Different strokes for different folk: Regulatory distinctions in New Zealand media
Bibliographic record
Abstract
For much of the past century there was broad acceptance of the stark contrast between the state’s involvement in the regulation of the content of broadcasting and its laissez-faire relationship with the columns of the press. The ‘failed market’ argument that substantiated regulation of the airwaves was difficult to counter. Fundamental changes in technology and media markets have, however, rendered the rationale open to challenge. Some aspects of the ‘failed market’, such as frequency scarcity, simply do not apply in the digital age. This article examines the nature of media regulation in New Zealand, noting its similarity to the dichotomous approach in Britain, Canada and Australia but also its divergence toward a more neoliberal market model that largely limits statutory oversight to matters that fall broadly into the categories of morals and ethics. It argues that, given the New Zealand government’s decision more than 15 years ago to forego regulation of ownership or the mechanisms that would serve the public good aspirations of a Reithian model, the continuing role of the state in regulation of broadcasting is questionable. A replacement model could be based on an effective regulatory body already present in the New Zealand media industry—the Advertising Standards Authority
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.
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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.028 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".