators across the continent's 54 countries offer vital perspectives that could reshape global XR practices. Drawing on theoretical frameworks from postcolonial scholars like Trinh T. Minh-ha and Jaishree Odin, the paper positions spatial and immersive storytelling as an epistemological challenge to Western narrative traditions. It highlights successful African XR projects, including Joel Kachi Benson's award-winning VR work and initiatives from studios like Black Rhino and Electric South, while acknowledging persistent access barriers. The discussion explores the convergence of XR with Internet of Things (IoT) and Artificial Intelligence, proposing that diverse experimentation is crucial for the medium's maturation. The paper advocates for moving beyond mimetic approaches and mobile-centric development to embrace more varied storytelling traditions, particularly those grounded in African orality and participatory practices. This research suggests that an Afro-centric future for XR could significantly expand the medium's potential for global storytelling and cultural expression.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it