Safe and Responsible Internet Use in a Connected World: Promoting Cyber-Wellness
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
Cyber-wellness concerns positive wellbeing in online spaces, including awareness of how to behave appropriately and protect oneself. We explain and illustrate the complex nature of cyber-wellness, focusing on four key aspects. Firstly, developing students’ information and media literacy skills is essential for promoting cyber-wellbeing. Such skills are also required for supporting democratic participation. Secondly, we identify and discuss the threats and challenges to young people’s cyber-wellbeing, arguing for the need to develop digital resilience. Thirdly, we discuss the role of policy at macro, meso and micro levels and how policy and educational practitioners can promote cyber-wellness awareness, knowledge and strategies. Finally we review the limited scholarship on cyber-wellness education and highlight the need to address this gap in the future. We conclude the article with consideration of the issues faced and opportunities for overcoming these. It is imperative that further work is undertaken on the conceptualisation of cyber-wellness and that concensus is developed. There are issues relating to the continual rapid developments of techologies and their uses; it is important to develop a shared understanding of the mutual relationship between technology and humans. Finally, there is a lack of guidance and good practice exemplars for cyber-wellness education.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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