Bibliographic record
Abstract
‘Elastic 3D Spaces’ is a practice-based exploration of the medium of stereographic 3D and its effect on audiences. Over the five-year span of the project (2014 – 2019), Head created a series of installations, each developing the idea of the relationship between the body and stereographic space. Stereographic space implies the illusion of depth and immersion that 3D stereo provides. Head’s contribution to the overall collaborative project took the form of four art-based experiments, Symphony of Light, iMigration, Flow, Light Years VR, as well as co-organising a number of international exchange symposia. Head has created understanding about the impact the body (of the viewer) has with stereographic 3D, in terms of physicality, movement and sense of immersion. Starting at a publicly funded event, Illuminate 2015, (Arts Council England), the first event of the calendar of UNESCO International Year of Light 2015, Head created Symphony of Light, a large scale interactive stereo artwork, enabling the audience to move around the space in front of the projection. Flow developed this understanding with a sculptural form that changed in perceived scale depending on how/where the viewer was positioned. This work led to Head becoming an Immersion Fellow for South West Creative Technology Network (£16,000) where his investigations moved into virtual reality resulting in his creation of Light Years VR. Subsequent funding from the Canadian SSHRC Connections Grant (CA$30,000) for ‘Elastic 3D Spaces’ led to an international workshop and colloquium with Concordia University (2016/17). Further funding of CA$160,000 led to two symposium and further exchanges between Canada, the UK and a growing network involved with ‘Elastic 3D Spaces’. Head led a workshop on the topic for ISEA 2017 in Colombia. Following a presentation at ‘Besides the Screen’ (Coventry 2016), Head was invited to co-write a chapter in the related book published by Oxford University Press.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.112 | 0.019 |
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".