Bibliographic record
Abstract
Our multimedia website project, “The New Virtuality”, explores the implications of highly realistic images that interact and socialise with human users, often seemingly “live” in real‑time. Created with imaging technologies such as holographic projection or virtual reality (VR) and usually boosted by AI and machine learning, we argue that these images present unprecedented directions in understanding how reality, liveness and presence are discerned and believed. Radically breaking down differences between real and unreal, they point to an era of blurred boundaries, dematerialization and limbic spaces which converges visual media with twenty-first century politics of dis/misinformation, post-truth and deep fakery. In this project, we discuss this era as “the new virtuality.” These developments underpin the project’s research questions: how to understand this media that so freely and near-seamlessly mix virtual and actual realities? How to place this phenomenon in media’s long history of blurred environments, while still appreciating their distinctive newness and challenges? What are the impacts of the new virtuality on our apprehensions and constructions of realities? How might this mediated reality relate – as code, as language, as consciousness – to the wider contexts of information that colour contemporary times? In our methodology, we interwove theory, multimedia expression and fiction as multiple voices to articulate the project’s arguments across three frameworks of distinct approaches, media elements and genre features. The first framework is a historical context with which to understand the continuities and divergences of virtuality. The second is the connection of theory – particularly from film, screen and media studies – with textual readings drawn across multiple media, including paintings, cinema, performance, VR, apps and architecture. The third is the employment of fiction and multimedia. Inspired by the “scientific fiction” work of Kai-Fu Lee and Chen Qiufan (Lee and Chen, 2021), we intertwined a fictional story through the project for greater animation and accessibility – a creative warp to the academic weft. Multimedia via the essays’ image margins and a 33‑minute video essay function as audiovisual “mood boards” to provide elaboration, illustration, colour and setting for conveying the new virtuality’s poetics of fudged and adrift unsettling across this new reality. The result is a work of multiple voices and hybridity which identifies a new framework of reality through contemporary mixed media. This new virtuality is no longer about the questions of realism or illusion (e.g. Friedberg 2009; Grau 2003) from computer‑generated imagery (CGI) or even deepfakes. They are about new technical codes and information which give rise to revised conceptions of ontology, anthropology, epistemology, literacy, time and space. They are new systems of complex linkages between media, codes, expressions, consciousness, change and history. These ideas not only impact understanding of our world. They also revise orientations of truth values and identifications of moral spaces.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.058 | 0.010 |
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".