Defining the boundaries of journalism and news publishers: implications of the Online Safety Act 2023 for the public interest and media freedom
Bibliographic record
Abstract
This paper examines how provisions in the Online Safety Act 2023 (OSA), designed to protect journalism, may unintentionally create challenges to media freedom by enhancing platform power. By granting protections to news publisher content and journalistic content, the legislation requires platforms to determine who qualifies for these privileges, thereby making them gatekeepers of journalistic status. While news entities advocated for these provisions to protect themselves from content takedowns, we argue the OSA exemplifies what Tambini terms the ‘privilege paradox’ – where protecting journalism necessitates defining its boundaries, creating new ‘vectors of control’. Unlike jurisdictions such as Australia and Canada, which have established alternative mechanisms for determining what qualifies as journalism, the UK law places this power primarily with platforms. This approach, combined with questions about the enforceability of the OSA’s duty of care framework, may inadvertently strengthen the gatekeeping role of platforms over journalism rather than rebalancing power relations as intended.
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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 | 0.029 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.050 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.014 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 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".