Setting the table doesn't mean the guests will come to dinner: televised courts in Australia
Bibliographic record
Abstract
The Australian courts are entering their second decade of experimentation with televised court proceedings. Yet, the process has been slow and largely unfulfilling for both the courts and the television networks. Developments in this field, compared to other countries, notably the United States, Canada and New Zealand, have progressed only on an ad hoc basis. A preliminary study indicates that the management in television newsrooms, notably news directors, have not been proactive in gaining camera access in any systematic or unified way. Indeed, the courts have argued: "we got the table set but nobody came to dinner". In contrast, the other countries mentioned above have all either introduced televised court proceedings on a reasonably regular basis, have undergone formal trial periods of allowing cameras in courts, or both. It is the proposition of this paper that the Australian scenario should be considered within the context of the free speech debate and the absence of a constitutional Bill or Charter of Rights, which guarantees a free media. This lack of a constitutional guarantee of free speech sets Australia at odds with these other three democratic countries.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".