Public Policy, Law, and Digital Media (Sample University-Level Course)
Bibliographic record
Abstract
Course Summary This course is for undergraduate students in the Faculty of Law, but may also be of interest to Master of Law students who are interested in public policy as it relates to new technologies. It is also valuable for graduate education students (school principals, senior teachers). Context, Rationale, and Objectives The goal of this course is to provide law students with an understanding of contemporary public policy challenges that have emerged with the rapid evolution of technologies and extensive adoption of digital forms of communication. Legal boundaries that were traditionally taken for granted have become increasingly blurred as policy makers in government, public institutions, and the corporate world attempt to balance free expression, privacy, protection, accountability, culpability, and regulation of online content. Students will consider questions about whether existing legal frameworks can adequately address and inform public policy, or whether public policy debates on uses of the Internet and digital media will inevitably re-shape the law. Why is a course on public policy and technology important for law students? There is currently much debate in the news media and academic and public forums on how we might better manage, control, monitor, regulate, and legislate online communication, particularly as it relates to social media and smart phones. Of particular concern in these policy debates are cases involving online hate, cyber-threats; cyberbullying; sexting; child pornography; trolling; identity theft; online extortion; and similar offenses. An alarming number of teen suicides resulting from cyberbullying and online rape culture have brought urgency to public policy agendas that call for increased and focused legislative action at both the federal and provincial levels.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.386 | 0.147 |
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".