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
Purpose To survey ambient intelligence research in Europe, the USA and Japan and, in particular, in the context of the issues of privacy, identity, security and trust and the safeguards proposed to protect them. Design/methodology/approach This paper is based on research being conducted by the SWAMI consortium under the EC's Sixth Framework Programme. SWAMI stands for Safeguards in a World of Ambient Intelligence. The consortium comprises five partners: the Fraunhofer Institute (Germany), the Technical Research Center of Finland (VTT Electronics), Vrije Universiteit Brussel (Belgium), the Institute for Prospective Technological Studies (IPTS) (Spain) and Trilateral Research & Consulting (UK). The 18‐month SWAMI project began in February 2005. Findings Most AmI projects do not take into account privacy, security and related issues. However, a reasonable number do (perhaps a quarter of those in Europe) to a greater or lesser extent and some have proposed safeguards. Research limitations/implications This paper references only a limited set of the research projects being carried out in Europe, the USA and Japan. More detailed information can be found on the SWAMI web site ( http://swami.jrc.es ). Practical implications A mix of different safeguards will be needed to adequately protect privacy, etc. in the new world of AmI. Originality/value Until now, there has been no reasonably comprehensive survey of AmI research projects in Europe, the USA and Canada focused on privacy, security, identity and trust issues. None has considered the range of safeguards needed to protect privacy, etc.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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