To track or not to track? Employees’ data privacy in the age of corporate wellness, mobile health, and GDPR†
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
Journal Article To track or not to track? Employees' data privacy in the age of corporate wellness, mobile health, and GDPR Get access Céline Brassart Olsen Céline Brassart Olsen Céline Brassart Olsen, PhD, Postdoctoral Researcher, Faculty of Law, Copenhagen University, Karen Blixen Plads 16, Copenhagen, Denmark. Email: celine.brassart.olsen@jur.ku.dk. Search for other works by this author on: Oxford Academic Google Scholar International Data Privacy Law, Volume 10, Issue 3, August 2020, Pages 236–252, https://doi.org/10.1093/idpl/ipaa004 Published: 27 April 2020 Article history Received: 27 June 2019 Revision received: 15 January 2020 Accepted: 21 February 2020 Published: 27 April 2020
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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