User Perceptions of Sharing, Advertising, and Tracking.
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
Extending earlier work, we conducted an online user study to investigate users’ understanding of online behavioral advertising (OBA) and tracking prevention tools (TPT), and whether users’ willingness to share data with advertising companies varied depending on the type of first party website. We presented results of 368 participant responses across four types of websites an online banking site, an online shopping site, a search engine and a social networking site. In general, we identified that participants had positive responses for OBA and that they demonstrated clear preferences for which classes of information they would like to disclose online. Our results generalize over a variety of website categories containing data with different levels of sensitivity, as opposed to only the medical context as was shown in previous work by Leon et al. In our study, participants’ privacy attitudes significantly dominated their sharing willingness. Interestingly, participants appreciated the idea of user-customized targeted ads and some would be more willing to share data if given prior control mechanisms for tracking protection tools.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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