Implications of Cyberspace Communication: A Role for Physicians
Bibliographic record
Abstract
Through the presentation of three clinical case reports and subsequent discussion, it is demonstrated that physicians must begin to familiarize themselves with the health-related implications of online communication, and must proactively address Internet use as it relates to health and well-being. Included case presentations highlight the following: the established association between those seeking sexual partners through the Internet and an increased risk for sexually transmitted disease; the implications of cyber-communication for young people and concerns related to unsafe online behaviors including sharing identifying information with strangers; the potential use of strategically constructed virtual identities to facilitate sexual exploitation; the impact of accelerated intimacy and disinhibition evident in online communication; and the invasive nature of Internet sexual harassment or bullying. Although it is recognized that most online activities do not negatively affect health, doctors must be prepared to ask patients about Internet use and become involved in educating children, teenagers, and parents about safe online relationships to promote optimal physical, mental, and social health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.016 | 0.009 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".