Following Digital Media into the Courtroom: Publicity and the Open Court Principle in the Information Age
Bibliographic record
Abstract
Despite the pervasive integration of technology into various social institutions, one public body—the courtroom—has largely resisted such efforts. This separation is collapsing, however, as trial spectators increasingly arrive at court expecting to use their handheld digital devices inside to publish information about trials in real-time on live-blogging platforms. Consequently, Canadian courts have been forced to grapple with what role, if any, digital media is to play within their walls as this new information age puts pressure on a centuriesold legal tradition. This article examines the debate on the use of digital devices in the courtroom from the perspective of the “open court principle,” as articulated in both law and general jurisprudential theory. It argues that using digital media as a platform to disseminate courtroom narratives has the potential to strengthen many of the open court principle’s foundational values, including accessibility, judicial accountability, and freedom of speech. These benefits may nonetheless come at a cost to the open court’s normative functions, since multiple, non-linear courtroom narratives created by digital media can undermine the publication of clear, determinate norms around which people can structure their lives. Accordingly, this article suggests that in deciding whether to permit digital media use in the courtroom, the justice system must determine which of the democratic values that underpin the open court principle ought to be given decisive weight in modern society
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.081 |
| Scholarly communication | 0.034 | 0.018 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".