Wireless Affections: Embodiment and Emotions in New Media/Theory and Art
Bibliographic record
Abstract
A central strategy in selling information technology has involved the appropriation of earlier historical notions of the ether: as an immersive environment, communicative medium and electronic presence. Just as telephony was connected to the ‘wireless ether’, virtual reality and cyberspace have been connected to the idea of a virtual, electronic sphere, represented as an informatic space, through which a mode of (digital) being is conducted. However, as this paper will argue, while the data trails generated through ‘dataveillance’ technologies, or the information collected by wearable computers, may indeed situate the individual within a digitally rendered ‘ether’, these technologies are based on the generation of knowledge more than the creation of a space, installing an epistemological, rather than an ontological framework for understanding telepresent agency. With reference to recent works by Canadian artist Catherine Richards, this paper will discuss both research into new ‘reality mining’ and ‘affective computing’ technologies and the discourse of posthumanism, as it elaborates the transformation from autonomous liberal subject to post-human hybrid currently underway, and the developing relationships between humans and embodied, emotionally intelligent machines.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".