Bibliographic record
Abstract
Social media platforms provide opportunities for individuals to share information and express views through social media and other communication platforms. In recent years, there has been a surge in concern about the human rights impacts of ICT companies, including social media providers. The BHR regime, as well as its global applicability regardless of the national jurisdictions of actors and victims, provides the regime with important potential in regard to social media companies. We contribute to remedying that gap by focusing on human rights due diligence in relation to the posting and re-posting of photos of individuals that social media enables. We outline the key features of the UNGPs related to how business enterprises should identify and manage harmful human rights impact and engage with their business relations to do so. We provide examples from case law and social media usage reports on posting, deleting, and deleting photos and outline the features of social media provider business models that differ from those in sectors typi-cally associated with business-related human rights infringements. We discuss implications for the relationship between a social media company and its users and draw conclusions about the potential of the BHR.
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.
How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".