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
Proxemics theory explains peoples' use of interpersonal distances to mediate their social interactions with others. Within Ubicomp, proxemic interaction researchers argue that people have a similar social understanding of their spatial relations with nearby digital devices, which can be exploited to better facilitate seamless and natural interactions. To do so, both people and devices are tracked to determine their spatial relationships. While interest in proxemic interactions has increased over the last few years, it also has a dark side: knowledge of proxemics may (and likely will) be easily exploited to the detriment of the user. In this paper, we offer a critical perspective on proxemic interactions in the form of dark patterns: ways proxemic interactions can be misused. We discuss a series of these patterns and describe how they apply to these types of interactions. In addition, we identify several root problems that underlie these patterns and discuss potential solutions that could lower their harmfulness.
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 | 0.001 |
| Open science | 0.000 | 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